28 results about "Computational problem" patented technology

The invention discloses an air-water cross-medium shell whole-course trajectory firing table compiling method, and belongs to the technical field of outer ballistic cross-medium trajectory correction theories, cross-medium fluid dynamics and artillery firing table compiling. The method comprises numerical simulation of an air trajectory, a water entry trajectory and a water trajectory and a whole-course trajectory shot table fast interpolation algorithm. Wherein the air trajectory is solved based on a six-degree-of-freedom trajectory model; the water entry trajectory and the underwater trajectory are obtained by solving a fluid control equation by adopting a fluid volume (VOF) multiphase flow model, a turbulence model, a cavitation model and a dynamic grid technology; the full-ballistic shot table fast interpolation algorithm is realized based on a least square method and a linear interpolation algorithm. The method is suitable for the cannonball trajectory air-water cross-medium condition, the rapid and accurate calculation problem of firing elements of an artillery fire control system in the air-water cross-medium environment of the firing table is solved, the continuity of the cross-medium full-trajectory firing table is achieved, the blank of the cross-medium firing table is filled up, and the cross-domain combat ability of an artillery weapon system is effectively improved.

The invention discloses a car insurance secret state modeling method based on multi-key fully homomorphic encryption, and belongs to the technical field of big data and data security. The method comprises the following steps: each participant independently generates an encryption key pair, encrypts local data, and uploads the encrypted data to a secure computing environment; performing generalized linear regression (GLM) model training and prediction in the ciphertext domain; after training is completed, all parties perform collaborative decryption through private key shares to obtain a model output result; according to the method, fully homomorphic encryption (FHE), privacy protection modeling and a generalized linear regression (GLM) algorithm are comprehensively applied, so that joint modeling and prediction of multi-party car insurance data in a ciphertext state are realized, and the privacy protection and efficient calculation problems in car insurance risk modeling and pricing participated by multiple parties are solved; and the requirements of effective fusion and privacy protection of multi-party data are met.

A method for managing a group of processing units configured to solve a cryptographic problem. The method includes a control unit of the group for: connecting to at least one computing devices network which collaborate in the search for a solution to a cryptographic problem by calculating possible solutions to the problem, determining a computing power available for each processing unit of the group; calculating a computing power of the group, based on the available computing power of each processing unit of the group, determining possible remaining solutions of the cryptographic problem which are to be calculated by the computing devices network, determining whether the computing power available of the group allows calculation of the possible remaining solutions in a predetermined time, and in the affirmative case, allocating the computing power available in the group of processing units to the calculation of the solution of the cryptographic problem.

Systems and methods in accordance with the present disclosure can implement a parallel processing system, such as a graphics processing unit (GPU)-based system, to generate solutions to complex computational problems. Aspects of this technical solution can retrieve a plurality of solutions each representing a plurality of values in a multi-dimensional space, allocate, to one or more processing units associated with the one or more circuits and having a parallelized configuration, one or more of the plurality of solutions, modify, by the one or more processing units according to the parallelized configuration, at least one value of the one or more solutions allocated to the one or more processing units, to determine a plurality of modified solutions, and output, from the plurality of modified solutions, according to one or more criteria indicating a diversity among the plurality of modified solutions, a selected solution.

The invention discloses an intelligent inspection problem identification and data processing method and system based on a multi-modal large model, and relates to the technical field of intelligent inspection data processing, and the method comprises the steps: carrying out the preprocessing of multi-modal original data collected in the inspection process, and extracting the feature representation corresponding to each modal; inputting the feature representation into a cross-modal fusion network, and obtaining a fusion feature representation by constructing an inter-modal weight matrix; inputting the fusion feature representation into a pre-trained multi-modal large model for identification processing, adopting a multi-label classification algorithm to complete inspection problem type identification and calculate a problem risk score, and outputting a problem identification result; and constructing a correlation graph by taking a problem identification result as a node, analyzing the correlation strength between the problems by using a graph neural network, identifying a problem propagation path and an influence range, and generating a structured patrol report. According to the method, the accuracy of patrol problem identification, the scientificity of risk assessment and the structuralization and interpretability of result expression can be improved.

