114 results about "Span tree" patented technology

The invention provides an intelligent fault diagnosis method and system for a photovoltaic system. The method comprises the following steps: collecting multi-source heterogeneous operation parameter data of the photovoltaic system based on an intelligent sensor network and carrying out standardized preprocessing; local feature extraction is carried out on edge nodes, a frequency moment is calculated, data summary aggregation is carried out through a frequency moment optimization algorithm, and a fusion key feature vector set is constructed by using a multi-modal data fusion model; performing anomaly detection based on the normal behavior mode baseline, and generating an abnormal state alarm signal and a preliminary anomaly type indication; constructing a weighted graph model based on a system topological structure, constructing a fault association sub-graph by using an approximate spanning tree algorithm, accurately positioning a fault unit and diagnosing a fault type; and generating and executing a self-healing operation scheme according to the fault diagnosis conclusion. Through the distributed multi-modal data fusion and approximate spanning tree fault positioning technology, rapid and accurate diagnosis and autonomous recovery of the photovoltaic system fault are realized, and the system reliability and the operation efficiency are improved.

The invention relates to the technical field of big data management, in particular to a data tracing method based on big data mining, which comprises the following steps of: acquiring an unstructured operation log, analyzing the unstructured operation log into a structured event record, and associating to generate a heterogeneous operation session set; performing access mode association analysis on the session set to extract a read-write path mode, and combining association strength and a time decay factor to determine a dependency weight and construct a blood relationship map; eliminating a loop of the graph to generate a directed acyclic graph, constructing a spanning tree serving as a retrieval trunk and a node index coding interval, and mapping a cross-branch associated edge to a bitmap index to generate a probability skeleton tree index; and positioning a trunk path by using the interval, calling a bitmap to perform multi-path verification, and outputting a traceability path and confidence. A probability consanguinity map and a probability skeleton tree index are constructed through mining logs, and data consanguinity reconstruction and large-scale node low-delay retrieval in the heterogeneous black box environment are achieved.

The invention belongs to the technical field of intelligent power distribution networks, distributed energy management and energy internet, and particularly relates to a transformer area micro-grid mutual aid regulation and control operation method and system considering a flexible interconnection device and topology flexibility. Acquiring basic data; constructing a node power flow balance model containing a flexible interconnection device, taking energy storage of each transformer area as an independent regulation and control unit, and establishing an energy storage operation model in combination with charge state constraint, capacity limitation, charge and discharge mutual exclusion and life constraint; virtual commodity flow constraints and spanning tree structure constraints are introduced, and a radiation type topology model capable of being dynamically switched is constructed; constructing a comprehensive optimization model, and solving by utilizing power flow-topology-energy storage coupling constraint to obtain a multi-transformer-area global optimal scheduling scheme; and outputting an optimal topological structure, a flexible interconnection device power instruction and an energy storage charging and discharging scheme. According to the invention, a traditional fixed topology and isolated energy storage scheduling mode is broken through, a unified optimization mechanism of power flow-topology-energy storage linkage is established, and active and flexible operation of the power distribution network is realized.

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 discloses a radial power distribution network topology identification method, system and device and a medium. The method comprises the following steps: acquiring node voltage amplitude measurement data; calculating a sample covariance matrix based on the voltage amplitude measurement data to obtain the covariance of the voltage amplitude between the nodes; estimating a precision matrix of the covariance matrix through a graph lasso model; calculating a partial correlation matrix based on the precision matrix, wherein the partial correlation matrix is used for representing a direct correlation coefficient between nodes in the radial power distribution network; and deriving an adjacent matrix through a maximum spanning tree based on the partial correlation matrix to obtain a radial power distribution network topological structure. According to the method, sparse learning and partial correlation analysis are combined to deal with the problem of limited data volume; the key condition dependency relationship between the nodes can be quickly and accurately identified only through voltage amplitude measurement data without a large number of samples and phase angle information, and the identification precision is high.

