95 results about "Minimum spanning tree" patented technology

The invention discloses a main station big data-based low-voltage transformer area topology hierarchy identification method and system, and the method comprises the steps: constructing a multi-dimensional voltage feature vector through the voltage time sequence data, collected by a main station side, of a transformer area general meter and a user ammeter, and forming an electrical feature matrix through feature extraction; and on the basis, judging the station area affiliation and the phase line affiliation of the user electric meter through similarity calculation. Then, generating a stable consensus cluster based on multi-time window clustering and the copolymerization matrix, and mapping the cluster into a virtual electric meter box node; constructing a minimum spanning tree and carrying out directionalization to obtain an initial radial topological structure; further introducing an electrical consistency criterion based on correlation of voltage drop and subtree current, performing multi-candidate structure optimization on the preliminary topology, and finally obtaining an optimal transformer area topology hierarchical structure consistent with a physical rule; high-precision automatic identification of the low-voltage transformer area topology can be realized without manual participation, and effective support is provided for digital operation and maintenance of a power distribution network.

The invention relates to the technical field of intelligent scheduling, and particularly discloses an intelligent scheduling decision control method and system for a distributed car washing robot, and the method comprises the steps: constructing a weighted graph model which comprises a vehicle position, obstacle distribution and path reachability, and dynamically adjusting the weight of an edge according to the path length, energy consumption and time; optimizing the graph structure by adopting an improved minimum spanning tree algorithm, and calculating a path efficiency index in combination with fuzzy logic and a neural network technology; on the basis of the optimized subgraph, applying a shortest path algorithm to obtain a local optimal path, and introducing a dynamic adaptation coefficient to evaluate the response capability of the path to environment change; fusing the path efficiency index and the dynamic adaptation coefficient into a comprehensive scheduling feature vector, inputting the comprehensive scheduling feature vector into a trained deep learning scheduling model, and predicting an optimal scheduling strategy in combination with a task priority and a robot resource state; and dynamically adjusting the moving path and the operation density of the robot according to a scheduling result, and realizing self-adaptive evolution and cooperative control of the system.

The invention provides an offshore wind plant current collection network topology optimization method based on an improved grey wolf optimization algorithm, and the method comprises the steps: S1, obtaining basic data of an offshore wind plant, initializing the grey wolf algorithm, and generating an initial solution set; s2, adopting polar coordinates and a minimum spanning tree to optimize and expand the initial solution set; s3, optimizing a connection mode in each group; s4, executing the optimal connection of each group of fan combination; s5, performing optimal solution set exploration on the grey wolf algorithm by adopting an operator; s6, repeatedly executing until a preset maximum number of iterations is reached, and generating a topology model of the current collection system of the offshore wind plant; the method can improve the initial solution quality and the convergence efficiency, gives consideration to the global search capability and the local optimization precision, and achieves the quick and effective processing of geometric constraints.

The invention discloses a whole wind network wind volume deduction method based on limited actual measurement wind volume and a topological structure, and relates to the technical field of wind volume deduction. The relation between the spanning tree air volume and the residual tree string air volume is obtained; the ratio of the number of independent loops to the number of total branches in the mine ventilation network is 1 / 3; establishing a maximum air volume residual tree string model and a minimum air volume residual tree string model; a corresponding minimum air volume spanning tree and a corresponding maximum air volume spanning tree are obtained; respectively putting known air volumes into the maximum remainder tree string, the minimum remainder tree string or the maximum spanning tree and the minimum spanning tree to construct four air volume deduction models; and solving the deduction model by adopting an FLA optimization algorithm, and outputting the air volume of each branch of the whole wind network. According to the method, through air volume adjustment and global optimization deduction, the air volume of the whole mine ventilation network is deduced rapidly and accurately, the air volume monitoring defect in the prior art can be effectively overcome, and more accurate and timely mine air volume state sensing is provided.

