44 results about "Shortest path search" patented technology

The invention discloses an automatic planning method and system for a curved surface path of a grinding robot, and the method comprises the following steps: S1, constructing a to-be-machined three-dimensional curved surface model and a triangular mesh model, and relates to the technical field of automatic control of robots for surface machining in the manufacturing industry. According to the method, a complex three-dimensional surface coverage path planning problem of a workpiece is converted into two low-complexity sub-problems of key point sampling of a two-dimensional path planning domain and three-dimensional shortest path searching on a triangular mesh model, a small number of sampling points are sampled only on the two-dimensional path planning domain, and the sampling process depends on a spatial index framework; according to the method, global traversal of disordered point clouds is avoided, three-dimensional coordinates are positioned through nearest neighbor search of a KD tree algorithm, adjacent three-dimensional ordered key points are sequentially connected through a graph search algorithm, and a continuous machining path is formed, so that the operand is greatly reduced, real-time response of path planning is facilitated, and the problems that traditional online planning is long in time consumption and difficult in real-time response are solved.

The invention discloses a translation memory bank retrieval and matching method based on semantic similarity, which relates to the technical field of computer-aided translation, and comprises the following steps: generating an internal edge and a cross-graph edge, calculating a one-time jump success probability, calculating edge and cross-graph edge cost based on cleanliness, correcting by using the one-time jump success probability to obtain an edge weight; generating a weighted graph, constructing an initial priority queue, searching by using a shortest path to obtain a distance matrix, calculating density based on a fuzzy similarity matrix, screening the density to obtain a genealogy center, calculating proximity, and generating candidate translations in combination with the distance matrix; static and dynamic fragment sets are constructed through a dependency syntax and BERT-NER, semantic matching precision and noise robustness are improved, a weighted graph is constructed in combination with cleanliness and transfer factors, shortest path matching is carried out, and the retrieval recall rate and quality of technical translation are improved.

The invention provides a path planning method, device and equipment and a readable storage medium, and the method is applied to a mobile device, and comprises the steps: obtaining a target map, dividing the target map into a plurality of sub-regions, and enabling the plurality of sub-regions to comprise a starting point region and an ending point region; determining an access point in the starting point area, and determining an outgoing point in the ending point area; a hybrid obstacle avoidance algorithm is utilized to determine an access path between the starting point and the access point and determine an outgoing path between the outgoing point and the terminal point, and the hybrid obstacle avoidance algorithm is a path planning algorithm combining a heuristic search algorithm and vehicle dynamics constraints; determining a main road path between the access point and the outgoing point by using a shortest path search algorithm; and determining a target path of the movable device based on the access path, the main road path and the access-out path. The driving requirements of the movable device can be met while the driving path is optimized.

The invention discloses a collaborative operation optimization method for a bus and subway integrated network. The method comprises the following steps: S1, carrying out collection and standardization processing on topological structure data, train operation timetable data and passenger travel demand data; s2, completing the construction of a multi-layer coupling space-time network; s3, K short path searching is executed, and a passenger reachable path set is generated; s4, carrying out reachability verification on the passenger path selection set under a train operation rule; s5, a scheduling scheme is formed based on the distribution probability output by the Logit model; and S6, inputting the time sequence operation data into the improved Mamba network, performing constraint check and correction on the line departure logarithm and the departure moment of the first station, and forming an evaluation index for optimizing the objective function. According to the method, collaborative optimization of the train operation time sequence and the passenger travel demand under the bus and subway integrated line network is achieved, and the method is suitable for intelligent scheduling and dynamic passenger flow regulation and control scenes of a large-scale urban rail transit system.

