Patent application number | Description | Published |
20080301679 | TECHNIQUE OF DETERMINING PERFORMING ORDER OF PROCESSES - The present invention provides to a technique of determining a performing order of processes. In particular, the present invention relates to a technique of optimizing a performing order of processes in such a case that a result of performing a previous process could be modified later depending on a performing order of processes. The invention further provides a method to determine a performing order of processes so as to minimize required time for a process of modifying a result of an already performed process based on a result of a process performed later. | 12-04-2008 |
20090119632 | METHOD FOR SUPPORTING DETERMINATION OF DESIGN PROCESS ORDER - A system and method which support determination of a design process order. The system includes: a storage device that stores constraint data indicating a strength of a constraint that is given to a respective design process from a respective of the other design processes; a detection unit that accesses the storage device to detect, from the constraint data, a loop of relationships concerning a design process receiving a constraint from another design process; a selection unit that accesses the storage device to select, from the detected loop, a pair capable of canceling the loop when the pair is deleted and having a minimum total constraint strength; and an output unit that deletes the selected constraint pair from the constraint data and outputs data indicating a constraint that is to be satisfied by each design process. | 05-07-2009 |
20120239453 | RESOURCE COST OPTIMIZATION SYSTEM, METHOD, AND PROGRAM - Apparatus and method use a Markov decision process (MDP) to reduce the cost of variations in electric power usage. The user notifies a power company of a predicted value for a period. The period is divided into subsections. For each subsection, on the basis of a MDP including a state that depends on an electric power usage amount error, charge amount, and set target, the amount of charging and discharging of a storage battery as an action at any given time is optimally decided depending on the electric power usage amount error, charge amount, time, and set target at that time. A predetermined time in a subsection is a target setting time, at which a future target is further set as the action. The action includes deciding the charging and discharging amount in that subsection and deciding a future target in a subsection whose target should be set. | 09-20-2012 |
20130346345 | RESOURCE COST OPTIMIZATION SYSTEM, METHOD, AND PROGRAM - Apparatus and method use a Markov decision process (MDP) to reduce the cost of variations in electric power usage. The user notifies a power company of a predicted value for a period. The period is divided into subsections. For each subsection, on the basis of a MDP including a state that depends on an electric power usage amount error, charge amount, and set target, the amount of charging and discharging of a storage battery as an action at any given time is optimally decided depending on the electric power usage amount error, charge amount, time, and set target at that time. A predetermined time in a subsection is a target setting time, at which a future target is further set as the action. The action includes deciding the charging and discharging amount in that subsection and deciding a future target in a subsection whose target should be set. | 12-26-2013 |
Patent application number | Description | Published |
20110288833 | METHOD AND SYSTEM FOR MEASURED VALUE SIMULATION - A method, system and computer program product for measured value simulation. The method including the steps of: observing measured values of an event to provide observed values, where the step of observing starts at a predetermined observation time; concurrently running a plurality of simulations, where the simulations have behaviors that are characterized by different parameters and start at the predetermined observation time; producing a discrete distribution at a predetermined timing after the predetermined observation time, where the discrete distribution are based on distances between the measured values provided by the predetermined timing and calculation of the simulations; and producing a second plurality of simulations based on the discrete distribution. | 11-24-2011 |
20120209801 | DECIDING AN OPTIMAL ACTION IN CONSIDERATION OF RISK - A method and system for deciding an optimal action in consideration of risk. The method includes the steps of: generating sequentially, by way of a Markov decision process based on a Monte Carlo method, a series of data having states on a memory of a computer; computing a risk measure of a present data by tracking generated data from opposite order to generation order, where the risk measure is calculated from a value at risk or an exceedance probability that is derived from risk measures of a plurality of states transitionable from a state of the present data; and executing the step of computing the risk measure while tracking back to starting data, where at least one of the steps is carried out using a computer device. | 08-16-2012 |
