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# Genetic algorithm and genetic programming system

## Subclass of:

## 706 - Data processing: artificial intelligence

## 706012000 - MACHINE LEARNING

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Document | Title | Date |
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20110184897 | Contingency planning system and method - A contingency planning system apparatus including a world description subsystem responsive to data representing a description of the world related to a planning problem and configured to instantiate a plurality of world codelets in a codelet workspace. A coderack subsystem is responsive to a slipnet network and is configured to instantiate a plurality of codelets in the codelet workspace each having one or more slots for binding with binding sites of lower level codelets and configured to monitor constraint changes thereto and propagate those changes to any related codelets. A temperature subsystem is configured to detect when temperature in the codelet workspace has reached a predetermined level indicating a satisfactory solution to the planning problem has been achieved. A plan extractor is responsive to the temperature subsystem and is configured to extract one or more contingency plans from the codelet workspace when the predetermined temperature is reached and configured to cause the temperature subsystem change the temperature in the codelet workspace such that the plurality of codelets will develop new bindings representing new solutions to the planning problem. | 07-28-2011 |

20090319455 | CONCURRENT TWO-PHASE COMPLETION GENETIC ALGORITHM MULTI-PROCESSOR INSTANCE SYSTEM - A genetic algorithm architecture implements a two-stage completion genetic algorithm with respect to an evolving current population data set. The two-stage completion genetic algorithm that includes genotype and phenotype completion loops. The genotype completion loop operates to compete the current population data set based on genotype field fitness scores. The genotype completion loop also implements a phenogenesis operator used to generate a current phenotype set. The phenotype completion loop operates, concurrently with the genotype completion loop, to evaluate the current phenotype set, constrained relative to the current population data set, against a fitness function to produce phenotype fitness scores. The phenotype completion loop implements a genotype reduction operator that then determines corresponding genotype fitness scores for use as the basis for competition in the genotype completion loop. | 12-24-2009 |

20090210366 | METHOD OF OPTIMIZING MULTIPLE PARAMETERS BY HYBRID GA, METHOD OF DATA ANALYSYS BY PATTERN MATCHING, METHOD OF ESTIMATING STRUCTURE OF MATERIALS BASED ON RADIATION DIFFRACTION DATA, PROGRAMS, RECORDING MEDIUM, AND VARIOUS APPARATUS RELATED THERETO - The present invention provides a Hybrid GA (HGA) in which local optimization operation is performed to only a few individual with lower fitness selected from each population of widely distributed generations in genetic algorithm (GA). Since this HGA shows very powerful global searching ability even in a vast multi-dimensional parameter space with strong multi-peak feature, the present invention may efficiently determine a number of structural parameters from a little information included in X-ray diffraction circles. As a result, the present invention may determine a complicated material structure from powder specimen even though it is hard to make a single crystal specimen. Thus, the development of new materials would be highly accelerated in the field of medicines or materials, etc. | 08-20-2009 |

20110196816 | MONEY ITEM ACCEPTOR - A method and system for accepting money items. The method for accepting money items comprises generating a money item signal that corresponds to a money item under test, determining a level of risk of a fraud attempt, and determining a fraud attempt based on the level of risk. The method further comprises generating a transformed money item signal as a function of the level of risk and the money item signal in response to determining the fraud attempt. The method further comprises comparing the transformed money signal to window limit values to generate a result and accepting or rejecting the money item based on the result. | 08-11-2011 |

20100076913 | FINDING COMMUNITIES AND THEIR EVOLUTIONS IN DYNAMIC SOCIAL NETWORK - Systems and methods are disclosed to find dynamic social networks by applying a dynamic stochastic block model to generate one or more dynamic social networks, wherein the model simultaneously captures communities and their evolutions, and inferring best-fit parameters for the dynamic stochastic model with online learning and offline learning. | 03-25-2010 |

20120246101 | Model for reconstructing a causation process from time varying data describing an event and for predicting the evolution dynamics of the event - A method of reconstructing a causation process from time varying data describing an event, the data consisting in a certain number of entities each having a position in a space, and each of the entities being characterized by at least a quantity or value relatively to at least one feature and in the quantity or value relatively to at least one of the features of the entities at least at two different times or at each time instant of a sequence of time instants; | 09-27-2012 |

20100042564 | TECHNIQUES FOR AUTOMATICALLY DISTINGUSIHING BETWEEN USERS OF A HANDHELD DEVICE - Various embodiments for automatically distinguishing between users of a handheld device are described. An embodiment includes collecting sensor data from a user interacting with a handheld device, where the sensor data is collected via embedded sensors in the handheld device. The embodiment further includes distinguishing the user from other users of the handheld device via the collected sensor data, at least one embedded machine learning algorithm and a profile for the user. Other embodiments are described and claimed. | 02-18-2010 |

20100161530 | METHOD FOR ENHANCED ACCURACY IN PREDICTING PEPTIDES ELUTION TIME USING LIQUID SEPARATIONS OR CHROMATOGRAPHY - A method for predicting the elution time of a peptide in chromatographic and electrophoretic separations by first providing a data set of known elution times of known peptides, then creating a plurality of vectors, each vector having a plurality of dimensions, and each dimension representing positional information about at least a portion of the amino acids present in the known peptides. A hypothetical vector is then created by assigning dimensional values for at least one hypothetical peptide, and a predicted elution time for the hypothetical vector is created by performing at least one multivariate regression fitting the hypothetical peptide to the plurality of vectors. Preferably, the multivariate regression is accomplished by the use of an artificial neural network and the elution times are first normalized using linear regression. | 06-24-2010 |

20090043719 | METHOD FOR SIMULATION OF HUMAN RESPONSE TO STIMULUS - A method is provided for simulating customer reaction to stimulus based on historical observable customer outcomes. Embodiments of the invention describe a series of steps that when taken together accomplish a predictive outcome of customer simulation from a plurality of source inputs without prior assumptions of relationship between inputs and simulated outcomes. The invention comprises a series of steps that effect the framing of the simulation model from which customer predicted outcomes are made. The various frames required to create the preferred simulation model include: customer database development, stimulus archetype development, model data development, model building, simulation of future customer reaction and suggested courses of action based on the results of the simulation. | 02-12-2009 |

20090327177 | SEMI-EXACT ALGORITHMS FOR OPTIMIZATION - Described herein is a meta-algorithm adaptable to different types of optimization problems and different computing platforms. A problem space is (i) browsed using a heuristic that computes objectives locally and (ii) while constructing a solution, key decisions are performed globally. A simple data structure—a probabilistic cache—is used to efficiently store intermediate sub-solutions. As an example, the meta-algorithm is applied to find an algorithm for solving the graph coloring problem. | 12-31-2009 |

20130073490 | CHOOSING PATTERN RECOGNITION ALGORITHMS AND DATA FEATURES - A system, method and program product for selecting an algorithm and feature set to solve a problem. A perpetual analytics system is disclosed that provides a genetic algorithm for jointly selecting an algorithm and feature set to solve a problem, comprising: an evolutionary computing engine for processing data encoded as chromosomes, wherein each chromosome encodes an algorithm and a feature set; a domain knowledge store that maintains a plurality of algorithms and a plurality of features; a system for applying a generation of chromosomes to a set of data to provide a set of results; and a fitness function for evaluating the set of results to rate a performance of each chromosome in the set of chromosomes; wherein the evolutionary computing engine is adapted to evolve a subset of the set of chromosomes into a new generation of chromosomes. | 03-21-2013 |

20090271341 | OPTIMIZATION PROCESSING METHOD USING A DISTRIBUTED GENETIC ALGORITHM - An optimization processing method comprises forming a plurality of islands each having a plurality of individuals and repeating crossover, mutation, evaluation and selection on the individuals until the desired condition has been satisfied by applying a genetic algorithm to each of the plurality of islands thereby obtaining an optimized solution, in which the optimized solution is obtained by migrating individuals to other islands. | 10-29-2009 |

20110047106 | CONSTUCTION OF TARGETED ADAPTIVE DESIGNS AND MAXIMUM LIKELIHOOD LEARNING FOR ADAPTIVE DESIGNS - In one embodiment, a method for targeted adaptive design processing is provided. The method comprises: determining data for a first stage of an adaptive design, each stage of the adaptive design being a set of experiments that are adapted based on a design mechanism, the data for a stage including data for the set of experiments for that stage; determining an estimator based on the data for the first stage; and analyzing the data using the estimator to adapt the design mechanism for a next stage of the adaptive design, the adaptive design mechanisms sign mechanism being considered more optimal to yield data for estimating a target parameter; and outputting the design mechanism for use in a second stage of the experiment. The method further comprises determining a second estimator for the adaptive design usable to estimate the target parameter of the adaptive design based on the analysis. | 02-24-2011 |

20120197829 | QUANTIFIED BELIEF PROPAGATION - A quantified belief propagation (QBP) algorithm receives as input an existentially quantified boolean formula (QBF) of existentially quantified boolean variables, universally quantified variables, and boolean operators. A tripartite graph is constructed, and includes (i) there-exists nodes that correspond to and represent the existentially quantified variables, (ii) for-all nodes that correspond to and represent the universally quantified variables, and (iii) sub-formula nodes that correspond to and represent sub-formulas of the QBF. A set of boolean values of the existentially quantified variables is found by (i) passing a first message from an arbitrary sub-formula node to an arbitrary for-all node, and (ii) in response, passing a second message from the arbitrary for-all node to the arbitrary sub-formula node. | 08-02-2012 |

20090234785 | SYSTEM AND METHOD FOR EXERCISING A REPRESENTATION TO INDICATE SOLUTIONS - A system for exercising a representation employing relationships among a plurality of input values to indicate solutions includes: an output controller unit coupled with the representation and presenting output values in response to receiving selected solutions from the representation; and an input controller unit coupled with the output controller unit and with the representation. The input controller unit presents a succession of the input values to the representation. The input controller unit receives indication of the output values from the output controller unit. The input controller unit selects the succession of input values in response to convergence by the output values. | 09-17-2009 |

20090037352 | System and method for automated determination of solutions to known equations - A system for automated determination of solutions to known equations, including a process orchestrator configured to retrieve at least one known solution from a known solutions datastore, a mathematics preprocessor configured to convert the at least one known solution to at least one machine-usable converted known solution, a genetic algorithm processor configured to generate at least one candidate solution from the at least one machine-usable converted known solution, and a results datastore configured to store a new solution corresponding to the candidate solution. There is also a method including retrieving at least one known solution from a known solutions datastore using a process orchestrator, converting convert the at least one known solution to at least one machine-usable converted known solution, generating at least one candidate solution from the at least one machine-usable converted known solution using a genetic algorithm processor, and storing a new solution corresponding to the candidate solution. | 02-05-2009 |

20090210367 | Method for Automatically Characterizing the Behavior of One or More Objects - Automatically characterizing a behavior of an object or objects by processing object data to obtain a data set that records a measured parameter set for each object over lime, providing a learning input that identifies when the measured parameter set of an object is associated with a behavior, processing the data set in combination with the learning input to determine which parameters of the parameter set over which range of respective values characterize the behavior; and sending information that identifies which parameters of the parameter set over which range of respective values characterize the behavior for use in a process that uses the characteristic parameters and their characteristic ranges to process second object data and automatically identify when the behavior occurs. Also disclosed is a method of tracking one or more objects. | 08-20-2009 |

20110289029 | AUTOMATIC MODEL EVOLUTION - A method comprising: performing on a processor, evaluating log data; determining at least one discrepancy between the log data and a system model; generating a candidate model based on the discrepancy and a model template; and updating the system model based on the candidate model. | 11-24-2011 |

20110295784 | ERROR CORRECTING METHOD OF TEST SEQUENCE, CORRESPONDING SYSTEM AND GENE ASSEMBLY EQUIPMENT - The present invention provides an error correcting method of test sequence, which involves receiving test sequences, configuring high frequency short string list based on a preset high frequency threshold value, traversing each received test sequence, searching an area with the largest number of continuous high frequency short strings on each test sequence in combination with high frequency short string list, configuring whole left sequence and/or right sequence of high frequency short strings at left side and/or right side of searched area according to corresponding received test sequence and high frequency short string list, and constituting corresponding test sequence according to configured left and/or right sequence and searched area. The present invention also provides corresponding error correcting system of test sequence and gene assembly equipment. | 12-01-2011 |

20120191635 | CLASSIFICATION TECHNIQUES FOR MEDICAL DIAGNOSTICS USING OPTICAL SPECTROSCOPY - Mathematical/statistical pattern-recognition systems and methods to distinguish between different pathologies and benign conditions (e.g., normal or cancerous tissue) given spectra measured using optical spectroscopy such as elastic-scattering spectroscopy (EES). | 07-26-2012 |