The invention provides a power collection system topology optimization method and device based on a variable weight minimum spanning tree, and relates to the technical field of offshore wind power topology optimization. The method comprises the following steps: grouping a plurality of fans based on the angle difference among the plurality of fans according to the position information of the offshore booster station to obtain a plurality of fan sets; a Delaunay triangulation method is adopted to construct a reference grid connecting line of each fan set; and based on the reference grid connection line of each fan set, generating the optimal topology of the to-be-processed offshore current collection system based on a variable weight minimum spanning tree algorithm. According to the method, the grouping clustering method, the Delaunay triangulation method and the variable weight minimum spanning tree algorithm are combined, and the topology design of the offshore wind plant current collection system is efficiently, economically and rapidly achieved. According to the invention, topological connection and cable specification type selection can be optimized synchronously, and a global optimal solution is sought between the cable path length and the type cost difference caused by the change of the current-carrying capacity, so that the fine control of the overall cost of the current collection system is realized.

The invention provides a three-dimensional steel structure full-coverage path planning inspection method based on topology reconstruction, and relates to the technical field of industrial robots, and the method comprises the steps: obtaining a model file of a to-be-inspected three-dimensional steel structure; constructing an original vertex set and an original edge set according to the model file; performing adaptive clustering on each original vertex in the original vertex set through a density-based spatial clustering algorithm to obtain a cluster; taking the geometric center of the original vertex in each cluster as a topological node, and establishing a mapping relation between the original vertex and the topological node; carrying out topology reconstruction on the original edge set, and constructing an undirected weighted graph; stitching non-connected sub-graphs in the undirected weighted graph through a K-dimensional tree and a minimum spanning tree algorithm to obtain a fully connected graph; generating a full-coverage continuous path sequence through a Chinese postman algorithm; the full-coverage continuous path sequence is converted into a three-dimensional space coordinate sequence, and the three-dimensional steel structure to be inspected is inspected according to the three-dimensional space coordinate sequence.

The invention discloses an automatic generation method of an intelligent unmanned system city simulation test scene, and relates to the field of simulation scene construction and intelligent unmanned system test.The method comprises the steps that based on terrain boundary parameters, a plurality of rectangular areas with function labels are generated through Poisson disc sampling and a distance gradient algorithm; constructing a navigation grid representing the passable area; arranging a plurality of road intersections by adopting a constrained Poisson sampling algorithm; calculating the heart weight based on each intersection, and calculating the connection strength between the intersections through a gravity model; generating a global road network topology structure by adopting an improved minimum spanning tree algorithm; performing path search by adopting an algorithm A to obtain an optimal path, and automatically generating a road model and ancillary facilities; and extracting road network, road parameters and subsidiary facility information in the generated urban scene, and generating a standardized scene description file according to an OpenDRIVE standard format. And the construction efficiency of the simulation test scene, the test effectiveness and the cross-platform compatibility are improved.

The invention provides a transformer area topology identification method and system based on a graph neural network, and relates to the technical field of power system power distribution networks, and the method comprises the steps: taking an HPLC concentrator as an edge module, carrying out the modeling of a transformer area into a graph structure, taking a transformer and an intelligent electric meter as the nodes of the graph structure, and taking the potential electrical connection between the nodes as the edge of the graph structure; the edge module collects multi-source data of each intelligent electric meter in a transformer area, and after the multi-source data is preprocessed, node feature vectors and edge feature matrixes are obtained according to the preprocessed multi-source data; the edge module learns node features and edge features by using a graph neural network based on the obtained node feature vectors and edge feature matrixes, and calculates the probability of electrical connection between any two nodes; and the edge module adopts a minimum spanning tree algorithm to generate a transformer area topological structure according with the set physical constraint according to the obtained result. According to the invention, high-precision automatic identification of the transformer area topology can be realized.