The application discloses an intelligent retrieval method and device for a knowledge base and a storage medium, and belongs to the technical field of information processing and artificial intelligence. The method comprises the following steps: acquiring a user question, and constructing a feature fusion model and a fine arrangement language model; extracting a knowledge text feature set of a preset knowledge base based on the feature fusion model, and associating the knowledge text feature set with the knowledge base to obtain a knowledge database; extracting a question feature of the user question based on the feature fusion model; matching the question feature with the knowledge database piece by piece, and calculating the similarity between the question feature and the knowledge text features of each knowledge point in the knowledge base based on a similarity algorithm to obtain a coarse arrangement set; and performing fine arrangement on the knowledge points of the knowledge base corresponding to the coarse arrangement set based on the fine arrangement language model by a text matching algorithm to obtain a retrieval result. The arrangement accuracy and the generalization of the intelligent retrieval for the knowledge base are improved by the method.

The present invention relates to a method for enhancing the privacy of delegated quantum computing, the method comprising a client (A) whose objective is to solve a computational problem based on sensitive data and / or using a sensitive algorithm, and a cloud computing service provider (B) which has superior quantum computing capabilities to the client (A) and is therefore capable of solving the problem and / or executing the client's desired algorithm, the method comprising a sequence including a) an optical emitter (10) controlled by the client (A) emits at least one pulse (11) having a specific quantum state (S1); b) a quantum emitter (20) controlled by the provider (B) receives the pulse (11); and c) the quantum emitter (20) emits a single photon (21) supporting a photon qubit (Q2), thereby defining a relationship between the quantum state (S1) of the pulse (11) and the photon qubit (Q2). The present invention also relates to a system for carrying out this method.

The invention discloses a fusion calculation method of a quantum classical hybrid calculation system and a related device, and the method comprises the steps: carrying out the splitting processing of a task request applied by the quantum classical hybrid calculation system, so as to obtain calculation subtasks independently completed by quantum calculation, classical calculation and intelligent calculation; in response to the split calculation sub-task type, configuring the heterogeneous calculation resources to the corresponding calculation sub-tasks; the heterogeneous computing resources comprise quantum computing resources, classical computing resources and intelligent computing resources; the computing resources are evaluated and analyzed according to the resource evaluation and intelligent analysis module to obtain a corresponding scheduling decision basis; inserting the calculation subtasks into the corresponding task queues, and scheduling the task queues based on the scheduling decision basis, the user-defined scheduling strategy and the first linkage relationship of the calculation subtasks; according to the method, a classical and efficient fusion calculation technical scheme of quantum is provided, and an efficient solution is provided for a complex calculation problem through computing power complementation.

The invention relates to the technical field of cloud edge computing, and particularly provides a cloud task migration decision-making method based on deep reinforcement learning, which comprises the following steps of: constructing a target function by taking maximization of a cloud task success rate as a target; a deep reinforcement learning framework is constructed, and an LSTM network model is adopted to observe and predict the current state of the system based on the system history; describing a decision process under the condition that the system environment is uncertain based on a partially observable Markov decision process; and taking the current state of the system as the input of the improved deep reinforcement learning model, and obtaining a migration strategy of the cloud task based on the improved deep learning model. According to the method, a proper service migration mechanism is designed aiming at the cloud edge calculation problem in a mobile state, so that the low delay of the service is ensured, and modeling is carried out on the delay and reliability of the service migration process; and a DCPPOSM algorithm based on deep reinforcement learning is designed for effective migration decision making with an optimization objective of maximizing a task execution success rate.

The invention discloses a virtual power plant distributed optimization and feasible region analysis method and system. The method comprises the following steps: establishing an interactive physical model of a virtual power plant and a power distribution network; based on an interactive physical model, relaxation decoupling is carried out on wide-area and neighborhood time coupling constraints caused by the state of charge of the energy storage system through a Lyapunov optimization theory, and a multi-period optimization problem of the virtual power plant is converted into a single-period optimization sub-problem; aiming at the single-period optimization sub-problem, adopting a particle swarm optimization algorithm HSIPSO improved based on a hybrid strategy and fusing the particle swarm optimization algorithm HSIPSO into an ADMM distributed optimization framework to form an ADMM-HSIPSO algorithm, and carrying out distributed solution on the single-period optimization sub-problem; converting a multi-period virtual power plant feasible region representation problem into a calculation problem of each scheduling period feasible region; a mathematical model of the feasible region of the virtual power plant is constructed, and an ADMM-HSIPSO algorithm is adopted for solving; the coordination and unification of the optimal distribution of the dispatching power of the power distribution network among the virtual power plants and the privacy protection in the virtual power plants are realized.

