66 results about "Simulated annealing" patented technology

This invention relates to the field of dynamic replanning technology for multi-UAVs in heavy-duty logistics, and particularly to a method for dynamic replanning of multi-UAVs for heavy-duty logistics. The method includes: accessing UAV information, cargo information, and initial map information; constructing an initial route and calculating its length after field checks, coordinate unification, and obstacle avoidance processing; generating a candidate route set; then sequentially performing distance, battery power, payload, and charging time constraints to obtain a static planning model; solving the model using a fusion of simulated annealing and ant colony optimization to obtain an initial path solution; updating the map information by real-time acquisition of unknown obstacle information using millimeter-wave radar; identifying the original path obscured by obstacles to generate an old solution; and finally, dynamically updating the old solution by performing path deletion, path addition, and objective function comparison based on operator weight probabilities to obtain a replanned path solution. This invention effectively shortens the maximum time of multi-UAV missions and significantly improves the robustness and adaptability of heavy-duty logistics transportation.

The application discloses a copper-clad aluminum busbar optimization method for reducing weight and conductive loss of a photovoltaic module, and relates to the technical field of photovoltaic busbar design, and comprises the following steps: according to electrical and geometric parameters of the photovoltaic module, a modified differential evolution algorithm is used to perform collaborative optimization on material size combination and structural configuration of the busbar. In the mutation operation, an adaptive mutation probability control of a simulated annealing strategy is introduced, and a dynamic crossover rate adjustment of a historical population entropy value is fused in the crossover operation. The aluminum core width, height and copper layer thickness of the top surface and the bottom surface are synchronously output in each iteration. Through calculation of unit length mass, direct current resistance and current carrying capacity, iterative optimization is performed under a current carrying safety margin, and joint optimization of weight and conductive loss is realized. The method improves global search and convergence precision of the algorithm, realizes collaborative matching of multiple parameters, reduces the weight of the busbar and reduces the conductive loss.

Disclosed are a cooperative positioning method and apparatus, a device, and a non-transitory computer-readable storage medium. The method may include: determining an initial positioning estimated value of each of a plurality of objects to be measured by a simulated annealing algorithm and a first preset positioning algorithm; screening at least two distance measurement values based on a preset error threshold to obtain a target distance measurement value, where the at least two distance measurement values are measurement values obtained by measuring a distance between each object to be measured and each of a plurality of target base stations for at least two times; and determining a position of each object to be measured according to a multi-target-source Taylor series algorithm, each target distance measurement value and each initial positioning estimated value.

This invention discloses a method for solving power system time-series optimization problems, comprising: constructing a dynamic mathematical model of the power system time-series problem and determining the objective function and constraints; generating an initial solution based on the dynamic mathematical model, performing pruning preprocessing on the initial solution using a fast pruning algorithm to select high-quality initial feasible solutions; generating neighborhood solutions based on the high-quality initial feasible solutions using a simulated annealing algorithm, determining whether to accept the neighborhood solutions according to the Metropolis criterion, and marking the completion of one iteration after the determination; performing pruning feedback and search direction optimization after each iteration until a preset iteration convergence condition is reached, and outputting the optimal solution for power system time-series optimization. This invention can effectively improve the efficiency, accuracy, and global optimality of solving power system time-series optimization problems, and is suitable for the complex requirements of high-voltage and high-efficiency power systems.

This invention discloses a collaborative optimization method for electromechanical control parameters of a dual-switched reluctance electric drive system, belonging to the field of electric drive system optimization technology. The method employs a "double-layer nested optimization" architecture: the inner layer targets motor torque / radial force fluctuation, losses, and efficiency, optimizing control parameters such as switching angle and phase current reference values ​​using the SA simulated annealing algorithm; the outer layer targets the total system mass, total losses, and efficiency under typical operating conditions (such as CLTC), optimizing motor structural parameters (stator outer diameter, air gap) and gear transmission parameters (transmission ratio, module) using the particle swarm optimization algorithm. During the optimization process, a finite element model is established using JMAG, a dynamic model is built using Simulink / Matlab, and Isight is used for automated iteration. A "constraint judgment-parameter adjustment" loop ensures that dynamic and strength requirements are met. This invention can improve system efficiency, reduce mass, and decrease torque fluctuations, making it suitable for scenarios such as new energy vehicles and wind power generation, and solving the problem of poor collaborative optimization in existing modular systems.