20120239601 | Restoration Switching Analysis with Genetic Algorithm - A method for generating switching plans to restore power to out-of-service areas after fault isolation through back feeding. A chromosome architecture is defined to create chromosomes representing candidate post-restoration systems. The chromosomes are evaluated are repeatedly genetically altered until an acceptable solution is identified. The solution identifies a plurality of switching operations that back feed power to the out-of-service areas in the most optimal manner. | 09-20-2012 |

20100161531 | MOLECLAR PROPERTY MODELING USING RANKING - Methods and articles of manufacture for modeling molecular properties using data regarding the partial orderings of compound properties, or by considering measurements of compound properties in terms of partial orderings are disclosed. One embodiment provides for constructing such partial orderings from data that is not already in an ordered form by processing training data to produce a partial ordering of the compounds with respect to a property of interest. Another embodiment of the invention may process the modified training data to construct a model that predicts the property of interest for arbitrary compounds. | 06-24-2010 |

20100268675 | METHOD AND DEVICE FOR AUTOMATED PALLETIZING OF PACKAGES TO FORM STABLE STACKS - A method for the automatic palletizing of stable package stacks includes the steps of virtual generation of multiple follow-up configurations by adding packages to at least one initial configuration, assessment of these follow-up configurations, and pursuit of follow-up configurations that are assessed as good as initial configurations. These steps are repeated until a termination criterion is satisfied. The follow-up configurations are assessed on the basis of different partial stack heights, towers and/or overbuildings. Another version of the method includes the steps of virtual generation of a package stack, and determination of a characteristic stability value of a package of a layer of a virtual package stack on the basis of the characteristic stability value of packages on which the package rests. | 10-21-2010 |

20090319454 | AUTOMATED LEARNING OF MODEL CLASSIFICATIONS - A method of providing an automated classifier for 3D CAD models wherein the method provides an algorithm for learning new classifications. The method enables existing model comparison algorithms to adapt to different classifications that are relevant in many engineering applications. This ability to adapt to different classifications allows greater flexibility in data searching and data mining of engineering data. | 12-24-2009 |

20090150313 | Vectorization of dynamic-time-warping computation using data reshaping - A method for comparing data sequences includes accepting first and second data sequences of data elements. A distance matrix is computed. The matrix includes rows and columns of matrix elements, describing distances between the data elements of the first sequence and the data elements of the second data sequence. The distance matrix is reshaped by applying successive, incremental shifts to the rows or columns so as to produce a reshaped matrix. A best-score path through the reshaped matrix is calculated using vector operations, so as to quantify a similarity between the first and second data sequences. Due to vectorization, a significant increase in computation speed is achieved in both software and hardware implementations. | 06-11-2009 |

20110264614 | Human Expert Assisted Evolutionary Computational Model - This invention outlines a method to extend computer-based evolutionary learning algorithms by supplementing with human reasoning rather than pure computational logic. Evolutionary algorithms such as genetic algorithms and neural networks are global search heuristics. These algorithms use techniques inspired by evolutionary biology such as inheritance, mutation, selection, crossover, neuronal pruning and adaption for identifying exact or approximate solutions to optimization and search problems. This invention discloses a method of allowing humans, who are experts in the domains of certain problems, to interact with and propose theories that are used as constraints to evolutionary algorithms and to provide feedback that may allow evolutionary algorithms to escape local minima during the evolutionary computing process. | 10-27-2011 |

20100293119 | SYSTEMS AND METHODS FOR PARALLEL PROCESSING OPTIMIZATION FOR AN EVOLUTIONARY ALGORITHM - The systems and methods may include receiving an initial population of parent chromosome data structures, where each parent chromosome data structure provides a plurality of genes; selecting pairs of parent chromosome data structures; applying at least one evolutionary operator to the genes of the selected pairs to generate a plurality of child chromosome data structures; allocating, the generated plurality of child chromosome structures to a plurality slave processors, where each slave processor evaluates one or more of the plurality of child chromosome data structures and generates respective objective function values; receiving objective function values for a portion of the plurality of allocated child chromosome data structures; merging the parent chromosome data structures with the received portion of the child chromosome data structures for which objective function values have been received; and identifying a portion of the merged set of chromosome data structures as an elite set of chromosome data structures. | 11-18-2010 |

20110137837 | INFORMATION PROCESSING APPARATUS, INFORMATION PROCESSING METHOD, AND PROGRAM - Provided is an information processing apparatus that prepares a processing method for data, that calculates an evaluation value of output data obtained in a case data is processed by the prepared processing method, by using an evaluator for calculating the evaluation value from the data, the evaluator being automatically created by using a plurality of data sets including data and an evaluation value of the data and performing a learning process based on a genetic algorithm, that repeatedly updates the processing method and calculates a processing method by which the evaluation value to be calculated will be higher, and that outputs, in a case the evaluation value of output data obtained in a case data is processed by the calculated processing method satisfies a predetermined condition, the output data, a combination of the output data and the processing method, or the processing method. | 06-09-2011 |

20100088258 | DYNAMIC INTELLIGENT OBJECTS - An contextual artificial intelligence system is disclosed. Intelligent business objects enable dynamic data object interaction and encapsulation of user context. Data is rationalized and data objects evolve by way of an artificial intelligence assisted process of self-discovery. Significant data is identified based upon factors such as cost, revenue and outcome and contextually significant result sets are automatically generated for users. | 04-08-2010 |

20110173145 | CLASSIFICATION OF A DOCUMENT ACCORDING TO A WEIGHTED SEARCH TREE CREATED BY GENETIC ALGORITHMS - A device for classifying a document comprises a module to generate a data tree structure and configured to assign terms to a first plurality of nodes of the data tree structure, where each of the first plurality of nodes is assigned a weight. In assigning the weights of the first plurality of nodes, a first generation of combinations of possible weights assignable as the weights of the first plurality of nodes is obtained, and a second generation of combinations of possible weights assignable as the weights of the first plurality of nodes is obtained by performing the genetic algorithms in the first generation of combinations of possible weights. The device determines whether the document is in a document class based at least the weights of the first plurality of nodes. | 07-14-2011 |

20110173144 | SYSTEM AND METHOD FOR CONSTRUCTING FORECAST MODELS - Embodiments of the present invention include a computational forecasting system that includes an identity of a dependent variable of interest and identities of a plurality of candidate indicators along with historical data or stored references to historical data, forecast-problem parameters stored in an electronic memory of the one or more electronic computers, an independent-variable selection component that generates correlations to the dependent variable of interest and lag times for the candidate indicators, and uses the generated correlations and lag times to select a number of the candidate indicators as a set of independent variables, and a model-generation component that, using a regression method, generates forecast models for the dependent variable of interest until a model that meets an acceptance criterion or criteria is obtained. | 07-14-2011 |

20090138417 | Parameter Adjustment Device - Efficient and high-accuracy parameter adjustment is performed by applying a genetic algorithm to a parameter adjustment such as a physical model of a transistor and so on. A parameter adjusting device includes a device generating new parameter genes by an initial population generating device and a special crossover processing by a Latin hyper square method. Also, a normalization device is provided for applying to parameters which are real numbers. Moreover, for example, to exactly meet a specific property of the transistor (MOSFET), an evaluation device which evaluates a parameter in consideration of a log scale, is provided. According to the above-mentioned structure, the genetic algorithm can be applied to the parameter adjustment with a large number of parameters such as the physical model of the transistor and so on, so that a parameter group can be determined with a high degree of accuracy within a short time. | 05-28-2009 |

20090287623 | METHOD AND APPARATUS FOR USING BAYESIAN NETWORKS FOR LOCALIZATION - The invention is a technique for performing sampling in connection with Markov Chain Monte Carlo simulations in which no attempt is made to limit the selected samples to a selected slice of the entire sample domain, as is typical in Markov Chain Monte Carlo sampling. Rather, samples are taken from the entire domain and any samples that fall below a randomly selected probability density level are discarded. | 11-19-2009 |

20100293122 | SYSTEMS AND METHODS FOR AN APPLICATION PROGRAM INTERFACE TO AN EVOLUTIONARY SOFTWARE PROGRAM - Systems and methods may include an application program interface that enables a user to: specify parameters associated with an evolutionary algorithm, where an execution of the evolutionary algorithm is in accordance with the specified parameters; define a chromosome data structure that includes a plurality of variables that are permitted to evolve in value in accordance with the execution of the evolutionary algorithm in order to generate one or more child chromosome data structures; identify one or more objective functions for evaluating chromosome data structures, including the generated one or more child chromosome data structures; and define an output format for providing one or more optimal chromosome data structures of the evaluated generated child chromosome data structures as designs to the identified objective functions. | 11-18-2010 |

20080243732 | Form-Based User Interface Tool for Specifying Time-Based, Distributed Algorithms for Distributed Systems - An apparatus for performing a distributed algorithm on a distributed system that comprises a plurality of components coupled together by a communication medium, comprises a user interface for permitting a user to enter a distributed algorithm specification that includes a time scale and tasks the components are to perform at specified times in the time scale; and a processor, coupled to receive the user-entered distributed algorithm specification and coupled to the distributed system on which the distributed algorithm is to be performed. The processor includes (i) a task generator for generating tasks for the respective components to perform according to a predetermined time line, and (ii) a distributor for distributing the tasks to the respective distributed system components. The respective distributed system components perform the distributed algorithm according to the distributed algorithm specification by (i) executing the respective tasks and (ii) communicating with each other over the communication medium. | 10-02-2008 |

20090265292 | OPTIMIZING OPERATIONS OF A HYDROGEN PIPELINE SYSTEM - Embodiments of the invention provide a computerized optimization system configured to optimize the operations of a hydrogen generation, processing, and delivery network. Such a network typically includes a complex of physical equipment, plants, and pipelines, including both production and distribution facilities. A hydrogen optimization system provides a software system that optimizes the production and distribution of hydrogen over such a hydrogen network. The hydrogen optimization system may use both a genetic algorithm configured to “evolve” a population of solutions to improve the quality of solutions over time as well as directed heuristics to identify a superior operating state for the hydrogen pipeline network. | 10-22-2009 |

20080313114 | SYSTEMS, METHODS, AND APPARATUS FOR RECURSIVE QUANTUM COMPUTING ALGORITHMS - A recursive approach to quantum computing employs an initial solution, determines intermediate solutions, evaluates the intermediate solutions and repeats using the intermediate solution, if the intermediate solution does not satisfy solution criteria. A best one of the intermediate solutions may be employed in the recursion. | 12-18-2008 |

20080270330 | Multi-Cellular Logic Circuits - A network performs an input-output function. The network includes a set of cells. Each cell has an identical structure, and neighboring cells are connected to each other to form a network. Each cell further includes a set of logic units configured to perform an input-output function, and in which the logic units output factor signals, inter-cellular signals and developmental output signals, the factor signals being input signals for the set of logic units in the same cell, the inter-cellular signals being input signals for the set of logic units in the neighboring cells, and the developmental output signals initiating development events, and in which developmental input signals to the logic units are set after the development events for the set of logic units in the same cell, and in which a structure of the set of logic units in each cell is identical. | 10-30-2008 |

20120296857 | Hardware acceleration of DNA codeword searching and fitness determination employing a code extender - An apparatus for a hybrid architecture that consists of a general purpose microprocessor and a hardware accelerator for accelerating the discovery of DNA reverse complement edit distance codes. An embodiment is implemented and evaluated, including a code extender that uses exhaustive search to produce locally optimum codes in about 1.5 hours for the case of length 16 codes. | 11-22-2012 |

20090313191 | Hardware design using evolution algorithms - The design of a hardware component such as a digital filter is optimized by taking an initial population of filter designs and encoding them as chromosomes. The fitness of each chromosome is then evaluated and parent chromosomes are then selected based on the fitness criteria. Offspring chromosomes are then generated using genetic operations such as mutation and cross-over from the pool of offspring, and optionally, parents. Individuals are selected to survive using a combination of Pareto fronts based on non-dominated individuals and clustering. The process is repeated or until a termination criteria is satisfied. | 12-17-2009 |

20090177600 | SYSTEM AND METHOD FOR COARSE-CLASSING VARIABLES IN A PREDICTIVE MODEL - A technique is provided to coarse-class one or more customer characteristics used in a predictive model. A set of functions are used to represent partition points of the customer characteristic into smaller classes. Each of the final classes of the customer characteristic is represented separately in the predictive model. An initial set of functions may be established to provide an initial set of partitions points of the customer characteristic. The set of functions is then processed using a genetic algorithm to evolve the partition points to new values. Processing the set of partitions using the genetic algorithm may continue until a stopping criterion is reached. | 07-09-2009 |