The invention relates to the technical field of high-current particle beam diagnosis, in particular to a high-energy ion beam three-dimensional reconstruction method and system based on secondary electron emission signals. According to the technical scheme, the method comprises the steps of data preprocessing and conversion, geometric space up-sampling, point assignment generation and model boundary division and output. According to the method, the spatial sparsity of original data is overcome through geometric upsampling, the fidelity of physical attribute reconstruction is remarkably improved by utilizing a topological structure based on a minimum spanning tree and a primary function frequency superposition model, automatic and accurate division of beam boundaries is realized according to a physical threshold value, an end-to-end automatic processing flow is formed, and the method has the advantages that the method is simple and convenient to operate and high in practicability. And outputting a visual three-dimensional model supporting interactive analysis, systematically solving the problems of data sparsity, interpolation distortion and boundary fuzziness in the prior art, and realizing high-precision and high-efficiency reconstruction and visual analysis of the three-dimensional form of the high-energy ion beam.

The application provides a sandwich combination structure lower hanging steel beam coordinate precision control method, and belongs to the technical field of wind tunnel construction. The application establishes an independent reference control network, sets a forced closed control point to block error linear transmission, calculates the lower hanging steel beam camber, and offsets the dead load deflection through reverse prefabricated bending processing. A buried part rigid positioning frame is installed and the position deviation is monitored. A hydraulic synchronous jacking device is used to iteratively adjust the posture of the steel beam. Pre-stressed tension is applied to realize reverse arch shaping. Finally, the least squares adjustment technology and the minimum spanning tree optimization algorithm are used to reasonably distribute the section cumulative error between the forced closed control points, thereby solving the technical problem of excessive steel beam coordinate precision caused by large-span multi-section construction cumulative error.

The invention discloses a wind power plant current collection system topology design method and system based on an improved genetic algorithm, relates to the technical field of system topology design, and aims to solve the core problems of collaborative optimization of fan grouping and submarine cable connection and accurate matching of current-carrying capacity and cost under high-dimensional constraints. According to the method, a parameter calculation module is combined with a formula to determine the maximum feeder fan number and the number range, a grouping connection module combines polar coordinate grouping with a minimum spanning tree algorithm to construct an initial scheme, a cost modeling module calculates the cost through an exclusive function, and an iterative optimization module dynamically adjusts the grouping and fan number based on an improved genetic algorithm. And the constraint screening module eliminates violation schemes through a penalty formula, and finally generates optimal and suboptimal topological graphs containing core parameters. According to the method, the high-dimensional optimization problem is layered and disassembled, the constraint satisfaction degree and the economical efficiency are considered, the submarine cable investment cost is greatly reduced, the design efficiency and the engineering feasibility are improved, and the method is suitable for topology design of various offshore wind plant current collection systems.

The application discloses a kind of wind farm power collection system topology design method and system based on improved genetic algorithm, it is related to system topology design technical field, to solve the core problem of wind turbine grouping and submarine cable connection collaborative optimization under high-dimensional constraint, accurate matching of load flow and cost.The method determines the maximum number of wind turbines and the number range of feeder by parameter calculation module simultaneous equations, grouping connection module constructs initial scheme by polar grouping combined with minimum spanning tree algorithm, cost modeling module calculates cost by exclusive function, iteration optimization module dynamically adjusts grouping and the number of wind turbines based on improved genetic algorithm, constraint screening module excludes illegal scheme by penalty formula, and finally generates optimal and suboptimal topology graph containing core parameters.The application divides high-dimensional optimization problem into layers, considers constraint satisfaction degree and economy, significantly reduces submarine cable investment cost, improves design efficiency and engineering feasibility, and is suitable for various offshore wind farm power collection system topology design.

The application discloses a conflict-aware automatic routing method and system for analog integrated circuits, and relates to the technical field of computers.The method comprises the following steps: constructing a minimum spanning tree based on layout file information of the analog integrated circuit, generating a topology of the analog integrated circuit based on the minimum spanning tree, and obtaining target topology information; performing access point planning processing based on the target topology information; performing initial path planning based on the target topology information and access point planning information, performing line network distribution on the initial path information based on a cross relationship graph, and obtaining initial path information after line network distribution; performing 3D monotonic routing processing on the initial path information after line network distribution; and performing enhanced routing processing based on 3D monotonic routing information by using an A algorithm, and obtaining target routing information of the analog integrated circuit.The application realizes reliable routing in a complex layout environment, and ensures that the routing result meets production process rules.