This invention relates to a method for generating frequency-agile radar signals, belonging to the field of radar frequency-hopping signal technology. The invention includes S1, quantizing an initial chaotic sequence into an integer chaotic sequence; and S2, determining the optimal control parameter u of the integer chaotic sequence using a simulated annealing algorithm. b S3, Generate the target chaotic sequence; S4, Construct the first frequency-agile radar sequence based on the target chaotic sequence; S5, Establish the data training set Ψ; S6, Train the CNN network model using the data training set Ψ, and use the CNN network to identify the given chaotic sequence and find the optimal threshold λ. k S6, perform binary quantization on the given chaotic sequence to determine the second frequency-agile radar sequence; S7, construct the target frequency-agile radar sequence. This invention utilizes two optimization methods—simulated annealing and convolutional neural networks—to enhance the randomness of the target frequency-agile radar sequence, enabling it to solve the problems of traditional radar systems, such as the ease of signal detection and interception, and susceptibility to interference.

The present application relates to the field of prefabricated component transportation scheduling of assembly type building, and particularly discloses a dynamic transportation scheduling optimization method for prefabricated components with interference of assembly type building, which designs an improved NSGA-II algorithm combining a simulated annealing mechanism and an adaptive strategy; for the multi-objective optimization problem of dynamic transportation scheduling of prefabricated components with interference, the present application combs three types of interference events, i.e., emergency orders, order modifications and vehicle transportation time changes, which occur frequently in the transportation process, and formulates dynamic rescheduling strategies for different disturbance types; in combination with a rolling horizon optimization method, the continuous dynamic scheduling problem is converted into a series of static sub-problems, and then static optimization schemes are adopted in each static process to realize dynamic optimization.

The application discloses a power communication network topology optimization method based on a complex network theory; the method firstly establishes a graph model of the power communication network, embeds power network tidal flow parameters and communication network service flow parameters in a weight matrix of the graph model, quantifies interlayer coupling degree according to node similarity, and constructs a coupling model of the network. Then, an elasticity evaluation index of the power communication network is proposed, a dynamic form of Kirchhoff coefficient is used to evaluate elasticity of the power communication network at different times, and development and evolution of the network in a cascading failure process is tracked. Finally, the elasticity evaluation index is used as a target function, a simulated annealing method is used to establish an optimization model, and optimal elasticity topology of the network is solved. The application is a network topology planning method, considers coupling characteristics of the power and communication networks, can adjust the topology relationship of the communication network, enhances structural strength of the power communication network, and improves resistance of the network in a failure.

The application is suitable for the technical field of safety monitoring, and provides a safety monitoring process line marking adaptive drawing method and system, including the following steps: obtaining historical monitoring data of a safety monitoring measuring point, drawing an original process line graph, performing image binarization processing thereon to generate an original binary graph; drawing a simplified line graph to generate a simplified line binary graph; obtaining the coordinates of the left and right endpoints of the process line in the simplified line binary graph; combining the endpoint, the time and measured value information of the marked point in the process line graph, and the coordinates of the endpoint in the simplified line binary graph to establish a linear mapping relationship from the simplified line graph to the original binary graph, and determine the initial center coordinates of the marking box; and iteratively optimizing the center coordinates of the marking box by using a simulated annealing algorithm. The application realizes full-process automation by automatically obtaining monitoring data, drawing a process line, positioning a marking point, and adaptively adjusting the position of a marking box by using an optimization algorithm.

This invention discloses a large-scale power grid simulation method, program product, and storage medium based on algebraic multigrid optimization. The method includes: parsing the netlist of a large-scale power grid to establish a power grid topology matrix; extracting global feature vectors based on the netlist and the power grid topology matrix; compressing the power grid topology matrix to obtain a compressed feature matrix; constructing and training a regression model, which is used to predict the solution time based on the compressed feature matrix, global feature vectors, and coarsening parameters; using the minimum output of the regression model as the objective function, and employing simulated annealing to find the optimal coarsening parameters; establishing a power grid simulation system Ax = b; and solving the power grid simulation system using the algebraic multigrid method with the optimal coarsening parameters to obtain the power grid unknown vectors, thus realizing large-scale power grid simulation. This invention improves solution efficiency and reduces memory consumption while ensuring accuracy.

A three-dimensional wire harness wiring method, system and medium relate to the field of wire harness layout. The method comprises: obtaining a three-dimensional space region to be wired, device coordinate information and device connection relationship; dividing the three-dimensional space region into multiple cross sections along a preset main wiring direction to obtain a cross section set, and determining a starting cross section of the cross section set; determining a plurality of wires passing through the starting cross section based on the device coordinate information and the device connection relationship to obtain a target wire set of the starting cross section; generating an initial channel group of the starting cross section by a first random algorithm based on the wire information of the target wire set; determining a target wiring solution of the starting cross section by a simulated annealing algorithm based on the initial channel group; determining a target wiring solution of a target cross section in sequence according to the preset main wiring direction based on the target wiring solution of the starting cross section; and determining a wire harness wiring result of the three-dimensional space region based on the target wiring solution corresponding to each cross section. The application can improve the accuracy of three-dimensional wire harness wiring.