20090070280 | METHOD FOR PERFORMANCE BOTTLENECK DIAGNOSIS AND DEPENDENCY DISCOVERY IN DISTRIBUTED SYSTEMS AND COMPUTER NETWORKS - A method for performance bottleneck diagnosis and dependency discovery in distributed systems and computer networks includes receiving a real-valued end-to-end measurement matrix, a number of end-to-end measurements, a number of time points, a number of network components, a loss function, and a plurality of constraints on output matrices. The method further includes learning basic output matrices by best approximation of a transpose of the real-valued end-to-end measurement matrix, selecting a first threshold based on a real-valued mixing-weights matrix and a second threshold based on a real-valued delay matrix, converting the real-valued mixing-weights matrix and the real-valued delay matrix into respective binary matrices using the first threshold and the second threshold, and returning the real-valued mixing-weights matrix, the real-valued delay matrix, and the respective binary matrices to represent bottlenecks dependencies of the distributed system or computer network. | 03-12-2009 |

20090182692 | SYSTEM AND COMPUTER READABLE MEDIUM FOR DISCOVERING GENE REGULATORY MODELS AND GENETIC NETWORKS USING RELATIONAL FUZZY MODELS - A system and computer readable medium for discovering gene regulatory models using relational fuzzy models. A system is providing that includes a data selection system that clusters gene expression data into a set of clusters and identifies a representative subset of genes from the set of clusters; and a relational fuzzy modeling system that builds a relational fuzzy model using the representative subset. | 07-16-2009 |

20090177599 | SYSTEM AND METHOD FOR DEVELOPING A PROPENSITY MODEL - A technique is provided for developing a propensity model for customer behavior. Multiple biased samples of customer characteristics and results from past activities are established. Initial propensity models are created for each biased sample. The propensity models established for each biased sample are processed separately from the propensity models established for the other biased samples. A genetic algorithm is used to evolve the propensity models. A select number of propensity models that best fit their respective biased samples are compared to a validation sample that is unbiased. A select number of these propensity models that best fit the validation sample are cross-bred into the propensity models established for each biased sample. The propensity models for each biased sample are then processed again using the genetic algorithms. However, a number of elite propensity models are maintained in their original form and not evolved using the genetic algorithm. This cycle continues until a stopping criterion is reached. | 07-09-2009 |

20090177598 | METHOD FOR BUILDING PREDICTIVE MODELS WITH INCOMPLETE DATA - A method that imputes missing values while building a predictive model. A population of solutions is created using a data set comprising missing values, wherein each solution comprises parameters of each of the predictive models and the missing values of a data set. Each of the solutions in a population is checked for fitness. After the fitness is checked, the solutions in a population are genetically evolved to establish a successive population of solutions. The process of evolving and checking fitness is continued until a stopping criterion is reached. | 07-09-2009 |

20090327178 | CONCURRENT TWO-PHASE COMPLETION GENETIC ALGORITHM SYSTEM AND METHODS - A genetic algorithm architecture implements a two-stage completion genetic algorithm with respect to an evolving current population data set. The two-stage completion genetic algorithm that includes genotype and phenotype completion loops. The genotype completion loop operates to compete the current population data set based on genotype field fitness scores. The genotype completion loop also implements a phenogenesis operator used to generate a current phenotype set. The phenotype completion loop operates, concurrently with the genotype completion loop, to evaluate the current phenotype set, constrained relative to the current population data set, against a fitness function to produce phenotype fitness scores. The phenotype completion loop implements a genotype reduction operator that then determines corresponding genotype fitness scores for use as the basis for competition in the genotype completion loop. | 12-31-2009 |

20110225110 | Software control of hardware accelerated DNA codeword searching - An apparatus for a hybrid architecture that consists of a general purpose microprocessor and a hardware accelerator for accelerating the discovery of DNA reverse complement, edit distance codes. Two embodiments are implemented and evaluated, including a code generator that uses a genetic algorithm (GA) to produce nearly locally optimal codes in a few minutes, and a code extender that uses exhaustive search to produce locally optimum codes in about 1.5 hours for the case of length 16 codes. Experimental results demonstrate that the GA embodiment can find ˜99% of the words in locally optimum libraries, and that the hybrid architecture embodiment provides more than 1000 times speed-up compared to a software only implementation. | 09-15-2011 |

20110225109 | Hardware acceleration of DNA codeword searching and fitness determination - An apparatus for a hybrid architecture that consists of a general purpose microprocessor and a hardware accelerator for accelerating the discovery of DNA reverse complement, edit distance codes. Two embodiments are implemented and evaluated, including a code generator that uses a genetic algorithm (GA) to produce nearly locally optimal codes in a few minutes, and a code extender that uses exhaustive search to produce locally optimum codes in about 1.5 hours for the case of length 16 codes. Experimental results demonstrate that the GA embodiment can find ˜99% of the words in locally optimum libraries, and that the hybrid architecture embodiment provides more than 1000 times speed-up compared to a software only implementation. | 09-15-2011 |

20080262988 | Vertical curve system for surface grading - A method is disclosed that generates design profiles and a surface therefrom that promote water drainage from soil in an area of interest. Topographical data describing an initial surface of the area of interest are used to form initial profiles. The method generates the design profiles using the initial profiles and desired design parameters such as minimum slope, maximum slope, optimal slope, maximum depth, optimal depth, starting elevation, ending elevation, rules of curvature, and rules of earth balancing. The method generates design surface profiles so that the cut volumes and fill volumes of the soil are at or near balance as much as possible from the available soil in the area of interest. | 10-23-2008 |

20110029468 | METHOD OF GENERATING AN OPTIMIZED, DIVERSE POPULATION OF VARIANTS - The present disclosure relates to methods of rapidly and efficiently searching biologically-related data space to identify a population set maximally diverse and optimized for sets of desired properties. More specifically, the disclosure provides methods of identifying a diverse, evolutionary separated bio-molecules with desired properties from complex bio-molecule libraries. The disclosure additionally provides digital systems and software for performing these methods. | 02-03-2011 |

20080319928 | Method, computer, and recording medium storing a program for computing an optimal solution to engine design variables - A method, computer, and recording medium storing a program are provided which, based on local optimal solutions, more efficiently calculate an optimal global optimal solution in a global operating area. System calculates the global optimal solution by solving, using a genetic algorithm based on the local optimal solutions and the initial values, an equation, which should be satisfied by the plurality of design variables, by obtaining the plurality of combinations of design variables composing local optimal solutions for each design variable respectively calculated for each of a plurality of combinations of a plurality of operating states, and by obtaining initial values for the plurality of combinations of design variables used for calculating the global optimal solution. | 12-25-2008 |

20110125683 | Identification of Co-Regulation Patterns By Unsupervised Cluster Analysis of Gene Expression Data - A method is provided for unsupervised clustering of gene expression data to identify co-regulation patterns. A clustering algorithm randomly divides the data into k different subsets and measures the similarity between pairs of datapoints within the subsets, assigning a score to the pairs based on similarity, with the greatest similarity giving the highest correlation score. A distribution of the scores is plotted for each k. The highest value of k that has a distribution that remains concentrated near the highest correlation score corresponds to the number of co-regulation patterns. | 05-26-2011 |

20090106177 | INFORMATION PROCESSING DEVICE, INFORMATION PROCESSING METHOD, AND PROGRAM - An information processing device for generating a target feature amount computational expression for outputting a target feature amount corresponding to input data, comprising: a feature amount extraction expression list generating unit configured to generate and update a feature amount extraction expression list; a feature amount computing unit configured to input actual data supplied as tutor data to each feature amount extraction expression included in the feature amount extraction expression list to compute multiple feature amounts corresponding to the actual data; a target feature amount computational expression generating unit configured to employ the multiple feature amounts, and an existing feature amount corresponding to the actual data supplied as tutor data for the same rank to generate the target feature amount computational expression by machine learning; and an evaluation value computing unit configured to compute the evaluation value of each feature amount extraction expression included in the feature amount extraction expression list. | 04-23-2009 |

20090106176 | INFORMATION PROCESSING APPARATUS, INFORMATION PROCESSING METHOD, AND PROGRAM - An information processing apparatus for generating an algorithm determining a similarity between a pair of data. The apparatus includes: a feature-quantity-extraction expression list generation mechanism generating a feature-quantity-extraction expression list including a plurality of feature-quantity-extraction expressions including a plurality of operators by updating the feature-quantity-extraction expression list of a preceding generation; a calculation mechanism inputting first and second data given as teacher data into each of the feature-quantity-extraction expressions included in the feature-quantity-extraction expression list to calculate a feature quantity corresponding to each of the first and the second data; an evaluation-value calculation mechanism calculating the evaluation value of each of the feature-quantity-extraction expressions using the calculated feature quantities and a similarity between the first and the second data given as the teacher data; and a similarity-calculation expression estimation mechanism estimating a similarity calculation expression for calculating a similarity between the first and the second data given as the teacher data. | 04-23-2009 |

20090222390 | Method, program and apparatus for generating two-class classification/prediction model - A method includes: a) preparing as training data a sample set that contains a plurality of samples belonging to a first class and a plurality of samples belonging to a second class; b) generating, by performing discriminant analysis on the sample set, a first discriminant function having a high classification characteristic for the first class and a second discriminant function having a high classification characteristic for the second class; c) by classifying the sample set using the first and second discriminant functions, isolating any sample whose classification results by the first and second discriminant functions do not match; d) forming a new sample set by grouping together any sample thus isolated, and repeating b) and c) by using the new sample set; and e) causing d) to stop when the number of samples each of whose classification results do not match in c) has decreased to or below a predetermined value. | 09-03-2009 |

20120197830 | EVOLUTIONARY COMPUTING BASED OPTIMIZATION - Methods and apparatuses for performing evolutionary based optimization are described. Specifically, some embodiments feature: a dominance archive, auto-adaptive operators, detection of search stagnation, exploitation of randomized restarts to escape local optima, and/or selection of recombination operators based on their success in generating high quality solutions. | 08-02-2012 |

20090248598 | Hardware acceleration of DNA codeword searching - An apparatus for a hybrid architecture that consists of a general purpose microprocessor and a hardware accelerator for accelerating the discovery of DNA reverse complement, edit distance codes. Two embodiments are implemented and evaluated, including a code generator that uses a genetic algorithm (GA) to produce nearly locally optimal codes in a few minutes, and a code extender that uses exhaustive search to produce locally optimum codes in about 1.5 hours for the case of length 16 codes. Experimental results demonstrate that the GA embodiment can find ˜99% of the words in locally optimum libraries, and that the hybrid architecture embodiment provides more than 1000 times speed-up compared to a software only implementation. | 10-01-2009 |

20090132448 | Segmented predictive model system - An automated method and system ( | 05-21-2009 |

20120123980 | OPTIMIZATION TECHNIQUE USING EVOLUTIONARY ALGORITHMS - Provided embodiments include a method, a system, a device, and an article of manufacture. A system for terminating a genetic algorithm (GA), where the GA uses an iterator and generates one best solution per iteration, includes a memory, an iterative processor, and a terminating processor. The memory is provided for storing a plurality of best solutions generated in a plurality of iterations of the GA. One of the best solutions generated in one of the iterations is stored in the memory if the one of the best solutions is better than a previous one of the best solutions generated in a previous one of the iterations. The iterative processor computes a variance of the plurality of the best solutions stored in the memory. The terminating processor terminates the iterator when the variance is less than or equal to a predetermined threshold. | 05-17-2012 |

20080215513 | METHODS FOR FEATURE SELECTION IN A LEARNING MACHINE - In a pre-processing step prior to training a learning machine, pre-processing includes reducing the quantity of features to be processed using feature selection methods selected from the group consisting of recursive feature elimination (RFE), minimizing the number of non-zero parameters of the system (l | 09-04-2008 |

20100153321 | FRAMEWORK OF HIERARCHICAL SENSORY GRAMMARS FOR INFERRING BEHAVIORS USING DISTRIBUTED SENSORS - Provided herein are methods, systems, and apparatuses that can utilize a grammar hierarchy to parse out observable activities into a set of distinguishable actions. | 06-17-2010 |

20100145897 | GENOMIC CLASSIFICATION OF MALIGNANT MELANOMA BASED ON PATTERNS OF GENE COPY NUMBER ALTERATIONS - The invention is directed to methods and kits that allow for classification of malignant melanoma cells according to genomic profiles, and methods of diagnosing, predicting clinical outcomes, and stratifying patient populations for clinical testing and treatment using the same. | 06-10-2010 |

20100235309 | METHOD OF CONTROLLING A LIGHTING SYSTEM BASED ON A TARGET LIGHT DISTRIBUTION - The invention relates to a method of controlling a lighting system with multiple controllable light sources | 09-16-2010 |