The application discloses a kind of polishing robot curved surface path automatic planning method and system, comprising the following steps: S1, the three-dimensional curved surface model and triangular mesh model of to be processed are constructed, involve the robot automatic control technical field of manufacturing industry surface processing, the three-dimensional surface covering path planning problem of complex workpiece is converted into two-dimensional path planning domain key point sampling and three-dimensional shortest path search two low-complexity sub-problems in the present application, only a small amount of sampling point is sampled on two-dimensional path planning domain, sampling process relies on spatial index framework, avoid global traversal of unordered point cloud, the nearest neighbor search positioning three-dimensional coordinates using KD tree algorithm, adjacent three-dimensional ordered key points are sequentially connected by graph search algorithm, form continuous processing path, to greatly reduce the amount of calculation, it is favorable for the real-time response of path planning, alleviate the problem that traditional online planning is time-consuming and difficult to respond in real time.

The invention discloses an automatic control method, system and equipment based on industrial big data analysis, and relates to the technical field of industrial big data analysis. The automatic control method based on industrial big data analysis comprises the steps of receiving order data in real time, and generating first data corresponding to a target product based on the order data; executing shortest path search in a preset process database based on the first data; collecting multi-dimensional historical data, and inputting the multi-dimensional historical data into the trained time sequence prediction model to obtain a load prediction value of each station in a future time period; performing rolling scheduling on the process chain by adopting a reinforcement learning algorithm to generate a work order sequence with a timestamp; and issuing the work order sequence with the timestamp to an edge controller, and carrying out adaptive adjustment on field equipment. According to the technical scheme, automatic control and self-adaptive scheduling based on industrial big data can be realized in a multi-variety and small-batch mixed flow production scene, and the production flexibility and the resource utilization rate are improved.

The invention discloses a shortest path searching method and a social network relation analysis method, and belongs to the technical field of network information, the social network relation analysis method comprises the steps that a knowledge graph of a social network is constructed, vertexes in the knowledge graph comprise users or entities, and edges in the knowledge graph represent the interaction relation between the vertexes; calculating a shortest path from the source point to the target point based on a shortest path searching method; wherein the source point and the target point belong to a vertex set of the knowledge graph; and obtaining a relation analysis result of the source point and the target point according to the interaction relation on the shortest path from the source point to the target point. According to the method, large-scale social network graph data with a complex structure can be efficiently and stably processed.

The application discloses a kind of grain map neural network's weld ultrasonic beam path correction method, it is related to the field of welding structure nondestructive testing, by obtaining the EBSD data of weld area, extract grain orientation, grain boundary type and spatial distribution characteristics, construct grain map structure, and calculate initial propagation time weight based on anisotropic sound velocity model;Using graph neural network to learn end to end for grain node and grain boundary edge features, output corrected edge propagation time weight;The time of flight from element to imaging pixel is obtained by shortest path search, and the time of flight predicted by neural network surrogate model is fused and corrected;Finally, the corrected time of flight is used to perform full focus imaging, and the weld defect image after optimizing the beam path is obtained.The method combines material microstructure characteristics and machine learning model, solves the problem that the beam path description is not fine enough in existing weld ultrasonic testing, significantly improves the accuracy and reliability of defect detection.

The invention discloses an intelligent process generation method and device based on knowledge graph embedding similarity matching, and belongs to the technical field of intelligent manufacturing process planning, and the method comprises the steps: constructing an assembly process knowledge graph; an assembly process sub-graph is extracted with the process as the center and serialized; the method comprises the following steps of: obtaining node-level embedding through a twin Transform encoder with shared parameters; obtaining graph-level embedding through batch embedding splicing and a pooling layer; performing bilinear interaction on an assembly subject, a relationship and an object by using an assembly element interaction neural tensor network, and extracting deep semantic features; outputting a similarity score of the two sub-graphs; retrieving the most similar process node based on the score; and executing shortest path search on the directed acyclic graph to complement missing nodes, and generating a target assembly process path. According to the method, rapid matching and automatic generation of different and semantically similar processes are realized, and the process reuse rate and the generation efficiency in a multi-variety, small-batch and rapid iterative manufacturing environment are remarkably improved.

