64 results about "Problem solution" patented technology

The invention discloses a path planning method and device for battery replacement, equipment and a storage medium. The method comprises the following steps: S1, establishing a model: defining variables; an objective function; constraint conditions; s2, selecting a solution algorithm: adopting an improved ant colony algorithm and combining with a local search strategy to improve the efficiency of problem solution; in the ant colony algorithm, an optimal charging station insertion heuristic mode is introduced, and the most suitable charging station insertion position is found for the path exceeding the maximum mileage of the vehicle or the unmanned aerial vehicle; and S3, sensitivity analysis: performing sensitivity analysis on main factors influencing path planning to optimize model parameters. According to the method, multiple factors of the electric vehicle and the unmanned aerial vehicle in the logistics distribution process, especially the influence of the battery replacement strategy, are comprehensively considered, more accurate and efficient path planning is realized, and by introducing the improved ant colony algorithm and the local search strategy, the problem solving efficiency is improved, and the calculation cost is reduced.

The invention relates to the technical field of artificial intelligence, discloses a customized question-answering system and method based on a large language model, and aims to solve the problems that an existing question-answering system is poor in accuracy and lacks permission adaptation ability. The question and answer platform is linked with a local large language model, an online large language model, a knowledge graph, a business knowledge base, an authority management module, a multi-modal data processing module and a feedback module; the enterprise communication tool receives the multi-modal question data sent by the user, and receives and displays a question and answer result; the multi-modal data processing module converts multi-modal problem data into corresponding text information, the authority management module obtains user authority information and adjusts access content and editing authority of a knowledge graph and a business knowledge base of a user, and the knowledge graph and the business knowledge base generate corresponding retrieval results. And the large language model generates a question-answer result according to the retrieval result. According to the method, the accuracy of professional knowledge questions and answers is improved, and permission adaptation is realized.

Example systems perform complex optimization tasks with improved efficiency via neural meta-optimization of experts. In particular, provided is a machine learning framework in which a meta-optimization neural network can learn to fuse a collection of experts to provide a predicted solution. Specifically, the meta-optimization neural network can learn to predict the output of a complex optimization process which optimizes over outputs from the collection of experts to produce an optimized output. In such fashion, the meta-optimization neural network can, after training, be used in place of the complex optimization process to produce a synthesized solution from the experts, leading to orders of magnitude faster and computationally more efficient prediction or problem solution.

This invention provides a method for constructing boundary conditions for a superhydrophobic cylindrical surface based on OpenFOAM, comprising the following steps: (1) reading the parameter setting file; (2) obtaining the position of the center of the cylindrical surface; (3) finding the position of the center of the first layer of grid near the cylindrical surface and its tangential velocity; (4) finding the position of the center of the second layer of grid near the cylindrical surface and its tangential velocity; (5) calculating the sum of the distances between the center of the cell and the center of the cylindrical surface; (6) calculating and updating the velocity of the cylindrical surface; (7) performing flow numerical simulation, repeating S2~S7 until the calculation is completed. This invention is based on OpenFOAM and has been further developed to construct a superhydrophobic surface boundary condition suitable for flow around a cylinder. This boundary condition supports parallel computation of the entire calculation process, improving computational efficiency and the scale of the problem solution.

The invention provides a system internal user satisfaction closed-loop management optimization method and device, and the method comprises the steps: constructing a plurality of role groups which are used for carrying out satisfaction process management, and at least comprise a first role group, a second role group and a third role group; an initial question list is obtained, and the initial question list comprises a plurality of reference questions; obtaining a screening result of the first role group for the plurality of reference questions based on a preset screening rule, and updating a question list ledger based on the screening result, the screening result including one or more target questions; obtaining a first verification result of the second role group for the target question; obtaining to-be-processed problems determined by the third role group based on the first verification result, and a problem solution corresponding to each to-be-processed problem; and updating the problem list ledger by the first role group based on the to-be-processed problem and the problem solution. Therefore, the user satisfaction cooperation management efficiency can be effectively improved.