The application provides a heterogeneous cooperative path planning method for a marine floating object target search task. A Parcel v2 particle simulator based on a Lagrange framework is used to predict the future trajectory and position of a plurality of particles according to real sea waves, ocean currents, wind fields and other information, and then a Parzen window method based on a Gaussian kernel function is used to obtain a target probability map. In the traditional GBNN method, the regional centroid and motion constraint are added to improve the external stimulation value of the neuron to plan the cooperative search path of the plurality of unmanned ships, so that the local optimum can be effectively avoided and the search efficiency is improved. A solar unmanned aerial vehicle is used as a communication relay of the plurality of unmanned ships, an optimal communication network connection is obtained by using a minimum spanning tree, and then the path of the unmanned aerial vehicle is planned. The application can improve the method for solving the marine search target of the plurality of unmanned ships, so as to improve the efficiency of the marine search target of the unmanned ships.

The invention discloses a power distribution network topological structure construction method and system adaptive to a double-high characteristic, and relates to the field of topology, and the method comprises the steps: collecting double-high characteristic data through a sensor, building an evaluation system, and calculating a node comprehensive influence index; k-means clustering grouping is carried out based on the index and the geographic position, an intra-group minimum spanning tree initial topology is constructed with the transformer substation as the center, and dynamic adjustment is carried out after simulation verification; then, the inter-group power exchange requirement is determined according to the load and new energy characteristics, and the optimal contact topology is determined through multi-objective optimization; and finally, the intra-group topology and the inter-group topology are integrated to form a complete structure, and a verification model is established to test the performance under different scenes. The method has the advantages that the challenges of high-proportion new energy and power electronic equipment are effectively coped with and stable and efficient operation of a power distribution network is guaranteed by comprehensively collecting double-high data, scientifically clustering nodes, hierarchically optimizing intra-group and inter-group topologies and combining double-high scene simulation dynamic adjustment and performance verification.

The application relates to the technical field of chip design, and particularly discloses a routing method and system based on timing criticality, which abstracts physical layout into a node network, constructs a weighted cost function of total wiring length and critical path length, adopts a minimum spanning tree algorithm to iteratively expand a path and record a parasitic parameter, calculates a merging cost value based on the product of the length of a coincident path and the timing criticality of a node, generates a virtual node by merging a node pair with the maximum benefit, and cyclically optimizes until a convergence condition is met, so that the dual objectives of wiring resource optimization and timing critical path delay reduction are achieved. The method is based on a more accurate time delay model, defines a target function which comprehensively considers the overall routing cost and the routing cost of a timing critical load node, makes timing analysis more accurate, reduces the signal delay and the size of a clock cycle of a load node according to the criticality of the load node, and effectively increases the running speed of a chip.

The application provides a TIN network construction method based on a spatial minimum spanning tree and a convex hull polygon, relates to the field of geographic information system data processing, and is used for solving the problems of low triangular network quality, topological errors and insufficient construction efficiency in the existing TIN construction method. In order to improve the construction quality of the TIN and maintain the global optimality, the spatial minimum spanning tree and the convex hull polygon of an input scattered point set are constructed in advance in the application, and then the two geometric structures are used as a framework to construct the TIN. In the growth process of the TIN, it is ensured that each generated triangle has excellent morphological characteristics (satisfying the "empty circumscribed circle" or "minimum angle maximization" condition) and topological correctness, and finally a high-quality irregular triangular network is constructed. Meanwhile, a "skip" mechanism of edges and points is provided, invalid traversal is avoided in the triangular network construction process, and the time efficiency of the algorithm is maximally improved.