20120330884 | DECIDING AN OPTIMAL ACTION IN CONSIDERATION OF RISK - A method and system for deciding an optimal action in consideration of risk. The method includes the steps of: generating sequentially, by way of a Markov decision process based on a Monte Carlo method, a series of data having states on a memory of a computer; computing a risk measure of a present data by tracking generated data from opposite order to generation order, where the risk measure is calculated from a value at risk or an exceedance probability that is derived from risk measures of a plurality of states transitionable from a state of the present data; and executing the step of computing the risk measure while tracking back to starting data, where at least one of the steps is carried out using a computer device. | 12-27-2012 |
20130084011 | PROOF READING OF TEXT DATA GENERATED THROUGH OPTICAL CHARACTER RECOGNITION - A novel system includes: a first proof reading tool for performing carpet proof reading on text data; a second proof reading tool for performing side-by-side proof reading on the text data; a storage unit configured to store a log of proof reading operations having been performed by using the first and second proof reading tools; and an analysis unit configured to determine, for each attribute serving as units in which carpet proof reading is performed with the first proof reading tool, whether or not to use the first proof reading tool in proof reading of the attribute, by comparing a first estimated value of a time taken when proof reading is performed by using the first proof reading tool with a second estimated value of a time taken when proof reading is performed by using the second proof reading tool without using the first proof reading tool, the first and second estimated values being calculated on the basis of the log. | 04-04-2013 |
20130085746 | PROOF READING OF TEXT DATA GENERATED THROUGH OPTICAL CHARACTER RECOGNITION - A novel system includes: a first proof reading tool for performing carpet proof reading on text data; a second proof reading tool for performing side-by-side proof reading on the text data; a storage unit configured to store a log of proof reading operations having been performed by using the first and second proof reading tools; and an analysis unit configured to determine, for each attribute serving as units in which carpet proof reading is performed with the first proof reading tool, whether or not to use the first proof reading tool in proof reading of the attribute, by comparing a first estimated value of a time taken when proof reading is performed by using the first proof reading tool with a second estimated value of a time taken when proof reading is performed by using the second proof reading tool without using the first proof reading tool, the first and second estimated values being calculated on the basis of the log. | 04-04-2013 |
Patent application number | Description | Published |
20120072259 | DETERMINING OPTIMAL ACTION IN CONSIDERATION OF RISK - A system and method for determining an optimal action in consideration of risk. The method includes the steps of: (a) selecting a state from possible states in a current term; (b) selecting an action from action candidates that can be executed in a selected state; (c) calculating a probability distribution of an evaluation value for a selected action; (d) calculating a risk measure using the probability distribution of the evaluation value; (e) determining a weighting function conforming to at least one preference by taking the risk measure into consideration; (f) calculating a value measure of the selected action; (g) repeating steps (b) through (f) for all other the action candidates that can be executed in the selected state; and (h) comparing the value measures of the selected actions in order to determine an optimal action for the selected state. | 03-22-2012 |
20120198447 | DETERMINING AN ALLOCATION CONFIGURATION FOR ALLOCATING VIRTUAL MACHINES TO PHYSICAL MACHINES - An information processing apparatus having a prediction section that determines the predicted peak usage amount of physical resources for each time interval for individual clusters each including a plurality of virtual machines having the same function; a setting section sets a constraint that ensures that, for individual combinations of a first physical machine, a second physical machine, and a time interval, the total predicted peak usage amount of a physical resource predicted for the first physical machine if the second physical machine stops during the time interval does not exceed a physical resource amount prepared for the first physical machine; and an allocation-configuration deriving section derives an allocation configuration by calculating, in accordance with the constraint, a solution to an optimization problem for minimizing, as an objective function, the sum total of the physical resource amounts of all of physical machines to which the virtual machines are allocated. | 08-02-2012 |
20120317573 | DETERMING AN ALLOCATION CONFIGURATION FOR ALLOCATING VIRTUAL MACHINES TO PHYSICAL MACHINES - A computer-executable method for determining an allocation configuration for allocating virtual machines to physical machines. The method includes the steps of determining a predicted peak usage amount of physical resources for each time interval for individual clusters wherein the clusters include a plurality of virtual machines; setting a constraint that ensures the total predicted peak usage amount of the physical resource predicted for the first physical machine does not exceed the physical resource amount for the first physical machine; and deriving an allocation configuration by calculating, in accordance with the constraint, a solution to an optimization problem for minimizing, as an objective function, the sum total of the physical resource amounts of the plurality of physical machines to which the virtual machines are allocated. | 12-13-2012 |