The embodiment of the invention provides a code compilation optimization method and device based on algorithm representation, electronic equipment and a storage medium, and belongs to the technical field of code compilation testing. The method comprises the steps of obtaining an initial binary file and a problem optimization instance corresponding to a source code, screening and finely tuning candidate compilation optimization models based on a first reference problem solution, and reconstructing a second reference problem solution through a finely-tuned target compilation optimization model, and performing code compilation optimization on the initial binary file based on a target compilation optimization item determined by the target reconstruction solution. Wherein the target compilation optimization model is used for representing an intelligent algorithm for solving the optimization problem instance. According to the embodiment of the invention, the intelligent algorithm most related to the problem optimization instance can be determined by screening and fine tuning the candidate compilation optimization model, compilation testing does not need to be carried out on each different compilation optimization item combination through the intelligent algorithm, automation of code compilation optimization is realized, and the efficiency and accuracy of code compilation optimization are improved.

The invention relates to the technical field of biomolecule electrostatic characteristic prediction, and discloses a partial differential equation solving method based on a finite volume element method. According to the method, an unstructured grid matched with a biomolecular interface is constructed, a solution of a Poisson-Boltzmann equation (PBE) is separated into an analytical solution G, a linear interface problem solution psi and a nonlinear interface problem solution by adopting a decomposition technology, and a non-homogeneous flux condition at the interface is processed by utilizing a controlled volume decomposition technology; linear and nonlinear problems are solved through a finite volume element method, and final electrostatic potential distribution and solvation free energy are obtained through assembling. The method solves the problems of insufficient precision and low efficiency when a traditional numerical method is used for processing a complex interface non-homogeneous flux condition, has second-order L2 convergence and first-order H1 convergence, and can be efficiently applied to the biophysical research fields such as protein solvation free energy prediction and the like.

The invention discloses a large-scale disassembly line balance optimization system and method based on transfer learning. The system comprises a single-target optimization module used for correspondingly storing each single-target problem optimization solution to an independent knowledge base; the multi-objective optimization module is used for performing multi-objective problem optimization by using an evolutionary algorithm; the mapping relation building module is used for building an integer type mapping relation from each single-target problem solution set of the current generation to a multi-target problem solution set when transfer learning is triggered; and the transfer learning execution module is used for obtaining a transfer solution on the multi-target problem according to the multiple single-target problem optimization solutions in the independent knowledge base and the integer type mapping relation, and obtaining an initial population of next-generation multi-target problem optimization according to the transfer solution. Based on a transfer learning mechanism and an evolutionary algorithm, the problem of large-scale disassembly line balance optimization under the conditions of discrete decision space, high variable correlation and complex constraint is effectively solved, algorithm convergence is remarkably accelerated, and the solution set quality is improved.

The invention discloses a robust self-interference suppression beamforming method based on a multi-missile collaborative scene, which comprises the following steps of: considering a non-ideal condition, constructing a coupling channel model containing a circular symmetry Gaussian distribution error, and constructing an expression of power of a transmitting signal and a self-interference signal. Based on a self-interference signal power expression, an optimization problem for self-interference suppression transmitted beam forming with robust estimation errors is constructed; wherein the optimization target is set to maximize the transmitting beam gain; the set constraint condition is that it is ensured that the power of self-interference signals coupled to all receiving array elements in the receiving sub-arrays is smaller than a set upper limit threshold value; and transmitting link full-feed power upper limit constraint. According to an optimization problem, an original non-convex opportunity constraint problem is converted into a convex problem to be solved through an approximation method of positive semi-definite relaxation and a Bernshi inequality, so that a transmitted beam weight vector solution is obtained, the robust self-interference suppression capability under a non-ideal coupling channel is realized, and normal receiving of a desired signal is ensured.