Techniques and architecture are described for a method that includes an in network compute (INC) manager receiving from switches of a fat tree configured network, arithmetic logic unit (ALU) capacity of the switches. Based at least in part on the ALU capacity of the switches and bandwidth, the INC manager determines one or more switches within each tier that are capable of supporting the processing units and based at least in part on the determining, the INC manager selects a first switch as a root, wherein the first switch is included within a tier of switches having intermediate tiers of switches located between the tier and the plurality of processing units within the fat tree configured network. The INC manager creates one or more paths of switches within each of the intermediate tiers from the root to the plurality of processing units to provide a constrained disjoint spanning tree of switches.

The invention discloses a sales demand analysis method and system based on AI and portraits. The method comprises the steps of collecting multi-source heterogeneous data such as basic information, transaction records and online behaviors of customers; according to the method, a self-developed large model of the Chinese human life research and development center is adopted, implicit requirements in a customer behavior sequence are deeply mined through an attention mechanism, a hierarchical clustering algorithm is used for generating a tree-shaped clustering graph based on a Ward connection method, and high-value features with variances larger than 0.8 and absolute values of correlation coefficients larger than 0.5 are screened out in combination with a rule engine; it is ensured that the extracted features have statistical significance and are directly associated with business targets, invalid feature redundancy is avoided, the efficiency and accuracy of subsequent portrait construction are improved, product recommendation priorities are determined through a decision tree algorithm, and a Q-learning framework is combined to optimize communication verbal skills and cross sales strategies, so that the sales strategies meet the current demands of customers, and the customer experience is improved. Potential requirements are guided, and the conversion rate and the customer satisfaction degree are both improved.

A network device may include memory circuitry and processing circuitry. The processing circuitry may be configured to obtain a spanning tree topology indicating at least one spanning tree interface state. The processing circuitry may be configured to perform reachability information advertisement based on the spanning tree interface state. In some illustrative configurations, the network device may be one of multiple multihoming network devices configured to provide an Ethernet segment and the reachability information being advertised based on the spanning tree interface state includes Ethernet Virtual Private Network (EVPN) route information.

The application provides a virtual power plant real-time simulation method and system based on digital twinning, relates to the field of virtual power plant real-time simulation, and comprises the following steps: constructing a state transition graph, distinguishing a deterministic path and a random path based on transition probability entropy value, respectively establishing a main twin model and a disturbance twin model, generating a tree-shaped operation trajectory bundle, calculating an intersection of an envelope boundary and an operation constraint boundary to identify a risk moment, and generating a control instruction according to the intersection. The application can realize intelligent prediction and real-time control of distributed power supply, and improve the operation reliability of a virtual power plant.

This invention relates to the field of blockchain technology and discloses a Merkle tree hardware acceleration system for blockchain data verification. The system includes a control module for coordinating and controlling various modules; an address generator for generating addresses of sibling and parent nodes in the Merkle tree based on the indices of the input leaf nodes; a storage unit for storing the leaf, internal, and root node data of the Merkle tree; a computation module for performing data concatenation, hashing, and comparison on the Merkle tree nodes based on the addresses provided by the address generator, and generating intermediate and verification results; and a buffer for temporarily storing node data read from the storage unit and intermediate results output by the computation module. This invention designs a hardware acceleration architecture tailored to the structural characteristics of Merkle trees, improving the computational efficiency of blockchain data verification, achieving low-power operation, and is suitable for the performance requirements of various blockchain application scenarios.

The invention provides a packet consistency research method for a cooperation-competition network discrete heterogeneous multi-agent system with packet loss, and the method is characterized in that the method specifically comprises the following steps: 1, determining a dynamic model of the heterogeneous multi-agent system; 2, designing a packet consistency control protocol about packet loss; 3, obtaining a closed-loop form of the kinetic model according to the control protocol in the step 2; 4, assuming that the topological structure of the heterogeneous multi-agent system is a bipartite graph containing a spanning tree, and setting establishment conditions; and 5, proving that the establishment condition is established, and indicating that the closed-loop form of the dynamic model can realize progressive grouping consistency.