A method and device for interpreting a graph neural network based on FPGA acceleration propose to use FPGA hardware to accelerate interpretation process of the graph neural network oriented to node classification in parallel, and improve node traversal and shortest path search of BFS, thereby optimizing requirements of algorithm calculation and storage, and accelerating generation of interpretation results. During calculating HN values, the present disclosure optimizes multiplication operation using the matrix characteristics, transforms the dense matrix multiplication into sparse-dense matrix multiplication, and optimizes the resource occupation using multi-PE parallel processing, greatly improving performance of graph neural network interpretation acceleration. Moreover, an overall architecture based on FIFO storage calculation task distribution is designed to reduce calculation difference between nodes, solving the difficulty of high time complexity of the graph neural network interpretation method based on node classification in actual data applications and improving the time efficiency of interpretation.

The application discloses a land surveying method and device based on multi-source data fusion, and relates to the technical field of surveying, which comprises the following steps: collecting three-dimensional geodetic coordinate data and three-dimensional space point cloud data, obtaining starting three-dimensional coordinate and ending three-dimensional coordinate of surveying, constructing a triangulated irregular network (TIN) terrain model and a shortest path search model on the ground, searching for a starting node and a target node in a weighted undirected graph, calculating the shortest path on the ground and the ground distance, rendering the TIN terrain model to draw the shortest path on the ground, and setting through points and forbidden areas to update the shortest path on the ground and the ground distance. The application breaks through the dependence of traditional land surveying on the line-of-sight condition by fusing multi-source data and constructing continuous digital terrain, intelligently calculates and visualizes the shortest path on the ground, avoids the error accumulation of manual segmented operation, provides interactive path replanning capability, and significantly improves the accuracy, efficiency and scientific nature of planning and decision-making of ground surveying under complex terrain.

The application relates to a ground object fused surface vector path planning method suitable for special vehicles, which comprises the following steps: reading and fusing a ground object classification layer according to the driving capability of a user-selected special vehicle; loading a layer fused vector file; obtaining a user-specified starting point A and ending point B; traversing each vector block in the fused vector; finding a vector block containing both A and B and gridizing the vector block; constructing a dijkstra dictionary for the grid points; finding the nearest starting and ending points in the vector block; and performing single-source dijkstra shortest path searching between the starting and ending points. The ground object fused surface vector path planning method suitable for special vehicles can intelligently adapt to the specific requirements of different vehicles, so that precise and efficient path planning can be realized in a complex ground object environment.

The application discloses a shortest path divide-and-conquer search method based on a condensation level, improves the operation efficiency of an algorithm by introducing network layering, limiting a search level, divide-and-conquer search and the like, wherein the network layering is adopted to divide network nodes according to a condensation level clustering method, a plurality of level subgraphs are obtained, and the complexity of the search is reduced; the search range is limited within a certain level by limiting the search level, and invalid calculation in the search process is avoided; meanwhile, in order to further improve the search efficiency, the divide-and-conquer search is adopted to divide the whole search process into a plurality of subtasks and perform simultaneously, and the whole search method can accurately and efficiently perform the shortest path search in an edge computing network.

This invention discloses a collaborative operation optimization method for an integrated bus and metro network, comprising the following steps: S1, collecting and standardizing topology data, train timetable data, and passenger travel demand data; S2, constructing a multi-layer coupled spatiotemporal network; S3, performing K-shortest path search to generate a set of passenger reachable paths; S4, verifying the reachability of the passenger path selection set under train operation rules; S5, constructing a scheduling scheme based on the allocation probabilities output by the Logit model; S6, inputting the time-series operation data into an improved Mamba network to constrain and correct the number of train departure pairs and the first station departure time, forming an evaluation index for the optimization objective function. This invention achieves collaborative optimization of train operation sequence and passenger travel demand in an integrated bus and metro network, and is applicable to intelligent scheduling and dynamic passenger flow control scenarios in large-scale urban rail transit systems.