The invention discloses a prompt optimization method and system for a large language model of an electric power system. The method comprises the following steps: acquiring data information of a target electric power system and data information of a corresponding large language model; constructing an initial prompt population of a fault diagnosis task of the target power system, and generating a diversified strategy in combination with domain problem description and a general thinking mode; performing mutation operation on the task prompt through a large language model to generate a variant adapted to a specific scene; screening to obtain a power grid problem solution by adopting a tournament selection mechanism; adjusting the strategy of the next round of evolution based on population KL divergence analysis; and prompt optimization of the large language model of the target power system is realized. According to the method, the prompt optimization of the large language model of the electric power system is realized, the reliability is higher, the accuracy is better, and the applicability of the scheme is better.

The invention provides an intelligent general drawing auxiliary layout method and system based on module calling and automatic verification, and is applied to the field of data processing application. According to the application, module calling and preprocessing are performed on basic data, a space module library G1 module is called in a one-key manner, data circulation from G1 to G3 is realized, and static spacing data, sunlight bar shadow graph data, a building number interval value, unit assembly basic data, a building-level house type index and a general graph-level business state index are generated based on a multi-city rule billboard; processing the static spacing data, the sunlight bar shadow graph data, the building number interval value, the unit assembly basic data, the building-level house type index and the general graph-level business state index to generate a compliance verification result; processing the compliance verification result to generate potential problem scheme information; and processing the potential problem scheme information based on the feature dimension to generate intelligent general graph auxiliary layout abnormal information.

The invention discloses a road network quality optimization method and device and electronic equipment. The method comprises the following steps: acquiring poor-quality data in a road grid network; processing the poor-quality data through a drive test agent according to a ReAct mechanism, and generating a problem solution corresponding to the poor-quality data; whether the problem solutions can meet preset requirements or not is judged, if the problem solutions cannot meet the preset requirements, defects existing in the reflection problem solutions are simulated, and according to the defects, the problem solutions corresponding to the poor-quality data are iteratively generated; if the maximum number of iterations is reached or the problem solution can meet a preset requirement, confirming the problem solution as a target solution; and optimizing the poor-quality data according to the target solution, thereby realizing road network quality optimization based on the road test agent ReAct mechanism. The method can improve the efficiency and accuracy of road network quality optimization.

Systems and methods for automatically identifying and resolving problem instances in data service workloads are disclosed. In some embodiments, a disclosed method includes: identifying a problem instance for a workload associated with a plurality of data service platforms; determining, using at least one machine learning model, a problem solution based on the problem instance and a catalog of problem solutions; executing the problem solution including operations across the plurality of data service platforms; and recovering the workload in accordance with a determination that the problem instance is resolved by the problem solution.

The application discloses a signal analysis method, system, device and medium based on quadratic constraint quadratic programming problem solution prediction, and belongs to the technical field of artificial intelligence. The method comprises the following steps: acquiring a target programming problem of a power transmission signal, wherein the target programming problem comprises a quadratic objective function and a quadratic constraint condition; encoding the quadratic objective function and the quadratic constraint condition to generate a target tripartite graph of the target programming problem; inputting the target tripartite graph into a message passing model; analyzing a plurality of nodes in the target tripartite graph and feature edges between the plurality of nodes by using the message passing model to obtain problem attributes of the target programming problem output by the message passing model, wherein the problem attributes comprise feasibility, an objective value and an optimal solution; and performing signal analysis on the power transmission signal based on the problem attributes. The method can process quadratic constraint quadratic programming problems in real time, and improves the analysis efficiency of the power transmission signal.