This application provides a method, system, and medium for load dispatching that considers both proactive peak shaving and demand response complementarity. The method includes the following specific steps: S1: Analyzing the peak shaving compensation and allocation methods of various generating units at the power generation level, considering the proactive constraints of peak shaving for various units, and establishing a model to incentivize various units to participate in peak shaving through peak shaving revenue; S2: Adopting price-based demand response on the load side to establish a model that guides users to actively participate in load adjustment; S3: Then, using the minimization of system operating costs and the minimization of wind and solar curtailment as optimization objectives, constructing a day-ahead optimal dispatching model for the new energy system that considers the proactive peak shaving of thermal power and demand response on the load side using the simulated annealing-particle swarm optimization algorithm; S4: Finally, conducting multi-scenario analysis using the improved IEEE 30-bus system as an example and verifying its feasibility. This application effectively promotes the consumption of renewable energy, improves the overall peak shaving efficiency of the system, and provides an effective method for coordinated dispatching decisions of multi-energy systems.

This invention discloses a method and system for coordinated operation scheduling of aircraft and vehicles at airport surfaces. The method includes: collecting multi-source airport operation and support resource data to construct an input data set for coordinated operation of aircraft and vehicles; constructing a parking stand allocation model based on coordinated scheduling, comprehensively considering flight schedules, parking stand resources, and support service constraints; constructing initial and secondary vehicle scheduling models and designing dynamic adjustment strategies; using the NSGA-II algorithm with fusion local search to solve the parking stand allocation and initial vehicle scheduling problems, and using a large neighborhood search algorithm combined with simulated annealing to solve the secondary vehicle scheduling problem. This invention overcomes the limitations of traditional single optimization models, solves the problems of low resource utilization and conflicts caused by independent scheduling of aircraft and ground vehicles, and fills the gap in airport surface coordinated operation scheduling technology.

The application provides a kind of unmanned aerial vehicle cluster path planning method for forest fire edge, first obtain the quasi-forest fire edge graph after edge expansion, and calculate to obtain scanning range convex polygon, the distance of discrete point in fire area to each side of scanning range convex polygon is solved, the shortest distance is regarded as the importance index of the discrete point, and according to the index, draw the equal importance line graph, and the different regions in the graph are weighted, the spacing of adjacent path of unmanned aerial vehicle scanning in the region is determined according to the weight of region, to improve the lateral overlap rate of edge region unmanned aerial vehicle scanning, so as to improve the aerial image precision of unmanned aerial vehicle;Then construct multi-unmanned aerial vehicle scanning range distribution function and unmanned aerial vehicle three-dimensional path cost function, the optimal position of range segmentation ray and the best three-dimensional path planning are solved by using particle swarm optimization algorithm and genetic simulated annealing algorithm.The application is reliable and practical, and has good adaptability for unmanned aerial vehicle cluster path planning in forest fire scene.

The invention discloses a ship plane segment workshop rescheduling method, which comprises the following steps of: establishing a scheduling model oriented to a ship plane segment workshop, adding processing time uncertainty into the scheduling model, establishing a constraint relation and constructing a target function; after the scheduling model is constructed, scheduling optimization is carried out by adopting an improved iterative greedy algorithm; constructing an algorithm dynamic destruction and reconstruction stage; developing a solution after the destruction reconstruction stage by adopting neighborhood search, and judging acceptance of the current solution by adopting a simulated annealing criterion; a rescheduling strategy is made according to two disturbance events of machine faults and workpiece insertion in the machining process, and an optimal scheme is solved. The method has the beneficial effects that a mathematical model is constructed by taking minimization of maximum fuzzy maximum completion time and start time deviation as an optimization target based on a processing task, and a rescheduling strategy is formulated for two disturbance events of machine fault and workpiece insertion to obtain an optimal segmented distribution and processing sequence; and the efficiency of a ship plane section processing workshop can be improved.

The application discloses a basic agent model and a ship lightweight optimization design method of variable-thickness steel plates, and belongs to the technical field of ship structure optimization related to finite element numerical simulation. The application solves the problem that the traditional ship variable-thickness structure optimization method in the prior art is difficult to obtain an optimal ship variable-thickness structure due to low precision and efficiency; the application establishes a ship longitudinal stiffened plate finite element model based on the geometric configuration of the ship longitudinal stiffened plate; defines core design variables of the ship longitudinal stiffened plate finite element model, sets constraint conditions, and constructs an objective function; adopts a Latin hypercube sampling method to perform test design, integrates output response values, and forms a DOE sample database; adopts a Kriging model to establish an agent model in combination with sample point correlation; and adopts a simulated annealing algorithm to output optimal design variable values. The application effectively improves the ship lightweight optimization efficiency and precision, and can be applied to the lightweight design of variable-thickness steel plate ships.