This invention relates to a geochemical prospecting method based on graph neural networks and spatial features, enabling geochemical prospecting under different geological environments based on accurately predicted background concentrations of different chemical elements. The method includes: preprocessing raw geochemical multi-element data and separating it from background data to obtain background area data; constructing spatial context statistical features for each sampling point of the geochemical multi-element data according to a preset spatial scale, and fusing them with the original environmental features of that sampling point to generate an enhanced environmental feature vector for each sampling point; constructing a graph topology based on the statistical correlation between chemical elements in the background area data using the maximum spanning tree algorithm; constructing a graph neural network based on the graph topology, inputting the enhanced environmental feature vector of each sampling point into the graph neural network, outputting the predicted background concentration of each chemical element at each sampling point, and calculating a mineral prediction map.

Example embodiments of the present disclosure relate to a solution for a communication network supporting spanning tree algorithms and protocols. In one solution, a first device receives configuration information for a spanning tree algorithm and protocol (STP) in a communication network. The configuration information will be used for calculation of spanning tree results based on edge ports and non-edge ports in the communication network. Then, the first device acquires state information indicating a result of the spanning tree, the state information being determined based on the configuration information. In this way, the STP may be flexibly supported in the communication network.

To achieve redundant data transmission in a communication network, at least a first (201) and a second virtual local area network (202), VLAN, are each configured on communication devices (101-104, 112-113, 122-123, 132-133, 142-144) of the communication network that forward datagrams (300). Different spanning trees are determined for each of the first (201) and second VLAN (202) within the communication network by applying a spanning tree protocol, said spanning trees being used to specify, for each of the first and second VLAN, active paths for forwarding datagrams via the forwarding communication devices. At least selected datagrams (300) to be transmitted are duplicated by a transmitter-side communication device (111) and transmitted both via the first VLAN (201) and via the second VLAN (202). Received datagrams (300) associated with the VLANs (201, 202) are each checked for identity with an already received datagram by receiver-side communication devices (121, 131, 141) and discarded if an already received identical datagram is present.

The application discloses a kind of command and control system safety risk assessment methods based on linear influence.First, the physical connection diagram and information flow diagram of command and control system are established, and the bottom map is aggregated to form the bottom map of causal diagram in layers;Non-causal relationship in the bottom map is eliminated from the opposite direction of the form of spanning tree to the cause transmission;An index abstraction system is established, and the resource nodes in the causal diagram are decomposed into index nodes;Input system operation raw data is normalized and data interpolation processed;The linear relationship of abnormal node to each path on the subnode is calculated by least square estimation;After traversing all paths of abnormal node, the influence degree of abnormal node on each path is calculated;The influence degree of abnormal node on subsequent nodes, influence domain range and alarm level are output.The method can effectively calculate the influence result of abnormal node under different risk scenarios, improve the reliability and safety of command and control system.

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 invention discloses a multi-center hierarchical management architecture unmanned cluster management method and system based on a minimum diameter spanning tree, and the method comprises the steps: collecting communication delay information among all nodes, and constructing a completely undirected graph which takes the nodes in an unmanned aerial vehicle group as vertexes and the communication delay among the nodes as edge weights; sorting the edges of the completely undirected graph from small to large according to the edge weights, and determining an optimal tree generation interval meeting the constraint of the multi-center hierarchical management architecture based on a bipartite enumeration method; solving a minimum diameter spanning tree of the sub-graph according to the sub-graph corresponding to the optimal spanning tree interval, and taking the minimum diameter spanning tree as the optimal spanning tree meeting the multi-center hierarchical management architecture; according to the degree of each node in the optimal generation tree and a central node of a diameter link, roles are distributed to each node; and when the inter-node communication index does not meet the preset threshold value, triggering regrouping by the master node. The method provided by the invention can still keep low delay and expandability in a complex scene.

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.