The invention discloses a dynamic examination system based on XR augmented reality and an implementation method, and relates to the field of XR technology and education examination fusion. Aiming at the problems of weak anti-cheating ability, insufficient foreign language scenario, limited occupational qualification examination practical operation evaluation and the like of a traditional examination, the system integrates intelligent anti-cheating, immersive scenario examination, multi-dimensional evaluation and AI digital human invigilation functions, including a complete version and a simplified version. The complete version system realizes full-process safety monitoring and scene assessment through an XR intelligent head-mounted display (supporting perspective / immersion dual-mode switching and integrating a multi-mode biological recognition module, a full-band detection module and the like), scene adaptive interaction equipment and an AI digital human invigilation engine; the simplified version is a low-cost transition scheme, a lightweight XR head-mounted display is adopted, synchronous display with a traditional computer host is supported, basic anti-cheating and scenarized functions are reserved, and the system is suitable for small and medium-sized examinations. According to the method, the examination safety and the evaluation accuracy can be remarkably improved, the deployment cost is reduced, the method is suitable for scenes such as large-scale selection examinations, foreign language evaluation and occupational qualification examinations, layered landing of the XR technology in the educational examination field is achieved, and examination evaluation is promoted to be transformed from'knowledge memory 'to'problem solution'.

The invention discloses a visual shared whiteboard system and method for solving a group collaboration mathematical problem, and belongs to the technical field of computer science and human-computer interaction crossing. The system comprises a multi-modal fusion input module used for converting input such as handwriting and voice into a structured mathematical object; the real-time semantic understanding and knowledge graph engine is used for constructing a collaborative cognitive model; the collaborative process management module based on the directed hypergraph is used for carrying out formalized modeling and navigation on a nonlinear problem solving process; the context-aware intelligent auxiliary module is used for providing verification, recommendation and guiding consensus achievement; and a multi-user cooperation engine ensures stable cooperation experience. According to the method, the problems of professional expression, real-time cooperation splitting, group thinking process management difficulty and the like are solved, and a unified, intelligent and efficient integrated cooperation environment is provided for group solving of complex mathematical problems.

According to the circulating mill disclosed by the invention, the internal circulating pipe interface is arranged in the area between the axial projection line of the impeller air inlet on the front cover or the rear cover and the axial projection line of the centrifugal fan inlet along the impeller, so that new problems brought by a grading problem solution constructed for solving the high pressure problem in the circulating mill in the background art are eliminated; and the pressure in the circulating mill is reduced, so that the rotating resistance of the impeller is reduced, and the energy consumption of the mill is reduced.

The invention discloses a distribution network planning problem automatic allocation solution measure algorithm library based on artificial intelligence, which comprises the steps of constructing a distribution network planning typical problem definition standard library model, constructing an artificial intelligence algorithm library, automatically analyzing distribution network planning typical problem solution measures, and automatically distributing the distribution network planning typical problem solution measures. The method comprises the following steps: automatically analyzing power distribution network planning typical problem solving measure process visualization, machine learning and deep learning analysis engine, intelligent fault problem positioning, artificial intelligence-based dynamic load problem prediction, and transformer area low voltage problem cause intelligent analysis. According to the distribution network planning problem automatic allocation solution measure algorithm library based on artificial intelligence, a unified problem definition standard library is established, the definition standard of the distribution network planning problem is standardized, and the early-stage planning analysis efficiency and accuracy of a power grid can be improved; and power grid planning and construction can be guaranteed, and disaster prevention and reduction power supply planning and construction can be promoted actively.

The application discloses a new energy automobile product whole life cycle problem management method based on a knowledge graph, which comprises the following steps: step one: inputting a problem, searching the problem in a historical problem database to determine whether the problem is a repeated problem; if yes, step seven is executed; if no, step two is executed; step two: classifying the problem based on professional knowledge and experience to determine the type and nature of the problem; step three: finding measures for solving the problem in the historical problem database and proposing a problem solution; step four: evaluating the feasibility and effectiveness of the proposed problem solution; if the evaluation is passed, step five is executed; if the evaluation is not passed, step three is executed; step five: practically verifying the problem solution; if the verification is passed, step six is executed; if the verification is not passed, step three is executed; step six: uploading problem data to a data center to update the historical problem database; and step seven: completing the problem solution.