The application discloses a millimeter wave movable array beam training method based on quantum correlation simulated annealing, and relates to the technical field of wireless communication.The application proposes a quantum correlation simulated annealing (QCSA) algorithm aiming at the high-dimensional, non-convex and strongly coupled beam-array position joint optimization problem caused by the movable array, and adopts an alternating optimization framework to decompose the joint optimization problem into iterative solving of the transmitting and receiving subspaces; in each subspace optimization, the physical correlation between parameters is learned through Gaussian sampling based on an adaptive covariance matrix, the global search capability is enhanced by using an acceptance criterion containing a thermodynamic term and a quantum tunneling term to escape from a local optimum, and a periodic oscillation thermal scheduling strategy is adopted to dynamically balance exploration and utilization, so that the application has the characteristics of low overhead, fast convergence and high robustness, and is suitable for 6G millimeter wave and terahertz movable array MIMO systems.

This invention relates to the field of building structure optimization design technology, and discloses a method for energy-saving optimization design of prefabricated tower buildings. The method establishes a discrete feature database containing component cross-sections and semi-rigid node parameters; performs topology reduction analysis, eliminating redundant elements based on sensitivity coefficients and verifying connectivity to generate a skeleton model; performs stiffness and internal force co-calculation, constructing a semi-rigid element stiffness matrix using modified shape function coefficients, and bi-directionally matching component cross-sections and node stiffness according to the dominant internal force mode of the components; calculates the structural assembly entropy, constructs an objective function containing the total structural mass and assembly entropy, and uses simulated annealing algorithm for iterative optimization; finally, based on the optimization results, it outputs a bill of materials and a three-dimensional building information model containing detailed node construction parameters. This invention achieves simultaneous optimization of structural lightweighting and component standardization through the coordinated adjustment of node stiffness and component cross-sections and assembly entropy constraints.

The application discloses a machine learning-based terahertz graphene adjustable super surface design method, which comprises the following steps: setting a first target matrix and a second target matrix for phase optimization according to target intensity and position of a far-field diffraction beam; constructing a phase optimization model based on the combination of simulated annealing and Fourier transform, using the first target matrix to obtain optimal phase distribution of the super surface through iterative optimization; constructing an amplitude-phase joint optimization model based on particle swarm optimization, using the second target matrix to jointly optimize the amplitude and phase of the super surface, obtaining a corrected disturbance phase distribution and a quantized amplitude distribution, and realizing dynamic switching of the number of far-field beams; the machine learning algorithm is used as the basis, the optimization model has universality, and the graphene super surface unit has a relatively deep modulation depth, so that the number of far-field diffraction beams can be arbitrarily changed and switched.

This invention provides an RBAC+ABAC-supported access control method for AI knowledge bases, belonging to the field of AI knowledge base technology. This invention employs a gradient boosting decision tree and a Bloom filter to construct a simplified decision model. An optimization algorithm based on thermodynamic entropy finds the policy configuration with the minimum entropy value through simulated annealing, eliminating rule conflicts and simplifying the logical structure. During vector retrieval, the permission encoding vector and semantic vector are concatenated to form a joint vector to construct a permission-aware index. During answer generation, a permission context fingerprint is attached, and secondary propagation of permissions is verified through a permission re-verification gateway. Operation logs are recorded using a hash chain structure to ensure the immutability of audit traceability. This invention solves the technical problem that AI knowledge bases cannot simultaneously guarantee the efficiency of permission decisions and the maintainability of policy rules when performing fine-grained access control.

The application relates to a steel hot rolling process task allocation method based on an Ising model. The method is realized through the following steps: firstly, setting a hot rolling scheduling problem parameter, establishing a multi-traveling salesman problem model of the problem and further converting the model into a conventional traveling salesman problem model; secondly, combining the Ising model to transform the original steel hot rolling scheduling problem model, converting the problem into a form capable of being solved by using the Ising model; then, based on the transformed Ising model, an Ising machine based on a Hamilton Monte Carlo sampling simulated annealing algorithm is used for solving; finally, the solving result is converted into an understandable hot rolling scheduling scheme. Compared with the prior art, the application introduces a novel simulated annealing algorithm based on a Hamilton Monte Carlo sampling, which is used for solving a large-scale scheduling problem. The algorithm can improve the search solving efficiency, and enhance the accuracy and applicability of multi-task allocation planning. Therefore, the application has important practical engineering application value.