20090043718 | Evolutionary hypernetwork classifiers for microarray data analysis - The present invention is to identify the gene modules associated with cancers from microarray data using the evolved hypernetwork classifier. | 02-12-2009 |

20100250475 | Tensor voting in N dimensional spaces - A tensor voting scheme which can be used in an arbitrary number N of dimensions, up to several hundreds. The voting scheme can operate on unorganized point inputs, which can be oriented or unoriented, and estimate the intrinsic dimensionality at each point. Moreover it can estimate the tangent and normal space of a manifold passing through each point based solely on local operations. | 09-30-2010 |

20100250476 | EVALUATION OF RISK OF CONFLICT FOR SECURITY SOLUTIONS INTEGRATION - A method and a system for evaluation of risk of conflict between a number of integrating security solutions. In a computer system, a number of fragmentary security solutions are received. A set of the received fragmentary security solutions is integrated to form a composite security solution to satisfy a number of security requirements. In one aspect, the security requirements are established during a design of a computer system. A risk of conflict between the set of integrating fragmentary security solutions is evaluated. In another aspect, the risk of conflict between the set of integrating fragmentary security solutions exists at authority level and at configuration level. Conflict at authority level arises when different authorities control the same fragmentary security solution. Conflict at configuration level arises when integrating fragmentary security solutions share configuration data. | 09-30-2010 |

20100205127 | METHOD FOR PLANNING A SEMICONDUCTOR MANUFACTURING PROCESS BASED ON USERS' DEMANDS - A method for planning a semiconductor manufacturing process based on users' demands includes the steps of: establishing a genetic algorithm model and inputting data; establishing a fuzzy system and setting one output parameter representing percent difference of each cost function in neighbor generations; setting to have a modulation parameter corresponding to each input parameter for adjusting fuzzy sets of the output parameter; executing genetic algorithm actions; executing fuzzy inference actions; eliminating chromosomes that produce output parameter smaller than a defined lower limit, and the remaining chromosomes that produces the largest output parameter is defined as the optimum chromosome, wherein the genetic algorithm actions stops being executed upon the optimum chromosome; then determining whether or not a defined number of generations has been reached, if yes, executing the optimum chromosome of the last generation; if no, continuing executing the genetic algorithm actions, thereby finding the optimum semiconductor manufacturing process for users. | 08-12-2010 |

20100114805 | Quantum entity state processing system & method - Systems and methods are described for processing quantum entity states by utilizing interference phenomena, and more specifically self-interference outcomes. The quantum entity states are embodiable in fermions and/or bosons, expressly including photons. Certain embodiments can utilize input quantum entity states that encompass one or more separable quantum entities and can be arranged to produce predictable outcome differences that are alterable in accordance with differences and/or similarities between separate input quantum entities. Additional outcome alterations are effectible via static and/or dynamic quantum entity state influencing constituents. Even further outcome alterations are effectible by associative quantum state influencing constituents that are additionally utilizable for interrelating separable embodiments. Interrelations of separable embodiments are achievable as well by employing at least a portion of at least a first outcome quantum entity state as an intermediary or a final interactor with at least a portion of a differing separable embodiments' quantum entity state. | 05-06-2010 |

20110112998 | METHODS AND SYSTEMS FOR VARIABLE GROUP SELECTION AND TEMPORAL CAUSAL MODELING - A “variable group selection” system and method in which constructs are based upon a training data set, a regression modeling module that takes into account information on groups of related predictor variables given as input and outputs a regression model with selected variable groups. Optionally, the method can be employed as a component in methods of temporal causal modeling, which are applied on a time series training data set, and output a model of causal relationships between the multiple times series in the data. | 05-12-2011 |

20100191685 | Methods and systems for feature selection in machine learning based on feature contribution and model fitness - Methods and systems are provided for feature selection in machine learning, in which the features selected for inclusion in a prediction rule are selected based on statistical metric(s) of feature contribution and/or model fitness. | 07-29-2010 |

20090319453 | Sampling Strategy Using Genetic Algorithms in Engineering Design Optimization - A sampling strategy using genetic algorithms (GA) in engineering design optimization is disclosed. A product is to design and optimize with a set of design variables, objectives and constraints. A suitable number of design of experiments (DOE) samples is then identified such that each point represents a particular or unique combination of design variables. The sample selection strategy is based on genetic algorithms. Computer-aided engineering (CAE) analysis or analyses (e.g., finite element analysis, finite difference analysis, mesh-free analysis, etc.) is/are performed for each of the samples during the GA based sample selection procedure. A meta-model is created to approximate the CAE analysis results at all of the DOE samples. Once the meta-model is satisfactory (e.g., accuracy within a tolerance), an optimized “best” design can be found by using the meta-model as function evaluator for the optimization method. Finally, a CAE analysis is performed to verify the optimized “best” design. | 12-24-2009 |

20080228677 | Identifying Co-associating Bioattributes - A bioinformatics method, software, database and system are presented in which combinations of bioattributes comprising pangenetic and non-pangenetic attributes that co-associate with a query attribute (i.e., an attribute of interest) are identified from a database containing attribute combinations and corresponding frequencies of occurrence of each of the attribute combinations for a group of query-attribute-positive individuals and for a group of query-attribute-negative individuals. | 09-18-2008 |

20100306141 | Method for transforming data elements within a classification system based in part on input from a human annotator/expert - A method and system are provided for classifying data items such as a document based upon identification of element instances within the data item. A training set of classes is provided where each class is associated with one or more features indicative of accurate identification of an element instance within the data item. Upon the identification of the data item with the training set, a confidence factor is computed that the selected element instance is accurately identified. When a selected element instance has a low confidence factor, the associated features for the predicted class are changed by an annotator/expert so that the changed class definition of the new associated feature provides a higher confidence factor of accurate identification of element instances within the data item. | 12-02-2010 |

20100332429 | SYSTEM AND METHOD FOR OPTIMIZING A SEQUENTIAL ARRANGEMENT OF ITEMS - A system optimizing a sequence according to an algorithm includes: an initiator; a tracker; a generator; a measurer; a regulator; and an output. The initiator provides initial sequences to the tracker. The tracker stores and effects a statistical treatment of the initial sequences. The generator employs the statistical treatment to present a new sequence. The measurer evaluates the new sequence according to the algorithm. The measurer provides the new sequence to the tracker when the evaluating indicates so, and provides the new sequence and a quality indicator to the regulator. The regulator employs the indicator to store at least a best-sequence-yet-received, and responds to a criterion to order the generator to present a new sequence or to present the best-sequence-yet-received at the output. | 12-30-2010 |

20110029467 | FACILITY FOR RECONCILIATION OF BUSINESS RECORDS USING GENETIC ALGORITHMS - A facility for the reconciliation of data records pertaining to business entities. One or more fitness functions are applied to fields contained in two conflicting data records to assess the similarity of each field. The results of the fitness functions are then weighted and combined to assess the likelihood that the two data records are associated with the same business entity. When the weighted fitness functions are applied to conflicting data records, the fitness functions generate a confidence level that the compared records are associated with the same business entity. If the confidence level exceeds a certain threshold, the facility accepts that the data records refer to the same business entity and synthesizes a business record from the data records. | 02-03-2011 |

20110213741 | SYSTEMS AND METHODS FOR GENERATING LEADS IN A NETWORK BY PREDICTING PROPERTIES OF EXTERNAL NODES - The present invention is directed towards systems and methods for predicting one or more desired properties of external nodes or properties of their relations with internal nodes, based on a selected group of nodes about which it is known whether the nodes have the desired properties, or it is known whether they have a desired relation property with an internal node. The method comprises storing in one or more data structures a first data set regarding external nodes and a second data set regarding nodes with known properties in a selected group, each data set having one or more data items representing one or more events relating to or attributes of each node in the data set, the second data set including one or more types of data items not included in the first data set. The method then models the second data set to identify from the second data one or more modeled events or attributes of internal nodes in the selected group that are statistically likely to identify the nodes or their relations, that have the desired properties and predicts which of the external nodes are statistically likely to have the one or more desired properties, or desired relation property with internal node, based on the identified plurality of modeled events or attributes and the events or attributes in the first data set. | 09-01-2011 |

20090313193 | HIERARCHICAL TEMPORAL MEMORY SYSTEM WITH HIGHER-ORDER TEMPORAL POOLING CAPABILITY - A temporal pooler for a Hierarchical Temporal Memory network is provided. The temporal pooler is capable of storing information about sequences of co-occurrences in a higher-order Markov chain by splitting a co-occurrence into a plurality of sub-occurrences. Each split sub-occurrence may be part of a distinct sequence of co-occurrences. The temporal pooler receives the probability of spatial co-occurrences in training patterns and tallies counts or frequency of transitions from one sub-occurrence to another sub-occurrence in a connectivity matrix. The connectivity matrix is then processed to generate temporal statistics data. The temporal statistics data is provided to an inference engine to perform inference or prediction on input patterns. By storing information related to a higher-order Markov model, the temporal statistics data more accurately reflects long temporal sequences of co-occurrences in the training patterns. | 12-17-2009 |

20100036782 | METHODS FOR FEATURE SELECTION USING CLASSIFIER ENSEMBLE BASED GENETIC ALGORITHMS - Methods for performing genetic algorithm-based feature selection are provided herein. In certain embodiments, the methods include steps of applying multiple data splitting patterns to a learning data set to build multiple classifiers to obtain at least one classification result; integrating the at least one classification result from the multiple classifiers to obtain an integrated accuracy result; and outputting the integrated accuracy result to a genetic algorithm as a fitness value for a candidate feature subset, in which genetic algorithm-based feature selection is performed. | 02-11-2010 |

20090048991 | Apparatus and Method for Processing Information, Recording Medium and Computer Program - An information processing apparatus includes a target problem acquisition unit for acquiring a target problem, a generation unit for generating a plurality of solution candidates to the target problem to solve the target problem, and a contribution ratio calculating unit for calculating a contribution ratio of each solution candidate to the target problem if the target problem is solved using all the plurality of solution candidates to the target problem acquired by the target problem acquisition unit. The generation unit generates a solution candidate to the target problem in a next generation in accordance with a genetic algorithm that uses an evaluation value that is calculated using at least the contribution ratio of each solution candidate to the target problem determined by the contribution ratio calculating unit. | 02-19-2009 |

20090313192 | EVOLUTIONARY FACIAL FEATURE SELECTION - An evolutionary feature selection system and method that determines a feature space for a dataset. A system is disclosed that includes: a system for generating a plurality of chromosomes; an agglomerative K-means clustering system for clustering data into clusters, wherein each of the cluster spaces is associated with a different one of the chromosomes; a linear discriminant analysis system for scoring each of the cluster spaces; and an evolutionary mating system that genetically mutates and mates at least two of the chromosomes associated with the highest scoring cluster spaces, and generates a final chromosome. The final chromosome can thereafter be used to define a feature space in a matching system that attempts to match inputted biometric data with entries in a biometric dataset. | 12-17-2009 |

20100131439 | BIT-SELECTION FOR STRING-BASED GENETIC ALGORITHMS - Selecting bits in a string-based genetic algorithm is provided. A type of genetic operation to perform is determined. Responsive to a determination to perform a crossover operation, an input comprising a pair of strings is received. The strings in the pair of strings are compared to identify a set of non-matching points. A set of points from the set of non-matching points is randomly selected, forming a set of randomly selected non-matching points. A new string for the pair of strings is generated using the set of randomly selected non-matching points. | 05-27-2010 |

20090216695 | System and method for constructing cognitive programs - The present invention is directed to a method to search for a solution to a problem in a domain. The method may comprise obtaining a plurality of agents each operable to produce one or more numerical bids and to propose one or more actions and a plurality of nodes each representing a state of the domain; automatically selecting a respective agent and a respective node based on a bids from the plurality of agents; and automatically adding a new node representing a new state which is obtained by applying to the state represented by the selected node an action proposed by the selected agent. The plurality of nodes may each have a depth associated therewith and the respective agent and the respective node may be selected regardless of the depth associated with the selected node. | 08-27-2009 |

20110082821 | Method of generating precedence-preserving crossover and mutation operations in genetic algorithms - A method for generating precedence-preserving crossover and mutations operations for genetic algorithms is provided. The method is based on the determination of activities' Forward Free Float (FFF) and Backward Free Float (BFF) values, utilizing these float values in randomly selected forward and backward paths, respectively. The method may be applied to the finance-based scheduling domain using large scale projects, with the chromosomes of the genetic algorithm encoding activities' start times in a resource-constrained scheduling problem. | 04-07-2011 |

