27results about "Computing models" patented technology

To calculate, with satisfactory accuracy and with less computing amount, an approximate Pareto solution group in a multi-purpose minimization problem.SOLUTION: A computing apparatus according to the present invention has a prediction unit, a selection unit, an update unit, a repeat control unit, and an output unit. The prediction unit executes prediction processing for predicting an increased amount of a Pareto hyper volume by using a wight pattern corresponding to each of a plurality of weight patterns. The selection unit executes selection processing for selecting a maximum weight pattern with a maximum increased amount. The update unit acquires, from a solver device, a plurality of solutions in a problem of minimizing a synthesized object function as a linear weighted sum of a plurality of object functions and a plurality of weight coefficient represented by the maximum weight patterns to add them to a candidate solution group, thereby carrying out update processing for updating the candidate solution group. The repeat control unit repeatedly controls a series of the prediction processing, the selection processing, and the update processing. The output unit outputs, as an approximate Pareto solution group, a group including a non-dominated solution of the candidate solution group.SELECTED DRAWING: Figure 6

This information processing device comprises: an acquisition unit that acquires one or a plurality of data points; a generation unit that references a plurality of data points including the data points acquired by the acquisition unit and generates, for each step, an internal polyhedron defined by the plurality of data points and an external polyhedron defined by the plurality of data points; and an identification unit that identifies, from a difference set between a set of weight vectors obtained by referencing the internal polyhedron in the current step and a set of weight vectors obtained by referencing the internal polyhedron in the previous step, a target weight vector by referencing a difference between an optimization result obtained by referencing a data point included in the internal polyhedron in the current step and an optimization result obtained by referencing a data point included in the external polyhedron in the current step.

It provides a control technique with a high degree of freedom for the available cost function. [Solution] The control device calculates the input sequence U that minimizes the cost function Φ(U). The cost function Φ(U) is a probability distribution Q corresponding to the initial state x0 and the input sequence U. U The probability distribution Q of the sum of the first cost S(V;x0), which is a function of the input sequence V, and the second cost T(U), which is a function of the input sequence U. U This is the expected value under the following conditions. The first cost S(V;x0) is the state sequence X(V;x0) corresponding to the input sequence V, and the states x0, x1, ..., x T State-dependent costs corresponding to each of the following: c(x0), c(x1), ..., c(x T-1 ),φ(x T It is defined by S(V;x0)=C(X(V;x0)) using a state sequence-dependent cost C(X) that cannot be decomposed into a sum of ).

This information processing device comprises: an acquisition unit that acquires one or more data points; a generation unit that refers to a plurality of data points including the data points acquired by the acquisition means, and generates an internal polyhedron defined by the plurality of data points and an external polyhedron defined by the plurality of data points; and a specification unit that, from a set of weight vectors obtained by referring to the internal polyhedron, specifies a target weight vector by referring to the difference between an optimization result obtained by referring to the data points included in the internal polyhedron and an optimization result obtained by referring to the data points included in the external polyhedron.

This method efficiently obtains the optimal or approximate solution to combinatorial optimization problems using large-scale language models. [Solution] The search device comprises: a first acquisition unit that acquires information related to the problem setting of a combinatorial optimization problem as natural language; a second acquisition unit that acquires an image of a directed graph composed of nodes and edges, in which the orientation of the edges connecting the nodes is set, and update instructions for the image of the directed graph in an iterative process for searching for the optimal solution; a search unit that inputs the natural language acquired by the first acquisition unit, the image of the directed graph and the update instructions acquired by the second acquisition unit into a large-scale language model, and searches for the optimal solution of the problem setting expressed in the input natural language using the orientation of the edges included in the directed graph and an iterative process accompanied by update instructions; and an output unit that outputs at least one of the optimal solution obtained by the search unit and an approximate solution of the optimal solution.

This system provides an information processing system that can reduce the time it takes to transmit data for other computers to perform processing. [Solution] The client includes a splitting unit that repeatedly generates an array by splitting the numerical component representing the most significant digit of each element of an input array whose elements are numbers, and sends it to the server. The splitting unit then subtracts the numerical values ​​of the split array from the numerical values ​​of the original array element by element, and generates an array by splitting the numerical component representing the most significant digit of the remaining element, and sends it to the server. The server includes a merging unit that, each time it receives an array from the client, performs calculations using a new array generated by combining the numerical values ​​of the received array element by element of the stored array.

The present invention belongs to the technical field of automatic driving, and particularly relates to a method, device, recording medium and electronic device for collision control by man-machine collaborative driving. The collision control method by man-machine collaborative driving includes the steps of: establishing a man-machine path tracking control game model corresponding to man-machine interaction behavior based on a driver's deterministic steering torque and a driver's random steering torque (S101); solving the man-machine path tracking control game model to obtain man-machine torque collision information (S102); and determining a shared control strategy based on the man-machine torque collision information, thereby controlling the vehicle based on the shared control strategy (S103). The collision control method by man-machine collaborative driving provided in the present invention can improve the accuracy of vehicle control by describing the mapping relationship between the difference in man-machine decision-making and the man-machine steering torque interaction.