20130060463 | METHOD, APPARATUS AND COMPUTER PROGRAM FOR SELECTING AND DISPLAYING ROUTE FAVORABLE TO DRIVER - A method and apparatus for selecting and displaying a route preferable to a driver while reducing the frequency of changing the route. A dynamic strategy is computed which depends on time required to reach each intersection to be passed through between a departure place and a destination place. A probability distribution of the required time for each intersection and a driving direction to be selected is computed according to the computed dynamic strategy. A driving direction having the highest probability of the required time is sequentially selected to determine intersections to be passed through to the destination. At each intersection, the probability of the required time for each driving direction can be added and a driving direction that has the highest total probability among the results of the additions can be sequentially selected. | 03-07-2013 |
20130096858 | SYSTEM, METHOD, AND PROGRAM FOR PREDICTING STATE OF BATTERY - A method and system for predicting degradation of a battery. Modeling of a battery is made to be separated into an aging section and a current-carrying section. The modeling is established such that the amount of degradation of a capacity retention ratio is determined by the linear sum of stay at each temperature and each SOC. The separation into degradation components at each temperature and each SOC enables predicting degradation under various degradation environments. A model for a battery separated into an aging section and a current-carrying section and a calculation model of a root law are combined into an objective function, and a table of discharge coefficients a | 04-18-2013 |
20130275677 | Method, Device and Computer Program for Identifying Items Having High Frequency of Occurrence Among Items Included in a Text Data Stream - A method, device and computer program for efficiently identifying items having a high frequency of occurrence among items included in a large-volume text data stream. Identification information for identifying an item and a count of items are stored in a higher level of memory and only identification information is stored in a lower level. Text data stream input is received, the increment of the count of an item is increased in response to storage in the higher level memory of identification information for an item included in a bucket divided from the received text data stream input, identification information for the item is transferred with the initial count to the higher level of memory in response to storage in the lower level and the identification information for the item is newly stored with the initial count in the higher level in response to not being stored on any level. | 10-17-2013 |
20130304688 | APPARATUS, PROGRAM, AND METHOD FOR SOLVING MATHEMATICAL PROGRAMMING PROBLEM - An apparatus and method for solving mathematical programming problems. The apparatus includes a first-time-point-solution generating unit generating at least one solution to a mathematical programming problem, a second-time-point-problem generating unit generating a plurality of mathematical programming problems to be on the basis of the solution to the mathematical programming problem to be solved at the first time point, a second-time-point optimum value calculating unit calculating an optimum value of each of a plurality of mathematical programming problems to be solved at the second time point, a relational expression estimating unit estimating a relational expression between the solution to the mathematical programming problem to be solved at the first time point and an optimum value of a mathematical programming problem to be solved at the second time point, and a correcting unit correcting the mathematical programming problem at the first time point based on the relational expression. | 11-14-2013 |
20130345889 | CONTROLLING POWER GENERATORS AND CHILLERS - A method of meeting a power demand of a power consumption unit is disclosed. A forecasted power demand for a power demand scenario for the power consumption unit is determined and a probability of occurrence of the power demand scenario is determined. An objective function for operating at least one power supply device is created that includes the forecasted power demand of the power demand scenario and the determined probability of occurrence of the power demand scenario. A substantial minimum of the objective function is located to determine a schedule for operating the at least one power supply device to meet the forecasted power demand. The at least one power supply device may be operated according to the determined schedule to meet the power demand of the power consumption unit. | 12-26-2013 |
20130345890 | CONTROLLING POWER GENERATORS AND CHILLERS - A method of meeting a power demand of a power consumption unit is disclosed. A forecasted power demand for a power demand scenario for the power consumption unit is determined and a probability of occurrence of the power demand scenario is determined. An objective function for operating at least one power supply device is created that includes the forecasted power demand of the power demand scenario and the determined probability of occurrence of the power demand scenario. A substantial minimum of the objective function is located to determine a schedule for operating the at least one power supply device to meet the forecasted power demand. The at least one power supply device may be operated according to the determined schedule to meet the power demand of the power consumption unit. | 12-26-2013 |