The application provides a data blood relationship full-link analysis method based on a graph technology, characterized in that the data blood relationship full-link analysis method based on the graph technology comprises: converting data in a data source into graph data according to a preset structure, wherein the graph data comprises at least one vertex, and the vertex comprises a vertex parameter and an edge parameter; obtaining an analysis result according to a preset algorithm based on the vertex parameter and the edge parameter; and forming an analysis report according to the analysis result. The preset algorithm involved includes but is not limited to a minimum spanning tree algorithm, a DFS algorithm, a degree centrality algorithm, a Louvain algorithm and the like. In addition, the application further provides a system and a computer device. The technical scheme of the application effectively solves the problem that the existing data blood relationship analysis cannot be intelligently and efficiently analyzed.

The application discloses a cross-agency financial data federated learning modeling system and a privacy compliance verification method, relates to the technical field of financial data processing, and comprises the following: a federated aggregation module, which is used for aligning financial time sequence characteristics of each agency by a timestamp hashing alignment strategy on a server side, and aggregating the aligned financial time sequence characteristics by using a federated time convolution network to generate time sequence model parameters for capturing cross-agency global time sequence dependence; a federated reasoning module, which is used for generating a minimum spanning tree representation of global enterprise correlation relationship based on a local subgraph of enterprise correlation relationship constructed by each agency client on the server side based on a secure multi-party computing strategy; the server side aggregates graph embedding vectors by using a federated graph attention network and performs cross-agency graph reasoning in combination with the minimum spanning tree representation to construct graph model parameters for identifying enterprise correlation risks; and a model joint training module, which is used for fusing the time sequence model parameters and the graph model parameters on the server side to determine global model parameters.

This invention belongs to the field of optical engineering technology and discloses a method, system, terminal, and storage medium for extracting true skeleton points of trees based on deep neural networks and the minimum spanning tree algorithm. The method includes: acquiring raw point cloud data; predicting the raw point cloud data using a deep neural network to obtain the vector, radius, and category information of each point cloud; centering the raw point cloud data according to the vector, radius, and category information of each point cloud, and extracting initial skeleton points using the minimum spanning tree algorithm; simplifying and smoothing the initial skeleton points, and updating them using a true skeleton point update method based on Euclidean clustering to obtain true skeleton points; and outputting the true skeleton points. This invention improves the accuracy of extracting true skeleton points of trees and enhances the reconstruction accuracy of tree models.

The application provides a pseudo matching point pair removal method and device and electronic equipment. The method comprises the following steps: determining a matching point pair between a registration image and a verification image; in the case that the number of the matching point pair exceeds a preset number threshold, generating a first minimum spanning tree according to matching points in a first image of the registration image and the verification image, and generating a second minimum spanning tree corresponding to the first minimum spanning tree according to matching points in a second image; for any edge in the first minimum spanning tree and the second minimum spanning tree, determining the error of the two edges according to the length error and the angle error of the two edges; for any matching point, determining the error of the matching point according to the error of the edge with the matching point as a vertex; and removing pseudo matching point pairs from the matching point pair according to the error of each matching point. The method can improve the feature point matching accuracy.

The application provides a BOP data acquisition EWI generation method, medium and system, and belongs to the technical field of production business data.The application firstly constructs a multidimensional BOP data load matrix, accurately calculates the contribution value of each parameter through a thermodynamic entropy equation, then establishes a standard EWI basic matrix, and optimizes the BOP data acquisition strategy and calculates the data integrity score by using the minimum spanning tree algorithm.In the data processing stage, the EWI mergable index is accurately generated by using the Lagrange multiplier method, the transverse error is calculated by using the Euclidean distance function to analyze the spatial relationship between parameters, the longitudinal error is calculated by using the Fourier transform to monitor the time change trend of parameters, the two kinds of errors are comprehensively formed into a hybrid error evaluation result, and finally, the comprehensive index accurately reflecting the production quality state is output in combination with the EWI mergable index.