The invention relates to the technical field of deep learning, and particularly discloses a neural network solving method and system for a weighted maximum satisfiability problem, and the method comprises the steps: representing an input conjunctive normal form formula as an edge splitting factor graph; constructing a graph neural network model, wherein the model comprises a supervised message passing layer and an unsupervised solution enhancement layer; an edge splitting factor graph is input to the graph neural network model, in the message passing layer, message passing is conducted on four types of edges through independent aggregation functions, and initial assignment prediction of variables is generated; and inputting the initial assignment prediction into the unsupervised solution enhancement layer, evaluating the quality of the current assignment, and carrying out iterative optimization on the variable assignment based on a relaxation optimization technology so as to output an optimized final solution. The invention provides a new graph representation method for a CNF formula, namely an edge splitting factor graph. According to the method, the spanning tree is generated, richer structure information is provided for the GNN, and therefore the learning efficiency is improved in the message passing process.

The invention discloses an unmanned ship full-coverage connection topological optimization path planning method and system for underwater target search and detection, a storage medium and electronic equipment, and the method comprises the steps: firstly carrying out the environment modeling and rasterization of a detection region, and obtaining a free grid set and neighborhood state information; the method comprises the following steps: establishing a mixed integer linear programming model containing geometric continuity constraints and topological structure rewards to obtain a global optimal rectangular decomposition scheme under the balance of geometric boundary cost and topological connection rewards; establishing a minimum turning spanning tree to minimize the turning times of the coverage path by judging the connection type and turning cost between the rectangles; and finally, generating a smooth coverage trajectory in combination with the kinematics constraint of the unmanned ship. According to the method, the problem of sonar image distortion caused by too many turning times in the existing coverage path planning method is solved, the global turning times of the coverage path are reduced, the problem of detection precision decline caused by the fact that acoustic imaging conditions are damaged due to frequent turning maneuvering in the traditional path is solved, and the detection path quality is optimized.

The disclosure provides for generating an inventory of trees in a target area. A LiDAR point cloud is acquired by an airborne scanner. The point cloud is used to generate a digital terrain model. It is segmented semantically into classes such as vegetation, then segmented panoptically both to further separate trees from low vegeation and to delineate trees. Each tree is projected to the digital terrain model, and the result is provided to an encoder and a classifier used to determine the tree species. An aerial image can optionally be acquired as well. The projected tree can be used to determine the crown class of the tree: dominant or overtopped. For dominant trees, a cropped image of the tree is generated and provided to a distinct encoder, allowing the classifier to benefit from the embedding of both the point cloud and the image.

The application relates to a power distribution network edge side topology identification method, device and equipment and a readable storage medium. The method comprises the following steps: establishing a voltage mutual information graph based on first voltage mutual information between each device in a target edge computing node, second voltage mutual information between devices in the target edge computing node and devices of adjacent edge computing nodes and each device in the target edge computing node; processing the voltage mutual information graph by using a distributed maximum spanning tree algorithm to establish a spanning tree; and obtaining a topology identification result based on the spanning tree and the voltage mutual information graph under the condition that all the devices in the voltage mutual information graph are contained in the spanning tree. The method can improve the topology identification efficiency.

The application discloses a transformer substation switch port flow abnormality diagnosis method and device, high-frequency data of the switch is collected through an SNMP probe, a SCD configuration file is analyzed to establish a mapping relationship between communication nodes and switch ports, and a physical network topology graph is constructed; the number of spanning trees of each service node is calculated as an index of network connectivity contribution degree by using a matrix tree theorem, and the importance of services borne by each port is rated; a sliding time window algorithm is used to extract time sequence characteristics, and a global minimum cut approximation algorithm is combined to establish a dynamic baseline model of each port; a differentiated threshold strategy is used for abnormality detection on ports of different service levels; an original dual covering small cut method is used for abnormal event correlation analysis, and a three-layer correlation model of a port-link-protection interval is established. The problems that a traditional static threshold model cannot adapt to dynamic changes of services are solved, and accurate mapping from network abnormality to service influence is realized.