A distance calculation system and method for clustering algorithms are proposed. Based on the information distance theory with Coriolis complexity, a unified method for information distance calculation, lossless compressed distance calculation, and lossy compressed distance calculation is designed, and a compressed distance calculation system under lossy conditions is formed. This solves the problem of lossy compressed distance calculation for continuous data such as images and videos, and forms a complete and unified compressed distance calculation method and system applicable to any data type.

The application relates to a coarse-fine grid fast interpolation technology for wall turbulence calculation, aiming at solving the problems of large calculation amount and complex implementation process of an existing interpolation method. Half of the minimum grid spacing of a fine grid is used as a judgment standard to intelligently switch the interpolation mode. For each fine grid point, when the distance between the fine grid point and the nearest coarse grid point is less than the standard, the physical value of the nearest coarse grid point is directly assigned to the fine grid point; otherwise, if the distance is greater than or equal to the standard, the inverse distance weighted average method is used for interpolation. The method simplifies the complex calculation problem by taking half of the minimum fine grid size as the standard for judging whether the fine grid point is directly assigned by the physical quantity on the nearest coarse grid value point, under the premise of ensuring the distortionlessness of physical information. The method avoids the complicated calculation process in the traditional method, effectively reduces the algorithm complexity, and significantly improves the speed and efficiency of the interpolation calculation.

The invention provides a multi-modal data fusion method based on a neural network algorithm, and the method comprises the steps: carrying out the data cleaning, feature extraction and normalization processing of original data, and obtaining a feature vector of the cleaned data; establishing a neural network architecture model and setting a plurality of different model branches, inputting different types of data into different model branches to obtain feature vectors of different modals, performing information integration to obtain comprehensive feature vectors of a multi-modal neural network model, and training the model branches to obtain prediction results of the model branches; carrying out fusion and feature extraction on the feature vectors of different modes through a fusion layer to obtain fusion features; and training the neural network architecture model, and predicting and analyzing the multi-modal data through the trained neural network architecture model. According to the method, the characteristics of each modal data can be better utilized, the correlation between the data is clearly expressed, and the calculation problem of large-scale multi-modal data is effectively solved.

The invention provides a construction method and device of a light quantum computing system, a medium and a light quantum computer, and relates to the technical field of quantum computing. The method comprises the following steps: determining a target transformation matrix for solving a target quantum calculation problem; constructing an initial light quantum computing system based on the complexity of the target quantum computing problem; determining an equivalent transformation matrix corresponding to the initial light quantum calculation system; and based on the difference between the equivalent transformation matrix and the target transformation matrix, adjusting system parameters of the initial light quantum computing system to obtain the light quantum computing system. According to the embodiment of the invention, accurate parameter mapping can be realized, so that system construction is accurately carried out.

The invention relates to the technical field of artificial intelligence, and discloses a calculation demand processing method and device, a medium and a program product. The method comprises the steps of obtaining an original calculation problem expressed by a natural language and input by a user, and processing the original calculation problem through a pre-trained demand extraction model to extract a formula retrieval keyword; matching in a preset formula knowledge base according to the formula retrieval keyword to obtain matched candidate formula data; calling a plurality of pre-trained code generation models in parallel, and generating formula calculation codes according to the candidate formula data and the original calculation problem; and running each formula calculation code by adopting a code sandbox, obtaining each initial calculation result, and determining a final calculation result according to each initial calculation result. Accurate understanding of calculation requirements can be achieved, the accuracy of calculation requirement processing can be improved, and the effective utilization rate of calculation power resources can be improved.

The application provides a graph question answering method, device, system and medium, the method comprises the following steps: calculating the similarity between a question vector and a candidate vector to determine a target vector in the candidate vector, wherein the question vector is a vector obtained by vector conversion based on a user question, the candidate vector is a vector set obtained by vector conversion based on a cut triple set, the similarity between the target vector and the question vector is greater than the similarity between other candidate vectors in the candidate vector and the question vector; answering the user question according to the triple corresponding to the target vector. In this way, when the similarity is calculated, the interference of the answer part in the triple on the question and answer is reduced, and the accuracy of the graph question answering system in answering the user question is improved.

This invention discloses a concept graph-based method for enhancing astronomical computational reasoning instructions, comprising the following steps: obtaining seed problems labeled with subdomains and topics as basic input; extracting knowledge points from the seed problems using a large language model to establish a knowledge framework covering subdomains, topics, and knowledge points; and transforming problem instances into conceptual representations; constructing a concept graph based on the knowledge framework; executing a dynamic random walk algorithm on the concept graph to output a complete concept combination; and using the complete concept combination to guide the large language model in generating astronomical computational problems and corresponding reasoning processes through example matching, data deduplication, and thought chain distillation. This invention, by constructing a concept graph and employing a random walk strategy, improves the diversity and logical rigor of the generated data, providing a new path for optimizing astronomical computational reasoning instructions.