20140196027 | LOW-RISK SERVER CONSOLIDATION - A method for virtual machine (VM) consolidation includes providing a plurality of resource usage levels for a set of VMs to be consolidated including a first resource usage level and a last resource usage level. An optimization problem is formulated to minimize an objective function such that any of one or more VMs of a set of VMs to be allocated to a target server may be assigned to the first resource level and remaining VMs of the set may be assigned to the last resource level while not exceeding a resource capacity of the target server. The set of VMs are allocated to a number of servers is accordance with the formulating to consolidate the set of VMs. | 07-10-2014 |
Patent application number | Description | Published |
20130085974 | USING CYCLIC MARKOV DECISION PROCESS TO DETERMINE OPTIMUM POLICY - A method for determining an optimum policy by using a Markov decision process in which T subspaces each have at least one state having a cyclic structure includes identifying, with a processor, subspaces that are part of a state space; selecting a t-th (t is a natural number, t≦T) subspace among the identified subspaces; computing a probability of, and an expected value of a cost of, reaching from one or more states in the selected t-th subspace to one or more states in the t-th subspace in a following cycle; and recursively computing a value and an expected value of a cost based on the computed probability and expected value of the cost, in a sequential manner starting from a (t −1)-th subspace. | 04-04-2013 |
20130085983 | USING CYCLIC MARKOV DECISION PROCESS TO DETERMINE OPTIMUM POLICY - A method for determining an optimum policy by using a Markov decision process in which T subspaces each have at least one state having a cyclic structure includes identifying, with a processor, subspaces that are part of a state space; selecting a t-th (t is a natural number, t≦T) subspace among the identified subspaces; computing a probability of, and an expected value of a cost of, reaching from one or more states in the selected t-th subspace to one or more states in the t-th subspace in a following cycle; and recursively computing a value and an expected value of a cost based on the computed probability and expected value of the cost, in a sequential manner starting from a (t−1)-th subspace. | 04-04-2013 |
20130179380 | PREDICTION METHOD, PREDICTION SYSTEM AND PROGRAM - A method for predicting an output variable from explanatory values provided as sets of combinations of discrete variables and continuous variables includes receiving input data that contains the explanatory variables to predict the output variable; searching for each element in the combinations for elements in a plurality of sets with matching discrete variables using training data which the output variable has been observed; applying a function giving the degree of similarity between two sets weighed by a scale variable to each element in the input data, and to one or more elements found in the elements of the input data to calculate function values, and calculating the sum of the function values for all of the elements in the input data; and applying the calculated sum for each element to a prediction equation for predicting the output variable to calculate a prediction value of the output variable for each element. | 07-11-2013 |
20130184992 | METHOD, APPARATUS AND COMPUTER PROGRAM FOR ESTIMATING DRIVER'S PERSONALITY OF ROUTE SELECTION - A method for selecting a route from a departure point to an arrival point includes acquiring information concerning a departure point and an arrival point and information concerning a route from the departure point to the arrival point; generating a plurality of basic routes; calculating a parameter of an evaluation function that yields the selected route as an optimum route; generating a new route using the calculated parameter, determining whether or not the generated new route is identical to the selected route; on a condition that the generated new route is not identical to the selected route, adding the generated new route to the basic routes, recalculating the parameter, generating a new route, and comparing the new route with the selected route; and if the new route is identical to the selected route, storing the parameter when the new data becomes identical to the selected route. | 07-18-2013 |
20130318023 | UPDATING POLICY PARAMETERS UNDER MARKOV DECISION PROCESS SYSTEM ENVIRONMENT - Embodiments relate to updating a parameter defining a policy under a Markov decision process system environment. An aspect includes updating the policy parameter stored in a storage section of a controller according to an update equation. The update equation includes a term for decreasing a weighted sum of expected hitting times over a first state (s) and a second state (s′) of a statistic on the number of steps required to make a first state transition from the first state (s) to the second state (s′). | 11-28-2013 |
20130325764 | UPDATING POLICY PARAMETERS UNDER MARKOV DECISION PROCESS SYSTEM ENVIRONMENT - Embodiments relate to updating a parameter defining a policy under a Markov decision process system environment. An aspect includes updating the policy parameter stored in a storage section of a controller according to an update equation. The update equation includes a term for decreasing a weighted sum of expected hitting times over a first state (s) and a second state (s′) of a statistic on the number of steps required to make a first state transition from the first state (s) to the second state (s′). | 12-05-2013 |