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 invention discloses a multi-step vulnerability utilization chain automatic generation method and device based on a knowledge graph, and belongs to the technical field of combination of cyberspace security and artificial intelligence. The implementation method comprises the following steps: 1, constructing a vulnerability knowledge graph; 2, performing full-text indexing and graph traversal on the vulnerability knowledge graph to obtain a structured context; 3, the Qwen3coder model constructs a penetration test spanning tree in the form of a tree structure by using the dependency relationship between penetration steps and hierarchical nodes, and obtains the current penetration test spanning tree state; 4, executing the analysis agent, the planning agent, the command generation agent, the execution agent and the evaluation agent in sequence in a circulation mode, and generating a complete vulnerability utilization chain plan; and 5, generating a penetration test report for defense by utilizing a Qwen3coder model based on vulnerability utilization chain planning. Compared with the prior art, in a complex network environment, automatic planning of a multi-step vulnerability utilization chain is achieved, and then vulnerability utilization defense is completed.

The invention discloses a low-temperature preheating and heat preservation control method and system for a lithium iron phosphate battery. The method comprises the following steps: acquiring temperature data of a battery pack, and calculating an optimal temperature measurement point distribution position through a small vertex coverage algorithm; on the basis of the temperature field distribution data, the preheating requirement is judged through a decision tree algorithm in combination with the environment temperature and the charge state; generating a preheating scheme by using a multi-objective optimization algorithm; constructing a heat conduction equation set through an algebraic method to calculate a PTC heating power dynamic adjustment curve; a heat recovery network topological structure is constructed through a small vertex coverage spanning tree algorithm, waste heat is captured, and a heat distribution strategy is calculated; and constructing a heat balance equation set through an algebraic method, and calculating working parameters of the liquid cooling or air cooling system. The problem that the lithium iron phosphate battery cannot be charged in a low-temperature environment is solved, efficient utilization of battery loop waste heat is achieved, and system energy consumption is remarkably reduced.

This application discloses a data rendering method, apparatus, and storage medium. Relating to the field of data processing, the method includes: receiving raw data to be rendered via a program interface, wherein the raw data has a tree structure; obtaining configuration options corresponding to the raw data, and generating tree structure data based on the raw data and configuration options; determining the target node range based on the tree structure data and a target display area, and flattening the data within the target node range in the tree structure data to obtain target data; passing the target data to a virtual scrolling list component, and rendering the target data based on the virtual scrolling list component to obtain a tree-like rendering result of the target data. This application solves the problem of insufficient performance in data rendering in related technologies.

The invention discloses a distributed construction method for an affine formation hierarchical topology of a multi-agent system, and the method comprises the steps: designing a hierarchical directed topology according to an affine formation configuration, and selecting the hierarchical directed topology as a spanning tree, so that the affine formation topology meets the condition that the number of interaction edges can be minimized under the condition that any target configuration can be reached; each node calculates an error between each neighbor node in a communication range of the node and an expected position of the node, and selects a neighbor with the minimum error in nodes with higher levels as a father node to form a local topology of each node so as to construct a spanning tree; and aiming at the local topology of each node, solving a stress value between the nodes by utilizing a stress balance condition so as to obtain an optimal interactive topology in real time. According to the method, after an expected configuration and a corresponding optimization index are given, each agent can optimize own neighbor selection in a distributed manner and calculate a stress value, so that a better interactive topology is generated in real time, and a system convergence error is optimized.

The application discloses a hierarchical three-dimensional modeling method and system taking a scene skeleton as an anchor point, and belongs to the technical field of computer vision and three-dimensional reconstruction. k The local subgraph is constructed and the local community is divided based on the abutment screening structure; the island-level graph is constructed based on the local community, the skeleton subgraph is constructed through the maximum weight edge disjoint spanning tree merging and the selective verification of the double-view disambiguator; the non-skeleton image is attached to the skeleton node in the corresponding community as a leaf node; and the scene skeleton is reconstructed based on the skeleton subgraph, and the complete reconstruction is completed by gradually absorbing the leaf node. Through the hierarchical graph construction and the selective verification mechanism, the application solves the problem that the robustness and the efficiency are difficult to be considered in the large-scale scene reconstruction, can effectively inhibit the visual ambiguity propagation while significantly reducing the calculation overhead, and realizes the high-integrity three-dimensional modeling.