20110099136 | METHOD AND SYSTEM FOR CONCURRENT EVENT FORECASTING - A method and system for characterizing, detecting, and predicting or forecasting multiple target events from a past history of these events includes compressing temporal data streams into self-organizing map (SOM) clusters, and determining trajectories of the temporal streams via the clusters to predict the multiple target events. The system includes an evolutionary multi-objective optimization (EMO) module for processing the temporal data streams, which are obtained from a plurality of heterogeneous domains; a SOM module for characterizing the temporal data streams into self-organizing map clusters; and a target event prediction (TEP) module for generating prediction models of the map clusters. The SOM module employs a vector quantization method that places a set of vectors on a low-dimensional grid in an ordered fashion. The prediction models each include trajectories of the temporal data streams, and the system predicts the multiple target events using the trajectories. | 04-28-2011 |

20110078100 | METHODS AND SYSTEMS FOR MULTI-OBJECTIVE EVOLUTIONARY ALGORITHM BASED ENGINEERING DESGIN OPTIMIZATION - The present invention discloses systems and methods of conducting multi-objective evolutionary algorithm (MOEA) based engineering design optimization of a product (e.g., automobile, cellular phone, etc.). Particularly, the present invention discloses an archive configured for monitoring the progress and characterizing the performance of the MOEA based optimization. Further, an optimization performance indicator is created using the archive's update history. The optimization performance indicator is used as a metric of the current state of the optimization. Finally, a stopping or termination criterion for the MOEA based optimization is determined using a measurement derived from the optimization performance indicators. For example, a confirmation of a “knee” formation has developed in the optimization performance indicators. The optimization performance indicators include, but are not limited to, consolidation ratio, improvement ratio, hypervolume. | 03-31-2011 |

20120303560 | SYSTEM AND METHOD FOR DEVELOPMENT OF A SYSTEM ARCHITECTURE - Methods, systems, and computer readable medium for developing a system architecture that involves defining resources constraints for kinds of resources and constraint values for optimization parameters, and defining a design space as variants, where each variant is a vector. Satisfying sets of variants are determined for optimization parameters by assigning membership values to each variant of the universe of discourse and performing a fuzzy search of the universe of discourse set using the corresponding membership values. A set of variants is determined based on an intersection of the satisfying sets of variants. An ordered list of variants is generated by sorting the set of variants and a variant is selected based on the position of the variant in the ordered list for use in developing the system architecture. | 11-29-2012 |

20110060710 | QUANTUM AND DIGITAL PROCESSOR HYBRID SYSTEMS AND METHODS TO SOLVE PROBLEMS - Quantum and digital processors are employed together to solve computational problems. The quantum processor may be configured with a problem via a problem Hamiltonian and operated to perform adiabatic quantum computation and/or quantum annealing on the problem Hamiltonian to return a first solution to the problem that is in the neighborhood of the global minimum of the problem Hamiltonian. The digital processor may then be used to refine the first solution to the problem by casting the first solution to the problem as a starting point for a classical optimization algorithm. The classical optimization algorithm may return a second solution to the problem that corresponds to a lower energy state in the neighborhood of the global minimum, such as a ground state of the problem Hamiltonian. The quantum processor may include a superconducting quantum processor implementing superconducting flux qubits. | 03-10-2011 |

20100306142 | METHODS OF ADIABATIC QUANTUM COMPUTATION - A method for quantum computing using a quantum system comprising a plurality of qubits is provided. The system can be in any one of at least two configurations at any given time including one characterized by an initialization Hamiltonian H | 12-02-2010 |

20110251983 | METHODS FOR THE SURVEY AND GENETIC ANALYSIS OF POPULATIONS - The present invention relates to methods for performing surveys of the genetic diversity of a population. The invention also relates to methods for performing genetic analyses of a population. The invention further relates to methods for the creation of databases comprising the survey information and the databases created by these methods. The invention also relates to methods for analyzing the information to correlate the presence of nucleic acid markers with desired parameters in a sample. These methods have application in the fields of geochemical exploration, agriculture, bioremediation, environmental analysis, clinical microbiology, forensic science and medicine. | 10-13-2011 |

20120203722 | APPARATUS AND METHOD FOR PROCESSING INFORMATION, RECORDING MEDIUM AND COMPUTER PROGRAM - An information processing apparatus includes a target problem acquisition unit for acquiring a target problem, a generation unit for generating a plurality of solution candidates to the target problem to solve the target problem, and a contribution ratio calculating unit for calculating a contribution ratio of each solution candidate to the target problem if the target problem is solved using all the plurality of solution candidates to the target problem acquired by the target problem acquisition unit. The generation unit generates a solution candidate to the target problem in a next generation in accordance with a genetic algorithm that uses an evaluation value that is calculated using at least the contribution ratio of each solution candidate to the target problem determined by the contribution ratio calculating unit. | 08-09-2012 |

20120203721 | SYSTEM AND METHOD FOR EFFICIENT INTERPRETATION OF NATURAL IMAGES AND DOCUMENT IMAGES IN TERMS OF OBJECTS AND THEIR PARTS - Methods and system employing the same for optimizing an objective function are provided. The objective function assesses the quality of a candidate solution. One or more variables of an objective function are selected as pivot variables. Each of the variables include one or more candidate values. An upper bound function is generated from the objective function, where the pivot variables are held fixed. For each combination of the candidate values, one or more candidate solutions are searched using the upper bound function. One or more optimal solutions are selected from among the solutions to the searches. | 08-09-2012 |

20110161264 | OPTIMIZED SEEDING OF EVOLUTIONARY ALGORITHM BASED SIMULATIONS - Seed candidate solutions can be inserted into the later generations of the population of an optimization problem during an evolutionary algorithm based simulation. Seed candidate solutions can be determined in response to an evolutionary algorithm based simulator receiving a problem description of an optimization problem. The seed candidate solutions can be sorted according to the seed candidate solutions' fitness. The simulator can start an evolutionary algorithm based simulation with a randomly generated initial population. The simulator can detect a condition for inserting seed candidate solutions into the population. The simulator can then insert the first seed candidate into the current population that is generated by the simulator in accordance with the evolutionary algorithm. A solution to the optimization problem can be determined based on successive generation of candidate solutions and insertion of additional seed candidate solutions in subsequent generations of the population. | 06-30-2011 |

20080256006 | Clinical Trial Phase Simulation Method and Clinical Trial Phase Simulator For Drug Trials - A clinical trial phase simulation method for drug trials, which method allows to predict the trend of the results of a clinical trial phase of a drug with the steps of providing a database comprising for each of a certain number of individuals a predefined number of independent variables each of which corresponds to a certain clinical parameter relevant or characteristic for a disease condition against which the drug to be tested is oriented and at least a further independent variable describing the specific treatment to which the individual has been subjected between at least two different treatments one with the said drug and the second with a placebo or with another known drug, the database comprising also for each individuals one or more dependent variables describing the effects of the said treatments; carryings out an input variable selection; adding to the independent variables selected as input variables the dependent variables describing the effects of the treatments; training and validating an artificial neural network with the selected variables as input variables and with the dependent variables; interrogating the said neural network by inputting the values of the variable describing one of the treatments and obtaining as an output the variable values of the effectiveness of the treatment to which the inputted values of the variable of the treatment correspond according to the trained artificial neural network. | 10-16-2008 |

20110055128 | PREDICTING PHENOTYPES USING A PROBABILISTIC PREDICTOR - Aspects of the subject matter described herein relate to predicting phenotypes. In aspects, a probabilistic predictor is used to summarize a relationship between a set of biological predictors and a phenotype. The probabilistic predictor may use a function that is selected based on the type of the phenotype (e.g., binary, multi-state, or continuous). The probabilistic predictor may use genetic and/or epigenetic information. The probabilistic predictor may be trained on a portion of the data in conjunction with predicting phenotypes in another portion of the data. The probabilistic predictor may be used for various analyses including genome-wide association analysis and gene-set enrichment analysis. | 03-03-2011 |

20100293123 | COMPLEX SITUATION ANALYSIS SYSTEM - A system for generating a representation of a situation is disclosed. The system comprises one or more computer-readable media including computer-executable instructions that are executable by one or more processors to implement a method of generating a representation of a situation. The method comprises receiving input data regarding a target population. The method further comprises constructing a synthetic data set including a synthetic population based on the input data. The synthetic population includes a plurality of synthetic entities. Each synthetic entity has a one-to-one correspondence with an entity in the target population. Each synthetic entity is assigned one or more attributes based on information included in the input data. The method further comprises receiving activity data for a plurality of entities in the target population. The method further comprises generating activity schedules for each synthetic entity in the synthetic population. Each synthetic entity is assigned at least one activity schedule based on the attributes assigned to the synthetic entity and information included in the activity data. An activity schedule describes the activities of the synthetic entity and includes a location associated with each activity. The method further comprises receiving additional data relevant to the situation being represented. The additional data is received from at least two distinct information sources. The method further comprises modifying the synthetic data set based on the additional data. Modifying the synthetic data set includes integrating at least a portion of the additional data received from each of the at least two distinct information sources into the synthetic data set based on one or more behavioral theories related to the synthetic population. The method further comprises generating a social contact network based on the synthetic data set. The social contact network is used to generate the representation of the situation. | 11-18-2010 |

20100293120 | SYSTEMS AND METHODS FOR BOX FITNESS TERMINATION OF A JOB OF AN EVOLUTIONARY SOFTWARE PROGRAM - Systems and methods may include receiving a respective plurality of objective function values for each chromosome data structure of a population, where the respective plurality of objective function values are obtained based upon an evaluation of each chromosome data structure; mapping the respective objective function values to respective epsilon values, where the respective epsilon values define a respective address associated with the plurality of objective functions; and performing non-domination sorting of the population to generate a reduced population of chromosome data structures; and performing epsilon non-dominated sorting to identify an elite set of addresses, where the prior steps are performed for a current generation, where the elite set of addresses are compared to a prior elite set of addresses for a predetermined number of prior generations to determine one or more variance values, where the one or more variance values are utilized to determine whether a current job of an evolutionary algorithm is to be halted. | 11-18-2010 |

20110119213 | SUPPORT VECTOR MACHINE - RECURSIVE FEATURE ELIMINATION (SVM-RFE) - Identification of a determinative subset of features from within a group of features is performed by training a support vector machine using training samples with class labels to determine a value of each feature, where features are removed based on their the value. One or more features having the smallest values are removed and an updated kernel matrix is generated using the remaining features. The process is repeated until a predetermined number of features remain which are capable of accurately separating the data into different classes. | 05-19-2011 |

20120150776 | ADAPTIVE MULTIMEDIA PROCESSOR AND ADAPTIVE DATA PROCESSING METHOD - Disclosed is a structure of an adaptive multimedia processor and a method for implementing an adaptive data processing algorithm. The adaptive multimedia processor includes a bit stream analyzer for analyzing bit stream information of multimedia data, and a bit stream learning device for converting multimedia data having a format which cannot be reproduced in a device, to multimedia data having a format which can be reproduced in a device, through an execution of a learning algorithm, based on an analysis by the bit stream analyzer. | 06-14-2012 |

20100185572 | METHODS AND SYSTEMS FOR MULTI-PARTICIPANT INTERACTIVE EVOLUTIONARY COMPUTING - Disclosed are methods, systems, and processor program products that include executing an optimization scheme to obtain a first solution set, presenting the first solution set to at least two users, receiving rankings of the first solution set from the at least two users, aggregating the rankings, and, generating a second solution set based on the aggregated rankings The optimization scheme can include a genetic algorithm. In embodiments, at least a part of the first solution set can be presented to the users based on the parts of the solution set associated with the user (e.g., user's knowledge). | 07-22-2010 |

20110137839 | METHODS AND SYSTEMS FOR APPLYING GENETIC OPERATORS TO DETERMINE SYSTEM CONDITIONS - Disclosed are methods, systems, and/or processor program products that include generating a population of genotypes, the genotypes based on at least one stimulus to a system, measuring at least one response of the system upon providing the population of genotypes to at least one model of the system, and, based on the measured at least one response of the system, performing at least one of: (a) applying at least one genetic operator to at least some of the population of genotypes, and iteratively returning to generating a population of genotypes, and (b) associating a condition of the system with at least one of the population of genotypes. | 06-09-2011 |

20110137838 | INFORMATION PROCESSING APPARATUS, OBSERVATION VALUE PREDICTION METHOD, AND PROGRAM - Provided is an information processing apparatus including a predictor construction unit that creates, by machine learning based on a genetic algorithm and by combining processing functions prepared in advance, a plurality of feature quantity extraction formulae for extracting, from an observation value observed before a predetermined time, feature quantities of the observation value, and creates a prediction formula for predicting an observation value at the predetermined time based on the feature quantities calculated by the plurality of feature quantity extraction formulae, and a prediction unit that predicts an observation value at a time t from an observation value observed before the time t, by using the prediction formula created by the predictor construction unit. | 06-09-2011 |