A data processing device (10) comprises a Gram matrix norm calculation unit (11), a lower bound calculation unit (12), a threshold value update unit (13), an upper bound calculation unit (14), and a candidate set update unit (15). The Gram matrix norm calculation unit (11) calculates a norm for each row of a Gram matrix of data including a plurality of parameters. The lower bound calculation unit (12) calculates a lower bound of an absolute value of each of the parameters on the basis of the norm. The threshold value update unit (13) updates a threshold value on the basis of the lower bound. The upper bound calculation unit (14) calculates an upper bound of the absolute value of each of the parameters on the basis of the norm. The candidate set update unit (15) updates a candidate set, which is at least a portion of the parameters, on the basis of the lower bound, the threshold value, and the upper bound.

The present invention provides an information processing method that allows a third party to confirm that there are no other candidates that could be valid besides the one obtained as a result of the determination, without having to re-execute the search process or the feasibility determination. [Solution] The method acquires input information related to multiple elements, generates a set of elements to be processed, generates candidates that can be derived from the set of elements to be processed, determines whether the derived candidates are valid or not based on predetermined validity conditions, if a candidate that does not satisfy the validity conditions is obtained, other candidates that have a predetermined relationship with that candidate are also treated as invalid, identifies the range of invalid candidates, selects a representative candidate from among the candidates that satisfy the validity conditions based on predetermined ordering rules, generates a candidate absence trail expressed in a form that can be verified by a third party, and outputs or retains the representative candidate and the candidate absence trail externally.

A model generation device 100 according to the present disclosure comprises: a determination unit 121 that, when a mathematical optimization problem represented by a mathematical expression having a plurality of terms is changed, determines a method for formulating a term corresponding to the change on the basis of the formulated mathematical optimization problem; and an update unit 122 that converts the term corresponding to the change by means of the determined formulation method and updates the formulated mathematical optimization problem.

This provides an optimization dispatch method for a fully decentralized integrated energy system based on preset time settings. [Solution] The optimization dispatch method establishes an integrated energy system operation optimization model and constructs an objective function with the goal of minimizing the total cost of the integrated energy system as the dispatch problem for the integrated energy system. The objective function is subject to safe operation constraints, which include power balance constraints, power upper / lower limit constraints, and operation ramp rate constraints. The method also assumes that the communication topology of the source, load, storage, and station sides of the integrated energy system is an undirected connected graph and solves the objective function using a fully distributed optimization algorithm with a preset time based on TBG so that the integrated energy system operation optimization model converges within the preset time and obtains the optimal output strategy for the integrated energy system.

To reduce calculation cost.SOLUTION: A storage section 11 stores values of a plurality of discrete variables included in an evaluation function and values of a plurality of local fields for a plurality of respective replicas, and storage sections 12b1 to 12bR provided corresponding to the plurality of respective replicas store the values of the plurality of corresponding discrete variables and the values of the plurality of corresponding local fields. A processing section 12 repeats processing of updating any value of the plurality of discrete variables, the values of the evaluation function, and the values of the plurality of local fields, on the basis of a temperature to be set and the values of the plurality of local fields stored in the storage sections 12b1 to 12bR for the plurality of respective replicas, performs re-sampling processing of a population annealing method every time the number of repetition reaches a predetermined number, reads the values of the plurality of discrete variables and the values of the plurality of local fields for a first replica from the storage section 11 when a second replica which is a duplicate of the first replica is generated, and stores them in a storage section 12bi provided corresponding to the second replica.SELECTED DRAWING: Figure 5

The problem of the time required to solve a constrained combinatorial optimization problem becoming excessively long. [Solution] The information processing device of the present disclosure includes: a priority setting unit that sets the priority of constraints according to the content of the constraints set in the optimization problem; a fixed value setting unit that sets the variables included in the constraints to fixed values ​​of predetermined values ​​based on fixed values ​​set in advance for the variables and the content of the constraints, in an order according to the priority; and a solution unit that solves the optimization problem with the variables included in the constraints set to fixed values.

The objective is to provide an information processing device, information processing system, program, and information processing method that can assist in creating an Ising model for solving the problem of finding the optimal solution for composite materials with formulation constraints using an annealing-type optimization machine. [Solution] An information processing device that receives bit information representing the optimal solution calculated by an annealing type optimization machine, converts the bit information into composition information of a composite material and displays it on a display device, and assumes that the bit information is configured to include, for each substance mixed in the composite material, an auxiliary bit indicating whether or not the substance is included in the composite material, and a sequence of quantity bits indicating the amount of the substance, and comprises a conversion unit that determines whether or not each substance is included based on the auxiliary bits, calculates the amount of each substance based on the sequence of quantity bits, and generates composition information including identification information and quantity of each substance, and a display unit that displays the composition information on a display device.