The present invention discloses a method for automatic wiring and optimization of superconducting quantum chips, belonging to the field of automated design of superconducting quantum chips. In the modeling phase, the method adopts a "combined wiring template" model under a fine-grained grid. The combined wiring template is used to discretize the problem, avoiding the complex geometric operations in the arc wiring problem solution process and significantly reducing the algorithm's search space. In the legal solution search phase, a one-sided wiring algorithm is adopted. Based on the wiring result characteristics of the algorithm, the line sequence search problem is extended and a line sequence tree search framework is designed. On this basis, the blocking relationship between lines is explored and a series of search optimization strategies are designed. An exchange winding action is adopted to meet the special line sequence requirements of the read line. In the wiring optimization phase, an iterative optimization wiring scheme based on space constraints is adopted. Based on the legal solution, the overall wiring result is optimized at multiple levels of objectives to ensure that the wiring result meets the design requirements.

The present invention discloses a method, apparatus, terminal device, and storage medium for coordinated planning of power supplies and fault current limiters. The method solves the coordinated planning problem of power supplies and fault current limiters as a main problem to generate an initial planning solution set. A first sub-problem is then used to eliminate all infeasible solutions in the initial planning solution set to generate a first planning solution set. A second sub-problem and a third sub-problem are used to analyze the stability and cost of the first planning solution set to generate a second planning solution set. A fourth sub-problem is used to analyze the relaxation error of the second planning solution set to ultimately generate an optimal planning solution. Therefore, the present invention decomposes the coordinated planning problem of power supplies and fault current limiters into several problems for solution, and through cyclic iterative solutions, the problem solution set is continuously converged and gradually approaches the optimal solution, ultimately generating an optimal planning solution, effectively solving a key problem in the field of GEP.

The invention discloses a steelmaking-continuous casting production scheduling optimization method for a large-scale production environment, and relates to the technical field of steelmaking-continuous casting production scheduling optimization. According to the method, machine learning is embedded into the efficient proxy Laplace relaxation iterative algorithm to optimize steelmaking-continuous casting production scheduling, so that the scheduling problem solving difficulty can be effectively reduced, and the solving speed can be improved; and the method is particularly suitable for the flow characteristics of multi-procedure, multi-coupling, multi-constraint and intermixed intermittent and continuous operation modes in the large-scale steelmaking-continuous casting production process. In the process of searching the optimal Lagrangian multiplier, a pointer network is adopted to predict a sub-problem solution to replace a serious time-consuming process of solving the sub-problem solution by branch cutting, and under the design of a masking mechanism, prediction backup and the like of the pointer network, certain solving quality is ensured, the convergence speed is greatly improved, and the method is suitable for large-scale popularization and application. The response speed of scheduling compilation in the large-scale steelmaking-continuous casting production process can be effectively improved, and the production benefits of enterprises are improved.

The present invention provides a task adaptive generation method, system, storage medium and electronic device based on loop feedback. The method includes: Step S1: generating an artificial intelligence operation task based on a test instance list and artificial intelligence operation feedback; Step S2: processing the artificial intelligence operation task to obtain an artificial intelligence operation result; Step S3: returning the artificial intelligence operation result as new artificial intelligence operation feedback to Step S1; Step S4: iteratively and circularly executing Step S1 to Step S3. The present invention realizes automatic task generation, dynamically adjusts according to the artificial intelligence operation result, avoids mechanically listing single-type questions, effectively couples the generated task with the artificial intelligence operation model, and truly realizes the loop optimization of automatic task generation and problem solution.

Disclosed, according to one embodiment of the present disclosure, is a method, performed by a computing device, for generating feedback information for a problem solution. The method may comprise the steps of: obtaining model answer information items related to a problem; generating reference answer information items on the basis of the model answer information items by using an artificial intelligence model; obtaining user input information items related to a solution of the problem; and generating feedback information for any one of the user input information items by associating the user input information items with the reference answer information items.