20100121794 | USING A MODEL TREE OF GROUP TOKENS TO IDENTIFY AN OBJECT IN AN IMAGE - Object recognition techniques are disclosed that provide both accuracy and speed. One embodiment of the present invention is an identification system. The system is capable of locating objects in images by searching for local features of an object. The system can operate in real-time. The system is trained from a set of images of an object or objects. The system computes interest points in the training images, and then extracts local image features (tokens) around these interest points. The set of tokens from the training images is then used to build a hierarchical model structure. During identification/detection, the system computes interest points from incoming target images. The system matches tokens around these interest points with the tokens in the hierarchical model. Each successfully matched image token votes for an object hypothesis at a certain scale, location, and orientation in the target image. Object hypotheses that receive insufficient votes are rejected. | 05-13-2010 |

20100023468 | METHOD AND APPARATUS FOR CHEMICAL GENETIC PROGRAMMING - A chemical genetic programming apparatus is provided, which enables programming by the application of a chemical genetic algorithm. A CPU | 01-28-2010 |

20090248597 | Method and apparatus for computing a change plan - A method, and computer program product for computing a change plan are presented. A model of a current configuration is identified, the model including modeled system assets and modeled tasks. A request to change the current configuration to a new configuration is received. The request to change the current configuration to generate a plurality of valid strategies to be used in a genetic programming parse tree corresponding to modeled assets and modeled tasks of said model is applied to the model. The request to change the current configuration is applied to at least one of said valid strategies to generate a plurality of potential change plans. The change plans are evolved according to genetic programming principles to a preferred change plan. | 10-01-2009 |

20080270331 | Method and system for solving an optimization problem with dynamic constraints - A method and system for solving an optimization problem comprising a plurality of dynamic constraints. A genetic algorithm is used to iteratively generate potential solutions to the problem. A constraint graph is used to model the plurality of dynamic constraints, and any potential solution that does not correspond to a connected subgraph of the constraint graph is infeasible and discarded. Real-time changes in dynamic constraints are incorporated by modification of the constraint graph between iterations of the genetic algorithm. An exemplary embodiment comprising the scheduling of air missions is presented. | 10-30-2008 |

20110307430 | Pareto Sampling Using Simplicial Refinement by Derivative Pursuit - A method of optimizing a plurality of objectives includes the steps of initializing a set of simplices; selecting a simplex from the set of simplices; computing one or more weights based at least in part on the selected simplex; and generating a point on a tradeoff surface by utilizing the one or more weights in a weighted-sum optimization. | 12-15-2011 |

20100332430 | APPLICATION OF MACHINE LEARNING METHODS FOR MINING ASSOCIATION RULES IN PLANT AND ANIMAL DATA SETS CONTAINING MOLECULAR GENETIC MARKERS, FOLLOWED BY CLASSIFICATION OR PREDICTION UTILIZING FEATURES CREATED FROM THESE ASSOCIATION RULES - The disclosure relates to the use of one or more association rule mining algorithms to mine data sets containing features created from at least one plant or animal-based molecular genetic marker, find association rules and utilize features created from these association rules for classification or prediction. | 12-30-2010 |

20120209798 | AUTONOMOUS BIOLOGICALLY BASED LEARNING TOOL - An autonomous biologically based learning tool system and a method that the tool system employs for learning and analysis are provided. The autonomous biologically based learning tool system includes (a) one or more tool systems that perform a set of specific tasks or processes and generate assets and data related to the assets that characterize the various processes and associated tool performance; (b) an interaction manager that receives and formats the data, and (c) an autonomous learning system based on biological principles of learning. The autonomous learning system comprises a memory platform and a processing platform that communicate through a network. Both the memory platform and the processing platform include functional components and memories that can be defined recursively. Knowledge generated and accumulated in the autonomous learning system(s) can be cast into semantic networks that can be employed for learning and driving tool goals based on context. | 08-16-2012 |

20080313113 | Method and Apparatus for an Algorithm Development Environment for Solving a Class of Real-Life Combinatorial Optimization Problems - The invention pertains to an algorithm development environment for solving a class of combinatorial optimization problems. Many practical real-life applications can be formulated as combinatorial optimization problems. Over the years, there have been many well-known algorithms proposed to solve these problems. The effort in customizing algorithms to fulfill a particular domain-specific application is still significant. Furthermore, conventional approaches towards codes generation and modification are tedious and thus inefficient. To address the need for rapid generation of algorithms that are efficient in solving a given class of real-life problems, embodiments of the present invention encompasses a hierarchical tree structure for managing a procedure modules library. Based on the preferred management and object-oriented design concept, users configure and generate a genetic algorithm (GA) via an intuitive graphical user interface. The goal-seeking approach of customization of the generated GA can be easily carried out for solving various optimization problems. This way, the efficiency of algorithm development is enhanced significantly. | 12-18-2008 |

20120005138 | MODIFYING CONSTRAINT-COMPLIANT POPULATIONS IN POPULATION-BASED OPTIMIZATION - Some embodiments are directed to determining a plurality of constraint compliant values for each of a plurality of constrained variables of an optimization problem, wherein a constraint condition mutually constrains possible values that can be used for the plurality of constrained variables, and wherein the plurality of constraint compliant values comply with the constraint condition. Some embodiments are further directed to generating a population of constraint compliant candidate solutions for a computer-based simulation that implements a population-based optimization algorithm for the optimization problem, wherein the constraint compliant candidate solutions use a subset of the plurality of constraint compliant values and each of the constraint compliant candidate solutions comply with the constraint condition. Some embodiments are further directed to, while running the computer-based simulation with the population of constraint compliant candidate solutions, determining that a mutated candidate solution created from mutating one of the constraint compliant candidate solutions fails to comply with the constraint condition. Some embodiments are further directed to modifying the mutated candidate solution to use at least one value randomly selected from the plurality of constraint compliant values for a corresponding one of the plurality of constrained variables resulting in a constraint compliant mutated candidate solution that complies with the constraint condition. | 01-05-2012 |

20120005136 | PERFORMING CONSTRAINT COMPLIANT CROSSOVERS IN POPULATION-BASED OPTIMIZATION - Some embodiments are directed to determining a plurality of constraint compliant values for each of a plurality of constrained variables of an optimization problem, wherein the plurality of constraint compliant values comply with a constraint condition that constrains possible values that can be used for the plurality of constrained variables; generating a population of constraint compliant candidate solutions for a computer-based simulation that implements a population-based optimization algorithm for the optimization problem, wherein the constraint compliant candidate solutions use a subset of the plurality of constraint compliant values and each of the constraint compliant candidate solutions comply with the constraint condition; while running the computer-based simulation with the population of constraint compliant candidate solutions, determining that a child candidate solution created from two of the constraint compliant candidate solutions fails to comply with the constraint condition; and modifying the child candidate solution to use at least one value randomly selected from the plurality of constraint compliant values for a corresponding one of the plurality of constrained variables resulting in a modified child candidate solution that complies with the candidate solution. | 01-05-2012 |

20120005137 | GENERATING CONSTRAINT-COMPLIANT POPULATIONS IN POPULATION-BASED OPTIMIZATION - Some embodiments are directed to determining a plurality of sets of variables of an optimization problem, where a first set of the plurality of sets comprises a constrained variable constrained by a constraint condition indicated by a constraint description for the optimization problem and where a second set of the plurality of sets of variables comprises a non-constrained variable. Some embodiments are further directed to determining a plurality of constraint compliant values for the constrained variable that comply with the constraint condition and generating a plurality of non-constrained values for the non-constrained variable. Some embodiments are further directed to randomly combining individual ones of the plurality of constraint compliant values with individual ones of the plurality of non-constrained values into a plurality of value sets that satisfy the constraint description for the optimization problem. Some embodiments are further directed to running a computer based simulation that implements a population-based optimization algorithm with the plurality of value sets input as a population for the computer-based simulation. | 01-05-2012 |

20110093419 | PATTERN IDENTIFYING METHOD, DEVICE, AND PROGRAM - The purpose is to provide a pattern identifying method, a pattern identifying device and a pattern identifying program, which able to correctly identify a pattern even in a case where an outlier is existed. The identifying method includes: reading, as data, an input pattern to be identified and a learning pattern previously prepared; computing a probability of a virtually generated virtual pattern existing between said input pattern and said learning pattern, as a first probability; computing a non-similarity of said input pattern with respect to said learning pattern, based on said first probability; and identifying whether or not said input pattern is consistent with said learning pattern, based on said non-similarity. | 04-21-2011 |

20120066162 | System and Method for Training an Adaptive Filter in an Alternate Domain with Constraints - The adaptive filtering techniques described herein allow a filter that is operating in a target domain to be trained in another domain, possibly with constraints, using the same adaptation framework used in a standard adaptive filter. As a result, the adaptation engine may be configured to run in a transform domain that is more desirable than the target domain. For example, the transform domain may be less susceptible to noise or may have more impact on the trained filter's desired results. The filter is trained in the transform domain and then the filter hardware is updated in the target domain. | 03-15-2012 |

20120016826 | EVOLUTIONARY CLUSTERING ALGORITHM - The invention relates to selecting a set of candidate genes from a pool of genes. The method comprising receiving a set of gene data; arranging the set of gene data into a set of clusters with similar profiles by use of a clustering algorithm; and inputting the set of clusters into a genetic algorithm to select a set of candidate genes from the set of clusters. The method thus relates to hybrid between selection by clustering computation and selection by evolutionary computation. This hybrid is also referred to as an evolutionary clustering algorithm (ECA). | 01-19-2012 |

20120158627 | FRAMEWORK FOR OPTIMIZED PACKING OF ITEMS INTO A CONTAINER - One embodiment is directed to a method of optimally packing items into at least one resource. The method includes receiving at least one of items, resources, and parameters, and setting up a set partitioning mixed integer programming (MIP) using the received items, resources, and parameters. The method further includes solving liner programming (LP) relaxation of the MIP, generating new packings, and checking whether new packings have been generated. When no new packings have been generated, solving the final MIP and creating a model of at least one resource packed according to the final MIP. | 06-21-2012 |

20120158626 | DETECTION AND CATEGORIZATION OF MALICIOUS URLS - This document describes techniques for using features extracted from a URL to detect a malicious URL and categorize the malicious URL as one of a phishing URL, a spamming URL, a malware URL or a multi-type attack URL. The techniques employ one or more machine learning algorithms to train classification models using a set of training data which includes a known set of benign URLs and a known set of malicious URLs. The classification models are then employed to detect and/or categorize a malicious URL. | 06-21-2012 |

20120072382 | SYSTEMS AND METHODS FOR MATCHING PEOPLE BASED ON PERCEIVED ACTIVITIES - Matching systems and methods for social networking systems can select matches for users based on observed activities. A matching system can include, for example, a preference unit, a monitoring unit, and a matching unit. Generally, the preference unit can receive and process matching preference information for a user; the monitoring unit can monitor the user's activities on or observable by the server; and the matching unit can select and recommend matches for the user based on the monitored activities. Thus, matches can be suggested to the user based on the user's observed activities, and not simply based on the user's potentially inaccurate self-description. | 03-22-2012 |

20120123981 | SOFTWARE TO FACILITATE DESIGN, DATA FLOW MANAGEMENT, DATA ANALYSIS AND DECISION SUPPORT IN STRUCTURAL HEALTH MONITORING SYSTEMS - This patent application describes (a) software to help people design monitoring systems and (b) methods to facilitate enhanced data flow management (including from large numbers of simultaneous sources), diagnostic and statistical analyses based on novel concepts of data compression using statistical state space techniques. The design assistance is structured around known but not widely practiced procedures such as documented in Graves, Rens and Rutz (2011). For data flow management, the present invention may transmit and store an estimated state space model only when the last stored model is not adequate to predict recent observations. It may also transmit and store outliers and samples of regular observations. This unique data storage format requires new methods for data analysis to properly extract the information contained therein. | 05-17-2012 |

20110106737 | Policy Scheduling - A policy scheduler scheduling a policy is provided. The policy scheduler receives the policy for a system and information of a current state of the system. The policy scheduler evaluates one or more rules based on the current state of the system and generates a new rule via an evolutionary algorithm based on the information of the current state of the system. The policy scheduler adds the newly generated rule into the one or more rules and schedules the policy based on the one or more rules including the newly generated rule. | 05-05-2011 |