The application discloses a remote supervision quality alarm method and system based on a large language model, and the method comprises the following steps: S1, uploading and analyzing technical specification documents, converting the documents into quality specification requirements in natural language expression; S2, performing block processing to obtain multiple technical specification items, converting the technical specification items into embedding vectors by using a large language model, and constructing a knowledge base; S3, collecting structured supervision data of a production environment in real time, constructing a data description question and a question embedding vector; S4, calculating the similarity between the question embedding vector and each embedding vector in the knowledge base, and screening out relevant technical specification items based on a similarity threshold; and S5, combining the data description question and the relevant technical specification items into a prompt, inputting the prompt into the large language model, and performing alarm according to the output result of the large language model. According to the application, whether the data collected from the production environment meets the requirements of the specification file can be judged based on the bidding technical specification book and the bid file specified by a user, and alarm can be performed.

The invention discloses a reliability analysis method for a composite fuselage panel structure based on chaos polynomial expansion. The reliability analysis method comprises the steps that a finite element model of the composite fuselage panel structure is obtained through a finite element method; determining all failure events of the structure and establishing a limit state function; establishing an uncertain parameter normal distribution model, obtaining a training sample point and a corresponding limit state function response maximum value, and establishing a chaos polynomial agent model; carrying out Monte Carlo simulation in combination with the proxy model to calculate a failure probability, obtaining a failure branch point based on a branch and limit theory, establishing a material attribute degradation criterion, and reducing the rigidity of a single-layer board corresponding to the failure branch point; and obtaining all failure paths of the structure and calculating the system failure probability of the structure. The method can solve the problem of reliability calculation of the composite fuselage wallboard structure containing uncertain parameters, and can effectively improve the calculation efficiency and reduce the redundancy of reliability design on the premise of ensuring that the calculation precision meets the engineering requirements.

The application belongs to the technical field of question and answer matching, and provides a question and answer matching method and system based on question pair matching and question and answer pair matching. After obtaining a question, a preset question-question matching model is used to obtain question vector representation in the question and vector representation of questions in a preset question and answer library, and on this basis, the similarity between the question in the question and the question in the preset question and answer library is calculated to preliminarily screen the question and answer library. Then, a preset question-answer matching model is used to obtain question vector representation in the question and vector representation of answers in the screened question and answer library, and on this basis, the similarity between the question in the question and the answer in the screened question and answer library is calculated, and the question and answer pair with the highest similarity score is taken as the final matched question and answer pair of the obtained question. In the question and answer pair matching process, the two times of similarity calculation realize preliminary screening and final determination of the question and answer pair, improve the accuracy of the similarity calculation, and ensure the matching effect.

The invention discloses a mechanical arm hand-eye calibration method using an optical three-dimensional motion capture system, and belongs to the technical field of robot vision calibration. The method comprises the steps that firstly, the positions of cameras and target points are arranged, each target point is made to be within the view field of at least three cameras, a mechanical arm demonstrator is used for setting poses needed by calibration, and three-dimensional position data of the target points under the corresponding poses are collected; then, according to the measured data, a point set matching algorithm is used for fitting rigid body motion of the tail end of the mechanical arm, and the calibrated mathematical model is converted into AX = XB; finally, the problem of solving the equation is converted into the least square calculation problem through the Lie algebra, and a transformation matrix of a mechanical arm base coordinate system-world coordinate system is obtained based on singular value decomposition; according to the calibration method based on the three-dimensional position data, kinematics fusion of a motion capture system and a mechanical arm system can be achieved, and the calibration method can be directly applied to mechanical arm measurement.

A computing power distribution method and apparatus, and a computing power server. The method includes: performing computational problem planning processing on a computational problem to obtain at least one sub-computational problem corresponding to the computational problem and a target algorithm type and computing mode corresponding to each sub-computational problem; according to the at least one sub-computational problem corresponding to the computational problem and the target algorithm type and computing mode corresponding to each sub-computational problem, determining at least one computational problem computing task corresponding to each sub-computational problem; according to dynamic computing power information of computing nodes and computing power calling relationships, determining at least one target node for each computational problem computing task; sending a computing power control command to the target nodes; and receiving computing results returned by the target nodes, and send the computing results to an application node.