The application provides a low-power Bluetooth network optimization method, an electronic device and a storage medium, and relates to the technical field of network optimization. In the method, an initial network connection relationship graph is constructed according to an initial routing table corresponding to a low-power Bluetooth network, a minimum spanning tree corresponding to the initial network connection relationship graph is taken as a new initial network connection relationship graph, an intermediate routing table is generated according to the new initial network connection relationship graph, and the intermediate routing table is sent to all communication devices in the low-power Bluetooth network except the self, so that the communication devices receiving the intermediate routing table determine whether to disconnect the communication connection between the self and other communication devices according to the communication connection relationship recorded in the intermediate routing table, the optimization of the low-power Bluetooth network is realized, the network connection relationship and the routing strategy can be dynamically adjusted, unnecessary communication connections are reduced while the communication quality is maintained, resource consumption is reduced, and the working efficiency and stability of the low-power Bluetooth network are effectively improved.

The invention discloses a teaching and learning knowledge graph and mind mapping construction system based on multi-modal digital intelligence, relates to the technical field of education informatization, and is used for solving the problem of knowledge logic extraction and visualization of teaching multi-modal data. The method comprises the following steps: firstly, establishing a space-time three-dimensional coordinate system, locking an effective time period by utilizing the interaction density of writing actions and voice accent, and intercepting an audio-visual synchronous data packet; then, geometric coordinates and indentation features of the text entities are analyzed, and an initial structured entity tree representing the hierarchical relation of the static space is constructed; the analyzed teaching operator constructs a cross-space implicit association edge through a logic tension coefficient and executes reverse pruning to generate a dynamic semantic topology network; and finally, executing a minimum spanning tree algorithm based on the multi-modal reproduction weighted value, reserving a backbone path, converting the backbone path into hierarchical tree data, and generating a mind map, thereby realizing intelligent construction from unstructured teaching field data to a structured knowledge graph.

The application discloses a kind of based on three-dimensional point cloud image's Pinus massoniana partial phenotypic parameter automatic measurement method. Three-dimensional point cloud image of Pinus massoniana plant under different viewing angles is collected;Pretreatment obtains the three-dimensional point cloud of Pinus massoniana plant;Registration is carried out to obtain fused point cloud;Extract the minimum spanning tree and the skeleton point of main stem, and then obtain the main stem point cloud and leaf point cloud;According to the minimum spanning tree, main stem point cloud and leaf point cloud processing obtain main stem length, Pinus massoniana ground diameter, average leaf length and leaf number.The method of the application can automatically identify Pinus massoniana plant in three-dimensional point cloud image, and complete the strategy of main diameter length, ground diameter, average leaf length, leaf length, improve the detection efficiency, realize high-precision, high-efficiency crop phenotypic data acquisition, achieve fast, low-cost crop phenotypic parameter accurate and nondestructive testing.

The application discloses a battery replacement cabinet intelligent operation monitoring method and system, the method comprises the following steps: based on the 24-hour sliding statistical data of the voltage and temperature of a single battery compartment in the battery replacement cabinet, a thermal-electric imbalance index is obtained through standardized deviation calculation and exponential smoothing; based on the multi-physical information of the threshold-exceeding compartment of the thermal-electric imbalance index, a multi-dimensional topology node set is constructed, and a thermal-electric coupling spread potential is calculated in combination with a minimum spanning tree structure; based on the thermal-electric coupling spread potential and the length of the waiting queue, an exponential adjustment of the time period adaptive weight and a tail risk penalty are fused to obtain a service resilience index; based on the service resilience index and the current number of idle compartments, a dynamic redundancy compression and a safety lower limit protection are performed to obtain an available safety margin; and based on the available safety margin of the battery replacement cabinet and the difference between the service resilience indexes of adjacent cabinets, a standard deviation discrimination and an exponential decay mapping are performed to obtain a regional collaborative guidance intensity. The application improves the intelligent level of the battery replacement cabinet in the aspects of safety risk perception and service capacity adjustment.