20120221500 | SYSTEMS AND METHODS FOR VALIDATING INTERPOLATION RESULTS USING MONTE CARLO SIMULATIONS ON INTERPOLATED DATA INPUTS - Embodiments relate to systems and methods for validating interpolation results using Monte Carlo simulations on interpolated data inputs. A database can store sets of operational data, such as financial, medical, climate or other information. For given data, a portion of the input data can be known or predetermined, while for a second portion can be unknown and subject to interpolation. The interpolation engine can generate a conformal interpolation function and interpolated input sets that map to a set of target output data. In aspects, in order to test the interpolated input data, the operator can initiate a Monte Carlo or other variational analysis using access a validation dialog. The Monte Carlo process can apply randomized perturbations to the values of the interpolated input variables, and track the results of that perturbation on the other interpolated inputs. A set of validation rules can be applied to those randomized results, to determine whether the remaining interpolated variables remain in conformance with expected ranges or values or demonstrate anomalous responses. | 08-30-2012 |

20120221501 | MOLECULAR PROPERTY MODELING USING RANKING - Methods and articles of manufacture for modeling molecular properties using data regarding the partial orderings of compound properties, or by considering measurements of compound properties in terms of partial orderings are disclosed. One embodiment provides for constructing such partial orderings from data that is not already in an ordered form by processing training data to produce a partial ordering of the compounds with respect to a property of interest. Another embodiment of the invention may process the modified training data to construct a model that predicts the property of interest for arbitrary compounds. | 08-30-2012 |

20120130929 | CONTROLLING QUARANTINING AND BIASING IN CATACLYSMS FOR OPTIMIZATION SIMULATIONS - Some embodiments are directed to generating a first probability value that represents a percentage of times that first bit values for a given bit position of a first plurality of candidate solutions equate to a pre-defined number, where the first plurality of candidate solutions has converged on a sub-optimal solution during a simulation of an optimization problem using an optimization algorithm. Some embodiments are further directed to generating a second probability value that is inversely biased from the first probability value; and generating a second plurality of candidate solutions with the second probability value, where the second plurality of candidate solutions are inversely biased from the first bit values for the given bit position. | 05-24-2012 |

20120130928 | EFFICIENT STORAGE OF INDIVIDUALS FOR OPTIMIZATION SIMULATION - Candidate solutions to an optimization problem comprise a set of potential values that can be applied to variables in a problem description. Candidate solutions can be large because of the complexity of optimization problems and large number of variables. The populations of candidate solutions may also be large to ensure diversity and effectiveness in computing a solution. When the populations and the candidate solutions are large for an optimization problem, computing a solution to the optimization problem consumes a large amount of memory. In some instances, several generations of candidate solutions are stored in memory. Compression of the candidate solutions can minimize the memory space consumed to compute a solution to an optimization problem. | 05-24-2012 |

20100205128 | METHOD AND APPARATUS FOR ANALYZING AND INTERRELATING DATA - A method for automatically organizing data into themes, the method including the steps of retrieving electronic data from at least one data source, storing the data in a temporary storage medium, querying the data in the storage medium using a computer-based query language, identifying themes within the data stored in the storage medium using a computer program including an algorithm, and organizing the data stored in the storage medium into the identified themes. | 08-12-2010 |

20100205126 | LOCAL GRAPH PARTITIONING USING EVOLVING SETS - Providing for local graph partitioning using an evolving set process is disclosed herein. By way of example, a computer processor can be configured to execute local partitioning based on evolving set instructions. The instructions can be employed to transition a set of analyzed vertices of a graph until a segment of the graph with small conductance is identified. A transitioning algorithm can expand or contract the analyzed set of vertices based on characteristics of vertices at a boundary of the analyzed set. Accordingly, as the set of analyzed vertices becomes large, significant processing efficiency is gained by employing the characteristics of boundary vertices to transition the set or determine conductance, rather than all vertices of the analyzed set. | 08-12-2010 |

20120254082 | METHOD AND APPARATUS FOR GENERATING PROFILE OF SOLUTIONS TRADING OFF NUMBER OF ACTIVITIES UTILIZED AND OBJECTIVE VALUE FOR BILINEAR INTEGER OPTIMIZATION MODELS - A computer system for generating at least one of a solution and a profile of solutions for a problem includes an augmenting unit that repeatedly solves a model to generate a profile of solutions. The profile trades off a reduction of an objective of the problem against a number of distinct activities utilized in a solution. | 10-04-2012 |

20120173468 | MEDICAL DATA PREDICTION METHOD USING GENETIC ALGORITHMS - A method may use a genetic algorithm to varying prediction parameters in forecasting software to obtain optimal predictions is disclosed. The method identifies parameters that can be varied and by modifying the parameters, the predictions of the forecasting software improve. The method uses sample data to train and validate the forecast and the optimal forecasting parameters are determined. | 07-05-2012 |

20100299291 | Cruncher - An MIP Solver Accelerator - Methods and systems are provided for solving an optimization problem using a model expressed in a mixed integer programming (MIP) language. The problem is constrained within a space of valid solutions by a plurality of MIP variables. A skeleton set of the variables are designated as eligible for fixed value assignments. An initial solution for the problem is obtained, which forms the basis for refinement. New versions of the problem are prepared and solved iteratively by fixing a proportion of the skeleton set to their best known values, as found in a previous problem-solving iteration. | 11-25-2010 |

20100010946 | METHOD FOR EVOLVING MOLECULES AND COMPUTER PROGRAM FOR IMPLEMENTING THE SAME - A computer-based method and system of evolving a virtual molecule with a set of desired properties is described that begins with extracting fragments from existing molecules and labeling those fragments. Connectivity rules existing between the fragments in the existing molecules are determined followed by combining these fragments according to the connectivity rules. The molecules generated by the combination are evaluated and some are selected for modification. The evaluation and modification steps are repeated for the selected molecules until either 1) a target evaluation value is achieved or 2) the evaluation step has been performed a predefined number of times. | 01-14-2010 |

20110131162 | AUTONOMOUS BIOLOGICALLY BASED LEARNING TOOL - An autonomous biologically based learning tool system and a method that the tool system employs for learning and analysis are provided. The autonomous biologically based learning tool system includes (a) one or more tool systems that perform a set of specific tasks or processes and generate assets and data related to the assets that characterize the various processes and associated tool performance; (b) an interaction manager that receives and formats the data, and (c) an autonomous learning system based on biological principles of learning. The autonomous learning system comprises a memory platform and a processing platform that communicate through a network. The network receives data from the tool system and from an external actor through the interaction manager. Both the memory platform and the processing platform include functional components and memories that can be defined recursively. Similarly, the one or more tools can be deployed recursively, in a bottom-up manner in which an individual autonomous tools is assembled in conjunction with other (disparate or alike) autonomous tools to form an autonomous group tool, which in turn can be assembled with other group tools to form a conglomerated autonomous tool system. Knowledge generated and accumulated in the autonomous learning system(s) associated with individual, group and conglomerated tools can be cast into semantic networks that can be employed for learning and driving tool goals based on context. | 06-02-2011 |

20090063376 | RECONSTRUCTION OF GENE NETWORKS FROM TIME-SERIES MICROARRAY DATA - Gene regulation network is reconstructed using time series microarray data under the method of the Bayesian network. Particular power-law function is used to calculate the joint probabilities among genes across time points. This invention discloses the use of the downhill simplex algorithm to find global maxima of interrelational likelihood. Arcs with higher frequencies are selected to establish the gene regulation network. Prior knowledge may be included into candidate gene networks to accelerate search for best networks. | 03-05-2009 |

20110131164 | SYSTEM AND METHOD FOR BUILDING A PREDICTIVE SCORE WITHOUT MODEL TRAINING - A system and method for building a predictive score without model training are disclosed. A set of predictive variables is defined based on raw data fields generated from raw data from one or more sources and domain knowledge. The raw data includes a historical set of transactions previously generated by one or more raw data sources. An scaled relative risk table to describe each predictive variable of the set of predictive variables is generated. The set of predictive variables is combined based on their associated relative risk tables to generate a predictive score for a future set of transactions. | 06-02-2011 |

20110131163 | Managing a Portfolio of Experts - Managing a portfolio of experts is described where the experts may be for example, automated experts or human experts. In an embodiment a selection engine selects an expert from a portfolio of experts and assigns the expert to a specified task. For example, the selection engine has a Bayesian machine learning system which is iteratively updated each time an experts performance on a task is observed. For example, sparsely active binary task and expert feature vectors are input to the selection engine which maps those feature vectors to a multi-dimensional trait space using a mapping learnt by the machine learning system. In examples, an inner product of the mapped vectors gives an estimate of a probability distribution over expert performance. In an embodiment the experts are automated problem solvers and the task is a hard combinatorial problem such as a constraint satisfaction problem or combinatorial auction. | 06-02-2011 |

20100169251 | MONITORING METHODS AND APPARATUS - A method of monitoring an evolving system, the method including the steps of: obtaining a plurality of sensor data streams relating to outputs from sensors monitoring said system, wherein at least one of said sensors monitors a condition of said system, and wherein at least one of said sensors monitors a causal agent for said condition; iteratively constructing a plurality of functional nests, each functional nest being a functional formed from a combination of selected functionals from a basic set of functionals; determining an output data stream for each functional nest by inputting said sensor data streams into said functional nests; selecting a functional nest from said plurality of functional nests based on said output data streams; and using said selected functional nest to monitor said system. | 07-01-2010 |

20100169252 | SYSTEM AND METHOD FOR SCALABLE COST-SENSITIVE LEARNING - A method (and structure) for processing an inductive learning model for a dataset of examples, includes dividing the dataset of examples into a plurality of subsets of data and generating, using a processor on a computer, a learning model using examples of a first subset of data of the plurality of subsets of data. The learning model being generated for the first subset comprises an initial stage of an evolving aggregate learning model (ensemble model) for an entirety of the dataset, the ensemble model thereby providing an evolving estimated learning model for the entirety of the dataset if all the subsets were to be processed. The generating of the learning model using data from a subset includes calculating a value for at least one parameter that provides an objective indication of an adequacy of a current stage of the ensemble model. | 07-01-2010 |

20120089544 | System and Method for Parameter Evaluation - The described implementations relate to machine learning. One implementation provides a technique involving logging data that includes outcomes and values of first and second parameters that are associated with the outcomes. The technique can also include determining an equation that includes a first coefficient for the first parameter and a second coefficient for the second parameter, normalizing the first coefficient based on the values of the first parameter, and normalizing the second coefficient based on the values of the second parameter. The first parameter and the second parameter can be ranked in order of contribution to the outcomes based on the normalized first and second coefficients. | 04-12-2012 |

20110276525 | REFERENCE MARKERS FOR BIOLOGICAL SAMPLES - The present invention provides methods, compositions and kits that include reference markers in biological samples. The reference samples can be marked with DNA oligomers that can be derived from sequences that do not to exist in the human genome. These sequences can be determined by an algorithm used to search published genomes for the shortest sequences which are not present (“nullomers”). Such reference markers can be used in forensic, medical, legal or other applications. | 11-10-2011 |

20110320390 | METHOD FOR IDENTIFICATION, PREDICTION AND PROGNOSIS OF CANCER AGGRESSIVENESS - A survival model, for each of one or more pairs of genes, includes a function of a corresponding measure of the ratio of expression levels of the pairs of genes. For each pair of genes, there is a corresponding a cut-off value, such that patients are classified according to whether the corresponding measure is above or below the cut-off value. It is proposed (in an algorithm called “DDgR”) that the cut-off value should be selected so as to maximise the separation of the respective survival curves of the two groups of patients. It is further proposed that, for each of a number of genes or gene pairs, a selection is made from multiple survival models. The selection is according to whether a proportionality assumption is obeyed and/or according to a measure of data fit, such as the Baysian Information Criterion (BIC). Specific gene pairs identified by the methods are named. | 12-29-2011 |

20120136818 | Information Processing Device, Information Processing Method, and Program - An information processing device for generating a target feature amount computational expression for outputting a target feature amount corresponding to input data, comprising: a feature amount extraction expression list generating unit configured to generate and update a feature amount extraction expression list; a feature amount computing unit configured to input actual data supplied as tutor data to each feature amount extraction expression included in the feature amount extraction expression list to compute multiple feature amounts corresponding to the actual data; a target feature amount computational expression generating unit configured to employ the multiple feature amounts, and an existing feature amount corresponding to the actual data supplied as tutor data for the same rank to generate the target feature amount computational expression by machine learning; and an evaluation value computing unit configured to compute the evaluation value of each feature amount extraction expression included in the feature amount extraction expression list. | 05-31-2012 |

20110161265 | METHODS, SYSTEMS, AND SOFTWARE FOR IDENTIFYING FUNCTIONAL BIO-MOLECULES - The present invention generally relates to methods of rapidly and efficiently searching biologically-related data space. More specifically, the invention includes methods of identifying bio-molecules with desired properties, or which are most suitable for acquiring such properties, from complex bio-molecule libraries or sets of such libraries. The invention also provides methods of modeling sequence-activity relationships. As many of the methods are computer-implemented, the invention additionally provides digital systems and software for performing these methods. | 06-30-2011 |