The invention provides a multi-robot path searching method for an optical communication scene, and belongs to the field of robot path planning, and the method comprises the steps: obtaining an optical communication scene road network containing optical communication sites and non-optical communication sites, and obtaining a simplified road network and road network nodes through the fusion of the non-optical communication sites; on the basis of neglecting conflicts among robot paths, forming an initial path scheme through a shortest path search algorithm, judging whether space-time conflicts exist or not, generating corresponding space-time constraints according to a space-time conflict judgment result, and recalculating to form a new path scheme through the shortest path search algorithm with the space-time constraints; and repeatedly executing the shortest path search algorithm with the space-time constraint until an optimal path scheme is obtained. The problems that in the prior art, due to the fact that continuous real-time wireless communication is relied on, effective conflict detection and avoidance cannot be carried out in an optical communication discontinuous communication scene, the robot collision risk is high, and the planning efficiency is low are solved.

This invention discloses a method for obtaining K shortest paths in a city that considers real-time traffic conditions, comprising: 1. Constructing a city road network based on traffic information at the initial time; 2. Defining and initializing parameters; 3. Searching for the k-th shortest path from the starting intersection node to the ending intersection node at the current time; 4. Searching for the (k+1)-th shortest path from the starting intersection node to the ending intersection node at the current time; 5. Obtaining the K shortest paths from the starting intersection node to the ending intersection node at the next time after updating traffic conditions, based on real-time traffic conditions. This invention can obtain K optimal travel paths that better reflect actual traffic conditions while improving computational efficiency, thereby ensuring the stable and efficient operation of social traffic.

The application discloses a multi-path video real-time splicing processing method based on an embedded platform and particularly relates to the technical field of image processing, which comprises the following steps: obtaining multiple images with consistent time stamps through hardware frame synchronization, calculating the light flow module length of the overlapping area after pre-alignment through cylindrical projection to generate a binary mask, establishing a control grid in the overlapping area to perform sparse disparity estimation and correction to obtain a sparse disparity map, up-sampling the disparity map to a dense disparity map, constructing a composite energy map containing a spatial color gradient cost and a time penalty cost, modulating the spatial cost by using the binary mask and smoothing the time penalty map, obtaining a dynamic avoidance seam through shortest path search, and forming an adaptive feathering band with the seam as the center. The application effectively eliminates static disparity ghosting and motion object half-cut artifacts under limited computing resources and realizes high-quality real-time panoramic splicing.

The application discloses a routing method, medium, equipment and product of a low-orbit satellite constellation, relates to the technical field of satellite routing, and comprises the following steps: according to a quality of service parameter, performing snapshot freezing on a current network topology to construct a static topology graph structure; constructing a basic quality of service parameter cost function for each link; performing an offline ant colony optimization algorithm to globally evaluate a satellite topology library constructed in advance, constructing a heuristic function according to a link basic quality of service parameter cost; initializing a pheromone value for each link, and updating the pheromone in an iteration process according to the heuristic function; adjusting the cost function based on the pheromone; taking the cost of the discounted pheromone as the final link weight of the satellite network, constructing a weighted graph structure, and adopting a shortest path search algorithm to calculate a routing path between a source node and a target node, so that an optimal routing path is obtained. The application solves the problems of high-speed time-varying satellite link state adaptability and poor quality of service.

The application discloses a kind of vehicle operating mode transfer planning methods for fuel consumption optimization, comprising: step 1: according to vehicle relevant test operating mode acquisition driving data;Step 2: each variable in the historical data obtained is filtered as different dimensions and is clustered into partitions;Step 3: according to the information extraction of each zone divided by cluster, the relationship and transfer cost of each zone are obtained from continuous operating mode data;Step 4: according to the relationship between each zone, the operating mode transfer directed graph is constructed, and all the minimum cost transfer paths between different initial and final regions are obtained;Step 5: according to the current operating mode and target operating mode information, the region selected by each operating mode in the path is selected as the same as the minimum cost path in step 4 as the optimal transfer path;The operating mode information in the historical data is divided into regions, then each region is regarded as a vertex in the directed graph, the transfer cost between regions is regarded as the distance between each vertex, and the vehicle operating mode transfer path planning is changed into the shortest path search of directed graph.