The application relates to a minimum spanning tree-based SAR tomography reference net generation method and device. The method comprises the following steps: calculating amplitude deviation index values of all PS points in a remote sensing imaging area constituting an imaging reference net, selecting a PS point with the minimum amplitude deviation index value from all PS points as a starting reference point according to the amplitude deviation index values of all PS points, adding the starting reference point into an SPS point set, and initializing an SPS edge set as an empty set; the imaging reference net comprises a PS point set; according to a pre-set distance threshold, PS edges meeting the distance threshold are sequentially found in the SPS point set and the PS point set, and a candidate SPS edge set is set; the highest-quality edge is selected from the candidate SPS edge set and added into the SPS edge set, and the end points corresponding to the highest-quality edge are moved from the PS point set to the SPS point set, and finally, an SPS edge set and an SPS point set are output; and a SAR tomography reference net is constructed according to the final SPS edge set and the SPS point set. The method can generate a reference net which maximally covers a full scene.

This invention relates to a time-domain electromagnetic simulation method based on Tree-Cotree decomposition and a hybrid DG-FE / SE domain decomposition. The method includes: dividing the computational domain into a tetrahedral finite element subdomain and a hexahedral spectral element subdomain according to geometric dimensions and electromagnetic properties; constructing a minimum spanning tree and cotree based on mesh edges to apply Gaussian divergence constraints; discretizing both the finite element and spectral element regions using scalar and vector basis functions to obtain Galerkin weak solutions; uniformly processing the interface between the finite element and spectral element subdomains using a topology identification-polygon decomposition-Gaussian integration method, and combining this with upwind flux to achieve continuous field transfer; assembling the spatial discretization matrix of the Galerkin weak solutions, and completing time propagation using an explicit fourth-order Runge-Kutta scheme. Compared with existing technologies, this invention systematically eliminates the low-frequency collapse problem, ensures the non-singularity of the system matrix, and guarantees solution accuracy and efficiency.

The present application discloses a method and system for extracting and measuring linear structure information of rock wall from point cloud data. In view of the problem that the prior art does not solve the whole process of extracting linear structure information of rock wall from point cloud data, the present application provides a method and system for extracting and measuring linear structure information of rock wall from point cloud data. The technical scheme fully utilizes three-dimensional color point cloud information of rock wall, comprehensively uses DBSCAN clustering, improved region growing algorithm, graph model, minimum spanning tree and other methods, establishes an automatic processing scheme of rock wall point cloud based on collaborative analysis of geometric features and color information, accurately identifies linear structure in the point cloud, and directly obtains measurement data through quantization, which is a point cloud automatic and high-precision processing scheme from field original collection to measurement data output. The present application provides a new idea of understanding rock wall structure from color information. The present application can be applied to engineering design and construction safety assessment, and can improve the response speed and accuracy of geological disaster warning.

The invention relates to a PCB wiring method and device of a power circuit and computer equipment, and the method comprises the steps: obtaining a plurality of basic characteristic parameters of each power signal network in the power circuit; each basic characteristic parameter comprises a network topology parameter and an electrical constraint parameter; generating a corresponding minimum spanning tree based on the network topology parameter of each power supply signal network; based on the electrical constraint parameter of each power supply signal network, determining a dynamic current value of each node in the corresponding minimum spanning tree; and based on the dynamic current value of each node in each minimum spanning tree, performing wiring planning on the connection path between the nodes in each minimum spanning tree to obtain a wiring scheme of the power supply circuit, thereby solving the problem of low wiring quality caused by incapability of realizing global collaborative planning of all power supply networks in the board without considering the actual demand of power supply wiring, and improving the wiring quality of the power supply circuit. All power supply networks in the board are globally and cooperatively planned based on the actual characteristics of power supply wiring, and the wiring quality is remarkably improved.