20110161263 | Computer-Implemented Systems And Methods For Constructing A Reduced Input Space Utilizing The Rejected Variable Space - Computer-implemented systems and methods are provided for generating a data model. A variable predictiveness determination is performed on the population of candidate variables. A plurality of variables from the population of candidate variables are selected as a selected set based on the variable predictiveness values. A plurality derived variables are generated based on variables in the rejected set without consideration of any variables in the selected set. One or more derived variables are selected as based on derived variable predictiveness values of the derived variables, and the selected set and the one or more selected derived variables are stored as the model input variables for the data model. | 06-30-2011 |

20130173510 | METHODS AND SYSTEMS FOR USE IN REDUCING SOLUTION CONVERGENCE TIME USING GENETIC ALGORITHMS - A computer system for finding a solution using a genetic algorithm is provided. The computer system includes a display, a user input device, at least one processor, and computer readable media. The at least one processor is programmed to execute a genetic algorithm. The genetic algorithm includes an initialization stage, an evolution stage, and an output stage. The evolution stage includes a domain restraint process. During the domain restraint process, children created during the evolution stage are compared with an environmental influence which represents domain knowledge. Children are influenced using the environmental influence in order to reduce the search domain by avoiding solutions known to be sub-optimal. | 07-04-2013 |

20130173511 | USING GLOBAL AND LOCAL CATASTROPHES ACROSS SUB-POPULATIONS IN PARALLEL EVOLUTIONARY COMPUTING - A parallel genetic algorithm computing process tracks forward progress of a first sub-population across generations thereof. The first sub-population is one of a plurality of sub-populations that form a population of candidate solutions to an optimization problem. At a current generation of the first sub-population, it is determined that forward progress of the first sub-population fails a set of one or more forward progress criteria. In response to determining that the forward progress of the first sub-population fails the set of one or more forward progress criteria at the current generation, a local catastrophe is invoked on the current generation of the first sub-population. The first sub-population is re-populated after the local catastrophe is invoked. The first sub-population is re-established after re-populating while constraining migration to the first sub-population. | 07-04-2013 |

20080222061 | Adaptive Multivariate Model Construction - The present embodiment is able to find the optimal or near optimal variables composition of multivariate models by an evolutionary process within acceptable amount of time and resources that are less than using full variables permutation methodology. Subjected to any data, it adaptively identifies and constructs the most effective combination of the relevant variables to achieve one or more objectives. The objective could be for high explanatory power, high predictive power, response measure, or other objectives that the user defines. The present embodiment solves the sequential F-test problem by conducting non-sequential and non-linear search. The algorithm also solves partial F-test dilemma by evaluating all candidate variables membership intact, maintaining fidelity of full variables membership test throughout its permutation. Furthermore, the stochastic nature of the algorithm neutralizes the prejudices of manual decisions in variables identification and membership construction. | 09-11-2008 |

20080215512 | SYSTEM, METHOD, AND COMPUTER-ACCESSIBLE MEDIUM FOR PROVIDING A MULTI-OBJECTIVE EVOLUTIONARY OPTIMIZATION OF AGENT-BASED MODELS - Agent-based models (ABMs)/multi-agent systems (MASs) are one of the most widely used modeling-simulation-analysis approaches for understanding the dynamical behavior of complex systems. These models can be often characterized by several parameters with nonlinear interactions which together determine the global system dynamics, usually measured by different conflicting criteria. One problem that can emerge is that of tuning the controllable system parameters at the local level, in order to reach some desirable global behavior. According to one exemplary embodiment t of the present invention, the tuning of an ABM for emergency response planning can be cast as a multi-objective optimization problem (MOOP). Further, the use of multi-objective evolutionary algorithms (MOEAs) and procedures for exploration and optimization of the resultant search space can be utilized. It is possible to employ conventional MOEAs, e.g., the Nondominated Sorting Genetic Algorithm II (NSGA-II) and the Pareto Archived Evolution Strategy (PAES), and their performance can be tested for different pairs of objectives for plan evaluation. In the experimental results, the approximate Pareto front of the non-dominated solutions is effectively obtained. Further, a conflict between the proposed objectives can be seen. Additional robustness analysis may be performed to assist policy-makers in selecting a plan according to higher-level information or criteria which is likely not present in the original problem description. | 09-04-2008 |

20130173512 | USING GLOBAL AND LOCAL CATASTROPHES ACROSS SUB-POPULATIONS IN PARALLEL EVOLUTIONARY COMPUTING - A parallel genetic algorithm computing process tracks forward progress of a first sub-population across generations thereof. The first sub-population is one of a plurality of sub-populations that form a population of candidate solutions to an optimization problem. At a current generation of the first sub-population, it is determined that forward progress of the first sub-population fails a set of one or more forward progress criteria. In response to determining that the forward progress of the first sub-population fails the set of one or more forward progress criteria at the current generation, a local catastrophe is invoked on the current generation of the first sub-population. The first sub-population is re-populated after the local catastrophe is invoked. The first sub-population is re-established after re-populating while constraining migration to the first sub-population. | 07-04-2013 |

20130091082 | USING A HEURISTICALLY-GENERATED POLICY TO DYNAMICALLY SELECT STRING ANALYSIS ALGORITHMS FOR CLIENT QUERIES - A method for dynamically selecting string analysis algorithms can begin with the training of the dynamic string analysis handler of a string analysis module to effectively handle a subset of string queries having contextual metadata received from a client application in an instructional environment. The effectiveness of the training module can be based upon feedback from the client application. Upon completion of the training, a string analysis algorithm selection policy can be synthesized. The string analysis algorithm selection policy can correlate a context of a string query in the subset to the usage of a string analysis algorithm. When in the operational environment, the dynamic string analysis handler can dynamically handle string queries having contextual metadata received from the client application in accordance with the string analysis algorithm selection policy. The string analysis algorithm to be used for a string query can be dynamically and independently determined. | 04-11-2013 |

20130124440 | DATA MINING TECHNIQUE WITH MAINTENANCE OF FITNESS HISTORY - Roughly described, a computer-implemented evolutionary data mining system includes a memory storing a candidate gene database in which each candidate individual has a respective fitness estimate; a gene pool processor which tests individuals from the candidate gene pool on training data and updates the fitness estimate associated with the individuals in dependence upon the tests; and a gene harvesting module for deploying selected individuals from the gene pool, wherein the gene pool processor includes a competition module which selects individuals for discarding in dependence upon their updated fitness estimate. The system maintains a fitness training history for each of the candidate individuals, and uses the historical information to assist in any one or more of: competition among the individuals; avoiding re-testing of an individual on the same data sample; removing duplicate test data before merging fitness evaluations; improving gene pool diversity; and selecting individuals for deployment. | 05-16-2013 |

20090070281 | System for hybridized efficient genetic algorithms to solve bi-objective optimization problems with application to network computing - A system and methods are presented for the generation of hybridized efficient genetic algorithms (EGAS) applied to bi-objective optimization problems. Applications are made to engineering systems involving collective behaviors, including network computing, robotics and evolvable hardware. | 03-12-2009 |

20110213742 | INFORMATION EXTRACTION SYSTEM - An information extraction system and methods of operating the system are provided. In particular, an information extraction system for performing meta-extraction of named entities of people, organizations, and locations as well as relationships and events from text documents are described herein. | 09-01-2011 |

20110251982 | Holographic computer system - A method and apparatus used for general purpose problem solving using entanglement properties of holography. Intelligent point-based entities having spatial and other electromagnetic properties called DROPLETS [Data-Representative-Object-Particle(s)-Liking-EnTanglement] are generated as delegate objects—avatars—connected to data sources representing situations, event or other problems. A DROPLET's properties are controlled by changes in input data, self-state, feedback, and/or changes of other DROPLETS. Coherent rays are introduced and interact with DROPLETS, generating an INTELLIGENCE WAVEFRONT. Interference patterns are recorded and converted to binary machine codes of a near-infinite set, instructing where to store human/machine-readable content within a plurality of associative memories. Said content includes waveforms, harmonics, codes, data, and other holograms, which are dispersed and stored wholistically throughout using spread spectrum techniques. Upon future recognition of like-patterns of situations, events and other problems, the appropriate content components are retrieved and presented as full or partial solutions. Hardware, software, and hybrid embodiments are envisioned. | 10-13-2011 |

20130132313 | METHOD OF REPAIRING FINANCIALLY INFEASIBLE GENETIC ALGORITHM CHROMOSOME ENCODING ACTIVITY START TIMES IN SCHEDULING - The method of repairing financially infeasible genetic algorithm chromosome encoding activity start times in scheduling problems determines cash availability during a given period, identifies all possible activities' schedules, determines the cash requirements for each schedule, ranks schedules based on the contribution on minimizing the increase in the project duration, schedules all activities of the selected schedule, and determines the impact of the scheduled activities on the project cash flow. Thus, the algorithm introduces effective chromosomes that maximize the utilization of the available funds and minimize project duration. | 05-23-2013 |

20130132312 | DATA PROCESSING METHOD AND APPARATUS FOR CLINICAL DECISION SUPPORT SYSTEM - Provided is a data processing method for clinical decision support system. The data processing method provides an algorithm capable of performing parsing based on an Ontology technique and automatically updating rule database in order to reduce time and labor overloads accompanied by update of the rule database. According to an aspect, the data processing method includes inferring input data having a natural language format based on an Ontology technique to recognize at least one input rule included in the input data; inferring storage data having a natural language format and stored in rule database based on the Ontology technique to recognize at least one storage rule associated with the input rule from the storage data; comparing the input rule to the storage rule using a Self Evolutionary Rule-base algorithm; and updating the storage data stored in the rule database to the input data according to the result of the comparison. | 05-23-2013 |

20100293121 | SYSTEMS AND METHODS FOR PARALLEL PROCESSING WITH INFEASIBILITY CHECKING MECHANISM - Systems and methods may include obtaining an input population of parent chromosome data structures, where each parent chromosome data structure provides having a plurality of genes representative of variables in which associated values are permitted to evolve; selecting pairs of parent chromosome data structures from the input population; allocating the selected pairs of parent chromosome data structures to respective ones of a plurality of slave processors, where each slave processor applies an evolutionary process to genes of the allocated pair to generate a plurality of child chromosome data structures; receiving a portion of the plurality of child chromosome data structures generated by the plurality of slave processors; merging the parent chromosome data structures with at least the received portion of the child chromosome data structures to generate a merged set of chromosome data structures; and identifying a portion of the merged set of chromosome data structures as an elite set of chromosome data structures. | 11-18-2010 |

20130185235 | NON-TRANSITORY COMPUTER READABLE MEDIUM STORING A PROGRAM, SEARCH APPARATUS, SEARCH METHOD, AND CLUSTERING DEVICE - Provided is a non-transitory computer readable medium storing a program causing a computer to function as a learning data acquiring unit that acquires learning data, a memory unit that performs machine learning using the learning data about cluster division where Markov chains of transition via a link from a node to a node on a network formed from plural nodes are divided into plural clusters each of which is indicated by a biased Markov chain and calculates a steady state of each biased Markov chain, a search condition receiving unit that receives a search condition from a user, a cluster extracting unit that extracts clusters suitable for the search condition, a partial network cutting unit that cuts a partial network formed by a node group belonging to the clusters, and an importance calculating unit that calculates importance of each node on the partial network. | 07-18-2013 |

20130185234 | System and Method for Using Genetic Algorithm for Optimization of Targeting Systems, Based on Aggregated Scoring Models - In our presentation here, as examples, we describe methods and systems with various optimization techniques. More specifically, they are directed to methods for applying genetic algorithms, and the use of genetic algorithms in optimizing targeting systems that use an aggregated scoring model. In general, the genetic algorithm principle gives guidelines for constructing practical search techniques when the number of possible trials is extremely large. The examples and other features and advantages of the system and method for using Genetic Algorithm for Optimization of Targeting Systems are described. | 07-18-2013 |

20120005139 | INFORMATION PROCESSING APPARATUS, INFORMATION PROCESSING METHOD, AND PROGRAM - There is provided an information processing apparatus according to the present application including a data acquiring unit which acquires string data representing a string of one or more characters, and a phylogeny analyzing unit which analyzes the string data acquired by the data acquiring unit to extract homologous string pieces in a string represented by the string data and performs phylogeny analysis based on the regional relationship and homological relationship of the extracted homologous string pieces. | 01-05-2012 |

20120041912 | Extracting Gene-Gene Interactions from Gene Expression Data - Disclosed are methods and custom computing apparatuses for identifying gene-gene interactions from gene expression data, based on which a gene regulatory sub-network can be built. In particular, relationships in which multiple genes co-regulate one target gene can also be identified. | 02-16-2012 |