The application discloses a kind of three-dimensional pipeline design drawing generation systems based on MBD size marking, it is related to engineering graphics automation field;The system includes: MBD semantic analysis module is used to extract the size, tolerance and technical requirements in three-dimensional model and establishes topological correlation;View projection planning module, the main extension direction of pipeline is calculated using principal component analysis, and the projection plane is rotated to minimize the overlap rate;Intelligent layout optimization module, construct the cost function including repulsion and compact weight, and use simulated annealing algorithm to iteratively optimize the marking position to eliminate occlusion;Drawing rendering module, output the engineering drawing and interactive SVG file in line with national standard.In addition, the system also has version change automatic cloud line marking and local magnified drawing automatic generation function.The application effectively solves the problems of information loss, layout confusion and change tracking difficulty in the process of three-dimensional to two-dimensional, and realizes the automated production of high-quality pipeline engineering drawing.

The application discloses a kind of directional reflection metasurface reverse design method and system, the method includes: generating directional reflection metasurface containing metal patch, and randomly generating the geometric parameter combination of directional reflection metasurface, calculate its reflection phase in working frequency band, construct the dataset of "geometric parameter-reflection phase";Attention-CNN-KAN hybrid prediction model is constructed and trained;Based on generalized Snell law, the trained Attention-CNN-KAN hybrid prediction model is used as forward agent, combined with simulated annealing algorithm, reverse search is carried out, and the optimal geometric parameter of each unit is output;According to the optimal geometric parameter of each unit, the arrangement mode of "grouping repetition" is used to construct metasurface array.The application builds Attention-CNN-KAN hybrid prediction model, so that the phase prediction determination coefficient of the model in 2-18 GHz wide frequency band is significantly improved, so as to improve the phase jump point prediction accuracy.

The application discloses an eVTOL landing site location method, comprising the following steps: determining an initial candidate landing site set based on a three-dimensional city model constructed according to city geographic space data combined with a GIS platform; establishing a mixed integer programming model with the maximum coverage area, the minimum flight energy consumption and the minimum flight time as the target; using a simulated annealing algorithm to perform iterative search based on the initial candidate landing site set to generate an initial layout scheme meeting preset conditions as an initial solution; using an exact solver to take the initial solution as a search starting point to perform accurate optimization on the mixed integer programming model and output an optimal eVTOL landing site layout. The application comprehensively considers the multi-objective trade-off between the complex three-dimensional space constraints of the city and the operation of the eVTOL, can plan a landing site layout scheme that is safe, efficient and optimal in service coverage, and can effectively improve the operation efficiency of the urban air transportation system.

This invention discloses a patrol path decision-making method for unmanned systems in adversarial environments, belonging to the field of autonomous unmanned systems and intelligent decision-making technology. The method includes: acquiring an undirected patrol topology graph of the physical environment to be patrolled; calculating the steady-state distribution of the target based on the value parameters, attack time parameters, and degree of each node; and defining a patrol strategy unpredictability index weighted by intra-strategy entropy and inter-strategy entropy. PSUI To address the uncertainty of strategies in terms of microscopic randomness and macroscopic diversity, a simulated annealing dual-entropy balance optimization algorithm is employed to maximize... PSUI To achieve the goal, a set of state transition matrix strategies is generated under the constraints of topological adjacency, row normalization, and target steady-state distribution. The unmanned system is then controlled to perform spatiotemporally decoupled patrols through random matrix switching and probabilistic transitions within the matrix. This invention unifies patrol strategy evaluation and optimization, significantly improves the unpredictability of patrol paths, and enhances the protection capabilities for critical infrastructure.

The present application belongs to the technical field of surface wave dispersion inversion, and particularly provides a multi-mode high-precision surface wave dispersion inversion method based on shallow layer optimization, and the specific steps comprise: step one, establishing a geophysical model; a geophysical model containing three layers of medium is established; step two, forward calculation; an improved global matrix method is used to solve Rayleigh wave dispersion equation; step three, adaptive phase velocity search; according to frequency V, the search range is dynamically adjusted to V min ~ V max : step four, constructing a shallow layer optimization objective function; step five, simulated annealing global optimization. The present application can significantly improve the accuracy of shallow layer parameters, reduce the first layer thickness error from 5-8% to 1-2%, and reduce the first layer velocity error from 6-10% to 1-3%; the calculation efficiency is greatly improved, the numerical stability is enhanced, the multi-mode data is fully utilized, and the result is complete and clear.