The invention relates to an edge device LLM deployment system and method based on memory filling and game optimization, and the system comprises a network state synchronization module, a distributed model deployment module and a model reasoning module. Through dynamic model deployment, cold-start-free model loading and self-adaptive adjustment are realized, and reasoning scheduling is optimized through a layer-device execution graph and shortest path search.

Disclosed are embodiments of shortest path search in an obstacle environment. Provided is a shortest path search method including: creating an epsilon graph; and determining k closest points from a query point on the basis of the graph, wherein the creating of the graph includes: creating a node group of nodes on the basis of a point group of arrival points; creating an edge group of edges on the basis of the created nodes; setting, on the basis of an obstacle group of at least one obstacle, whether each of the nodes is a valid node or a non-valid node; setting, on the basis of the obstacle group, whether each of the edges is a valid or non-valid edge; and including, for each of the arrival points, a particular arrival point on an anchor list of a valid node closest from the particular arrival point among the valid nodes.

The invention discloses a concealed pipe drainage design method and system for saline-alkali soil. The method comprises the following steps: firstly, acquiring a farmland or saline-alkali soil surface image, processing the image by adopting a machine vision technology, and automatically generating a mask pattern of a water accumulation area; then, according to the area of a mask connected domain, the number of drainage points is calculated in a self-adaptive mode, and drainage point coordinates are extracted through a clustering algorithm; a cost field is constructed in combination with a mask graph, an eight-neighborhood weighted grid graph is established, and a direction penalty function and an acute angle suppression rule are introduced in shortest path search, so that the generated drainage path is smoother, has no sawteeth and meets the construction requirements of concealed conduits. Automatic grouping is achieved through the shortest path distance between terminal points, and a multi-concealed-pipe layout scheme with the minimum total cost is obtained in combination with automatic selection of exit points and multi-threshold global search. According to the invention, full-process automation from image recognition to drainage path generation can be realized, and the intelligent level of saline-alkali soil treatment and farmland drainage design is improved.

The present application relates to the field of rail transit, and specifically provides a regional multi-mode rail transit network passenger flow distribution prediction method, medium and computer device, wherein the regional multi-mode rail transit network passenger flow distribution prediction method comprises the following steps: improving the K-shortest path search algorithm according to the hierarchical characteristics of the pre-constructed regional multi-mode rail transit network; constructing a set of feasible paths between any OD based on the pre-generated passenger flow OD matrix of the "region + urban area" and the improved K-shortest path search algorithm; and integrating the set of feasible paths between any OD into a travel path probability selection model to realize the passenger flow distribution of the regional multi-mode rail transit network. Through such a structure, more scientific integrated analysis of the passenger flow demand of the regional rail transit network can be provided, so as to meet the diversified travel demands of passengers in different regions, with different functions and different speeds.

The application discloses a full-loop signal retrieval method based on SDD and SCD models, and the method comprises the following steps: firstly, the physical path of an incoming signal full loop is acquired through the shortest path search method by analyzing the SDD model; then, the virtual loop path of the incoming signal is acquired by analyzing the signal forwarding process of the SCD model; finally, the virtual and real loop association is established by analyzing the.smap file, and the full-loop signal retrieval based on the SDD and SCD models is realized. The method effectively solves the problem that the fault positioning and loop query of the current operation and maintenance system mainly depend on manual work, and the virtual and real loop query needs to manually read multiple documents, which is time-consuming, labor-consuming and low in efficiency, and greatly improves the operation and maintenance efficiency.