The present application relates to the technical field of geographic information analysis, and discloses a fast space-time road network K function graph generation method, system, terminal and storage medium based on a range tree and a prefix count array, which comprises the following steps: for the calculation problem of a single space-time road network K function and the calculation problem of generating a space-time road network K function graph, the data structures of a range tree and a prefix count array are used to solve the problems respectively, different methods are selected according to the structures on each edge, and the space-time road network K functions of multiple thresholds are calculated by using the selected structures. The present application selects different data structures for calculation according to different calculation problems, and the time complexity is significantly reduced while the space complexity and the accuracy remain unchanged.

The present disclosure relates to a hybrid quantum computing architecture for solving systems of linear binary relations. A method for driving a quantum computing network to find a solution to a computational problem comprising a system of linear binary relations is provided, the method comprising: initializing a computational qubit, applying a set of quantum gates to the computational qubit and measuring a result state, and determining a solution to the system of linear binary relations associated with a variational parameter based on a plurality of candidate solutions for individual relations of the system of linear binary relations encoded in the result state, wherein a state of the register qubit is associated with a selected one of the binary relations and a state of the ancilla qubit is associated with a candidate solution for the selected one of the binary relations.

The invention discloses a chip parasitic resistance network visualization method, electronic equipment and a storage medium, and relates to the technical field of chips, and the method comprises the steps: obtaining two-dimensional netlist data of parasitic resistance networks generated by all conductor stacking structures in a chip according to a parasitic parameter file of the chip, obtaining a stack structure data table of the chip according to the process parameter file of the chip, and obtaining three-dimensional netlist data of the parasitic resistance network according to the stack structure data table and the two-dimensional netlist data, establishing a first three-dimensional model of the parasitic resistance network according to the three-dimensional netlist data, establishing a second three-dimensional model for generating each stacked structure of the parasitic resistance network according to the process parameter file, and displaying at least part of the first three-dimensional model and a target second three-dimensional model, a user can conveniently and quickly search calculation problems existing in the back-end simulation calculation process based on the three-dimensional information storage table, and the problem search efficiency and accuracy are improved.

This invention relates to the field of digital twin and watershed environment monitoring simulation technology, specifically a watershed environment data simulation and extrapolation system based on digital twin technology. The system includes: a digital twin management center for retrieving multi-source heterogeneous monitoring data of the watershed environment to obtain an aligned environmental data sequence; a causal coupling analysis unit for obtaining steady-state logic signals or dynamic decoupling signals; when a dynamic decoupling signal is generated, a topology adaptive reconstruction unit for performing structural mutation identification and feedback analysis on the computational graph of the digital twin model to obtain a reconstructed topology graph; and when a steady-state logic signal is generated, a simulation and extrapolation execution unit for performing environmental evolution extrapolation analysis on the aligned environmental data sequence based on the current computational graph to obtain simulation and extrapolation results. This invention effectively avoids model calculation divergence or misleading output caused by sensor failures and solves the computational problems caused by the heterogeneity of multi-source data.

The application provides a construction method and device of a light quantum computing system, a medium and a light quantum computer, and relates to the technical field of quantum computing. The method comprises the following steps: determining a target transformation matrix for solving a target quantum computing problem; constructing an initial light quantum computing system based on the complexity of the target quantum computing problem; determining an equivalent transformation matrix corresponding to the initial light quantum computing system; and adjusting system parameters of the initial light quantum computing system based on the difference between the equivalent transformation matrix and the target transformation matrix to obtain the light quantum computing system. The embodiments of the application can realize accurate parameter mapping, thereby accurately constructing the system.

The invention relates to the technical field of power grid intelligent scheduling and artificial intelligence decision making, in particular to a power grid intelligent scheduling decision making method, device and equipment based on retrieval enhancement generation, and the method comprises the steps: extracting a power grid scheduling problem text in a dispatcher query text; the power grid dispatching problem text is input into the fine-tuned pre-training language model, a candidate knowledge text set is inquired from a power grid dispatching knowledge base through the model, and the candidate knowledge text set at least comprises one candidate text; calculating the semantic similarity between the question text and each candidate text, sorting the question text and each candidate text, and determining a target knowledge text according to a sorting result; and generating a retrieval enhancement prompt text from the problem text and the target knowledge text, inputting the retrieval enhancement prompt text into the pre-training language model after fine tuning, and outputting a power grid intelligent scheduling decision scheme through the model. Therefore, the problems of model illusion, knowledge update lag, difficulty in tracing decision and the like in the intelligent dispatching of the power grid in the related technology are solved.