The present invention provides an apparatus and method for performing vector × vector multiplication within an optical domain. [Solution] The device includes: a plurality of optical signal generators arranged to emit beams of light having different carrier wavelengths, each modulated by an input signal that models each variable of a vector of variables; one or more sets of optical modulator elements arranged to receive beams of light modulated by different input signals from the input signals and to apply corresponding weights from a weighting vector to generate weighted optical signals; each set of optical sensor elements in the set; and one or more optical combining elements arranged to guide the weighted optical signals of each set onto their respective optical sensor elements and thereby generate their respective outputs in the form of analog electronic signals that sum the weighted optical signals of each set.

This route planning device is for planning routes of a plurality of agents, and is characterized by comprising: an information acquisition unit for acquiring a start state and a goal state of each of the plurality of agents; and a homotopy class calculation unit for calculating a homotopy class of a route from the start state of the plurality of agents to the state after movement.

This information processing device is equipped with at least one processor. Said processor performs processing which involves: receiving an input of structure data which expresses the structure of a chemical substance and an evaluation function for evaluating the specific performance of the chemical substance; extracting a known chemical substance, the basic structure of which is shared by the input structure represented by the inputted structure data, from a database for recording structure data which expresses said chemical substance structure for each of a plurality of known chemical substances; generating a novel structure by modifying the input structure on the basis of the extracted known chemical substance structure or modifying the extracted known chemical substance structure; deriving an indicator value pertaining to specific performance for the generated novel structure; deriving an evaluation value for the novel structure on the basis of the derived indicator value and the evaluation function; and displaying the novel structure according to the evaluation value.

This optimization device (2) is configured to comprise: a condition acquisition unit (11) that acquires a condition to be used for optimization calculation; a prediction information acquisition unit (12) that acquires prediction information, which is information predicted on the basis of the condition; a restriction information acquisition unit (13) that acquires restriction information for imposing a restriction on the optimization calculation on the basis of the prediction information; and an optimization unit (14) that optimizes a multi-objective function on the basis of the condition and the restriction information.

According to one aspect of the invention, when an optimal target of an action is calculated by using a model based on a graph configured with a plurality of vertices indicating a state represented by a degree of achievement of the action and a required time for the achievement of the action and a plurality of edges indicating the action that a person can take in the state, a reward for achieving the state, a maximum value of the required time, and a present bias parameter for weighting a cost for taking the action in a time series are acquired. The optimal target for the action is calculated by substituting the reward, the maximum value of the required time, and the present bias parameter into an optimal target calculation formula generated based on a simplified model in which a shape of the graph is restricted by reflecting a present bias.

The present invention refers to a method for at least partially decentralized calculation of the state of health (SH1, SH2) of at least one wind turbine (1) based on corresponding wind turbine individual data (D) to enable a diagnosis as well as prescriptive information to enable avoidance of occurrence of pre-known specific failure modes.

The problem of the time required to solve a constrained combinatorial optimization problem becoming excessively long. [Solution] The information processing device of the present disclosure comprises a search unit that searches for solutions to variables included in an optimization problem, a state recording unit that records changes in the state of variables during the solution search process, and a constantization unit that converts the variables included in the optimization problem into constants based on the changes in state, wherein the search unit performs a solution search for the optimization problem in the state in which the variables have been converted into constants.

An optimization processing device 1X mainly comprises an acquisition means 50X, a division pattern determination means 55X, and a solution determination means 56X. The acquisition means 50X acquires information about an optimization problem for which a solution is to be determined. The division pattern determination means 55X determines a division pattern for dividing an optimization problem into a plurality of partial problems, on the basis of a machine learning model obtained by machine learning a relationship between an optimization problem and a division pattern applied to the optimization problem, and information about the optimization problem for which a solution is to be determined. The solution determination means 56X determines the solution of the optimization problem on the basis of the plurality of partial problems obtained by dividing the optimization problem by the division pattern.

[PROBLEM TO BE SOLVED] To provide a large-scale and highly accurate optical Ising calculation device capable of significantly increasing the number of spins, realizing optimum binary branching for a problem to be solved by an arbitrary nonlinear function, and stably and more quickly converging. [SOLUTION] This invention comprises: a pulse light source 1; an optical fiber loop 3 into which an optical pulse from the pulse light source 1 is introduced; an erbium-added optical fiber amplifier 4 provided in the optical fiber loop 3; a homodyne detection circuit 5 for detecting the optical pulse from the optical fiber loop 3; a matrix / nonlinear arithmetic circuit 6 for digitally calculating an interaction function and a nonlinear function for binary branching with respect to the optical pulse detected by the homodyne detection circuit 5; and an AM optical modulator 2 to which the optical pulse from the pulse light source 1 and information obtained in the digital calculation by the matrix / nonlinear arithmetic circuit 6 are inputted, and which modulates the inputted optical pulse and then makes the modulated optical pulse enter the optical fiber loop 3.