The invention discloses a land measurement method and device based on multi-source data fusion, and relates to the technical field of measurement, and the method comprises the steps: collecting three-dimensional geodetic coordinate data and three-dimensional space point cloud data, obtaining a measured starting point three-dimensional coordinate and an end point three-dimensional coordinate, constructing a triangulation network terrain model and an earth surface shortest path search model, and searching a starting node and a target node in the weighted undirected graph, calculating a shortest surface path and a surface distance, and updating the shortest surface path and the surface distance by rendering a triangulation network terrain model, drawing the shortest surface path and setting an inevitable point and a forbidden area. By fusing multi-source data and constructing a continuous digital terrain, the dependence of traditional land measurement on intervisibility conditions is broken through, error accumulation of manual segmented operation is avoided by intelligently resolving and visualizing the shortest earth surface path, meanwhile, the interactive path re-planning capability is provided, and the method and the system have the advantages of being high in accuracy and high in reliability. The precision and efficiency of earth surface measurement under the complex terrain and the scientificity of planning and decision making are obviously improved.

The invention belongs to the technical field of emergency command and dispatch management evaluation, and particularly discloses and provides a multi-dimensional dynamic perception integrated cooperative command and dispatch system, which comprises a traffic weight updating module for updating the real-time traffic weight of each link of a whole road network according to the real-time vehicle traffic speed and the real-time ponding depth; the ponding trend prediction module determines a ponding prediction area based on the starting point and the ending point of the scheduling task, and predicts the ponding depth change of each link in the area in a future time period through hydrological deduction; the passing time window judgment module is used for judging a time window for keeping a passable state of each link in a future time period in combination with the accumulated water depth change; and the passing plan generation module is used for generating a scheduling path and a time plan by adopting a time-dependent shortest path search algorithm. According to the invention, the problems that the scheduling instruction is disjointed from the dynamic environment and the rescue deployment is in a passive response state are solved, and the accuracy and response efficiency of emergency command are improved.

This invention discloses an AI large-scale intelligent question cloud analysis method and system, comprising: a question preprocessing module for acquiring and preprocessing natural language question requests, and simultaneously establishing a data asset set in the cloud; a semantic retrieval module for recalling and re-ranking candidate semantic elements and constructing a training sample set; a model fine-tuning module for performing multiple rounds of fine-tuning on the LLaMA model, and performing semantic parsing and multiple rounds of planning to form a question intent field; a path selection module for performing bidirectional shortest path search on the data asset set in the cloud and selecting the optimal execution path as the question execution path; an operator compilation module for cost optimization compilation to generate a cloud-executable task instruction sequence; and a feedback optimization module for collecting feedback data and performing incremental fine-tuning updates. This invention enables the understanding of natural language question intent and improves the accuracy of question intent parsing.

The disclosure provides a knowledge graph-based expert recommendation method and device and a storage medium, and relates to the technical field of computers. The method comprises the following steps: setting a corresponding path weight for a connection path in a joint expert knowledge graph, setting a plurality of dimension weights corresponding to a second keyword based on a plurality of weight settings, searching in the joint expert knowledge graph based on a search keyword and using a shortest path search algorithm to determine a path between the search keyword and an expert node, and calculating the similarity between the expert node and enterprise demand information according to the corresponding path weight and the comprehensive weight to determine a recommended expert that matches the enterprise demand information. The method, device and medium of the disclosure make the recommended expert information more accurate and perfect, can more comprehensively and accurately recommend technical experts by finding the shortest weighted path in the knowledge graph through the shortest path algorithm, and improve the user experience.

The invention belongs to the related technical field of energy systems, and provides an energy router optimization method and system based on information physical fusion, an energy router system is constructed into a directed graph model, a node set represents various physical devices, and an edge set represents an energy flow path between nodes; carrying out shortest path search by adopting a path search algorithm, optimizing a minimum loss energy path for a source-load in real time, and generating a dynamic routing table; on the basis of economic flow and power flow, an energy storage carbon collaborative optimization target is introduced, a multi-target optimization model is constructed, and dynamic optimization of an energy transmission path, rapid stabilization of power fluctuation and unified optimization of economic and carbon emission targets are realized.