An optimization device (10) comprises: a solution procurement unit for obtaining an original problem solution that satisfies a boundary condition of a combinatorial optimization problem containing a plurality of objective factors to be combined; a subproblem generation unit (12) for dividing the plurality of objective factors into a plurality of groups based on the original problem solution and for generating a subproblem set for each of the plurality of groups; a subproblem solution unit (13) for finding a solution for the subproblem generated by the subproblem generation unit; an inverse transformation unit (14) for generating a candidate solution for the original problem based on the solution of the subproblem obtained by the subproblem solution unit;and a solution update unit (15) for determining whether it is possible or not to update the original problem solution based on the result of a comparison between the candidate solution generated by the inverse transformation unit and the original problem solution obtained by the solution procurement unit.

The application discloses a kind of open-pit mine horizontal mining inner discharge pressure slope under the action of three-dimensional stability calculation method of side slope, comprising: S1, according to the form of the side slope of the mining area in the research area, weak layer of sliding body and potential sliding surface form, using three-dimensional numerical simulation technology, potential sliding surface spatial form equation is established;S2, based on spatial form equation, the side slope is divided into several i rows, j column micro column, and the stress analysis is carried out to each micro column, respectively calculate the anti-sliding force and the sliding force of each micro column in each region;S3, the force of each row micro column is superimposed along the main sliding line direction, and the total anti-sliding force and the total sliding force on the main sliding line are obtained;S4, three-dimensional slope stability problem is converted into two-dimensional problem solution, and the stability coefficient is calculated using unbalanced thrust method, and the application can provide important theoretical support and technical guidance for safe and efficient recovery of deep slope coal resources.

The invention discloses a new energy station frequency-voltage control parameter feasible region calculation method, and belongs to the technical field of new energy power systems. The invention discloses a new energy station frequency-voltage control parameter feasible region calculation method. The method comprises the following steps: constructing a new energy station model considering frequency-voltage combined control; a two-stage optimization model is constructed, the first stage is a main problem, and a feasible region of frequency voltage control parameters is maximized under constraint conditions; the second stage is a sub-problem, and the feasibility of the main problem solution is verified by using the solving result of the target function; and solving the two-stage optimization model by utilizing a column and constraint generation algorithm. According to the new energy field station frequency-voltage control parameter feasible region calculation method, through collaborative optimization of the main problem and the sub-problems, the feasible region of the control parameters is expanded as much as possible on the premise that the frequency and the voltage are not out of limit, and the flexibility and the robustness of the system are improved.

A processor according to the present invention receives submission input of problem solution data from one or more creators, extracts features of the submitted problem solution data, receives user input of a query pertaining to a problem or a desired solution, extracts features of the query, calculates a similarity between the features of the problem solution data that has been input through the submission and the features of the query, and outputs solution data as a proposal to the user in accordance with the similarity.

The application discloses a kind of reservoir group multi-objective scheduling cooperation search method and system, comprising the following steps: ① based on the basic information of reservoir establishes cascade reservoir multi-objective scheduling model;② constraint condition is added to model;③ construct a kind of reservoir group multi-objective scheduling cooperation search method and system solve reservoir optimal scheduling scheme, by using team communication strategy, internal competition strategy in the whole solution space is widely searched, simultaneously by self-learning strategy and self-adapting jump out local optimum strategy jump out local optimum, realize the dynamic balance of global exploration and local exploration.The application can effectively improve reservoir group scheduling calculation efficiency, quickly give reservoir group scheduling scheme set, with less calculation parameters, convergence speed is fast, global optimization ability is strong and not easy to fall into local optimum and the like advantage, while avoiding complex parameter adjustment process, programming is simple to realize, widely applicable scene, for complex reservoir group multi-objective engineering problem solution provides more effective technical method.

A method includes obtaining a sequence of instructions for generating a final result of a computation from a large language model by processing a user prompt requesting the computation. The method further includes converting the sequence of instructions to a sequence of mathematical expressions. The method further includes evaluating, by a numerical solver, the sequence of mathematical expressions to obtain a corresponding set of intermediate results. The method further includes evaluating the final result using the corresponding set of intermediate results, and presenting the final result.