22 results about "Depth-first search" patented technology

This invention relates to a multi-agent orchestration and execution method supporting complex cyclic graph structures, comprising: S1: receiving workflow configuration and constructing a directed graph data structure; S2: performing a depth-first search traversal on the directed graph data structure, detecting and outputting strongly connected components in the directed graph data structure; S3: abstracting strongly connected components containing multiple nodes into super nodes, and keeping single-node strongly connected components as ordinary nodes, thereby constructing a directed acyclic graph containing super nodes; S4: performing topological sorting on the directed acyclic graph to generate a hierarchical execution plan containing multiple execution layers; S5: scheduling execution items according to the hierarchical execution plan, and when an execution item is the super node, starting a loop executor for iterative execution. This method, by constructing a multi-layered technical system, integrates graph algorithm innovation, unified context management, abstraction layer design, metadata-driven techniques, etc., to achieve automated orchestration and execution of multi-agent workflows supporting cyclic graph structures.

The present application relates to the field of automatic drawing, in particular to a substation secondary circuit drawing multi-element collaborative identification and topology reconstruction method, the method comprises the following steps: receiving scanning drawing, photo, CAD export image multi-source input, drawing standardization pretreatment; terminal and device symbol are recognized by using target detection, text information is extracted and classified through OCR, and connection line is tracked by using skeleton extraction; confidence data of each element is generated synchronously; based on distance, direction and format constraint, matching score is calculated, terminal and number binding is realized by using optimal matching, and correlation is iteratively corrected by device and terminal attribution, connection line and terminal adsorption rule; the recognition result is converted into graph structure, topology network is constructed, loop type and closure are identified by using depth first search; abnormal elements are automatically marked, quality evaluation report is generated; output data supports drawing incremental update and version traceability, and connects downstream application platform.

The application discloses a three-dimensional human skeleton fitting method and system based on a multi-camera joint association graph and combined search, and relates to the three-dimensional human skeleton fitting method, which comprises the following steps: S1, acquiring images collected by multiple cameras, detecting human two-dimensional joint nodes by using a two-dimensional pose estimation algorithm, and projecting the two-dimensional joint nodes into three-dimensional rays; S2, taking the joint nodes as nodes and the geometric consistency between three-dimensional rays of different cameras as edge weights, constructing a multi-camera joint node association graph; S3, performing group clustering on the cross-camera joint nodes with high geometric consistency on the association graph by using a breadth-first search, and forming a candidate skeleton cluster; S4, reserving the first K joint nodes with the highest geometric consistency with the candidate skeleton cluster in each camera, and obtaining candidate joint node pairs; S5, using a depth-first search (DFS) to enumerate the cross-camera joint node pairs, and screening optimal joint node pairs in combination with a pruning strategy; and S6, performing triangulation processing on the screened optimal joint node pairs, obtaining three-dimensional skeleton points, and outputting a three-dimensional human skeleton structure.

The application discloses a substation work ticket knowledge graph construction method based on a large language model, and belongs to the field of energy power and artificial intelligence. The method comprises the following steps: based on standardized electrical drawing annotation data, independent knowledge graphs are generated through data reorganization preprocessing, rough knowledge graph construction and attribute supplement reasoning; all independent knowledge graphs are divided into framework layer graphs and detail layer graphs according to voltage levels, and hierarchical fusion strategies are adopted to complete full graph fusion; breakpoint detection is carried out by using an isolated point detection algorithm based on degree centrality, connectivity analysis is carried out through depth-first search, and non-connected subgraphs are re-fused; abnormal nodes are screened based on electrical connection rules, a large language model is input to automatically fill in Agent to generate correction suggestions, and graph optimization is completed. Through the cooperation of the large model Agent and multiple algorithms, the application improves the efficiency and accuracy of electrical data structuring, and provides knowledge network support for substation automation operation and fault diagnosis.

The application discloses a kind of construction methods of automobile parts full life cycle digital twinborn model, it is related to digital twinborn technical field, including, life cycle dataset is input initial life digital twinborn model, time domain local feature fusion is carried out in feature extraction layer, degradation trend is captured in time series analysis layer, form the life prediction value of automobile parts, extract actual detection value in life cycle dataset, calculate the deviation of life prediction value and actual detection value of automobile parts, deviation is mapped in time series relationship, generate dynamic causal graph, graph traversal is carried out to dynamic causal graph, obtain key degradation path node, correlation analysis is carried out to key degradation path node using dynamic causal reasoning, generate degradation characteristic parameter, the application is realized by using depth-first search and analytic hierarchy process, dynamic causal correlation accurate modeling of life digital twinborn model, significantly enhance the robustness of life digital twinborn model under actual complex working conditions.

The application provides an OpenAPI multi-step state fuzzy testing method and related device, and relates to the technical field of network security. Through two stages of offline knowledge construction and online state exploration, the problems of too large sequence space, poor request executability and disconnection of exploration are solved, the search space is effectively compressed, semantic guidance is provided, and combination explosion is avoided; through runtime load multiplexing, the executability of deep state paths is ensured; deep-first search scheduling and snapshot rollback are adopted to ensure exploration efficiency and result reproducibility, thereby having the advantages of efficiently detecting multi-step state vulnerabilities.

The application discloses a contract attack detection method and device based on symbolic execution and a graph neural network, comprising: obtaining deployment bytecode and runtime bytecode of a smart contract; performing symbolic execution on the runtime bytecode, extracting external calls and event information through depth-first search and taint tracking; constructing a contract call information graph and iteratively simplifying it; performing multi-dimensional feature coding on each node to generate a node feature vector; encoding on-chain metadata of a deployer into a deployer feature vector; constructing and training a graph embedding network and a classification network, the input of the graph embedding network being the simplified contract call information graph, the node feature vector and edge type information, and the output being a graph-level feature vector; the input of the classification network being a joint feature vector obtained by splicing the graph-level feature vector and the deployer feature vector, and the output being a contract classification result. The application can cover multiple attack types and realize attack contract identification with low false alarm rate by extracting contract execution logic structures for detection.

The present application belongs to the field of multi-robot path planning, and specifically relates to a double-layer multi-robot path planning method based on state search and priority. The algorithm uses a deep-first search guided iteration framework in the upper layer to provide full-view planning, and uses a priority-based method in the lower layer to avoid obstacles. Meanwhile, the lower layer search adds a turning penalty factor in the single-robot path cost function to reduce the number of turns; combines priority inheritance and expands the time window considered when avoiding conflicts to reduce the number of conflicts; and pre-processes the map to search out narrow passages, which are regarded as mutual exclusion quantities, and only allow one robot to pass through to avoid the situation of avoiding after entering the passage. The present application has wide application value and can meet various tasks and constraint conditions, and has many practical applications in flexible manufacturing systems such as intelligent workshops, logistics centers, automated warehouses and the like. The present application has important significance for improving system efficiency and reducing system cost.

The application discloses a network security event report generation method and device based on a dynamic resolution community discovery algorithm, equipment and a medium, and relates to the field of network security. The method comprises the following steps: extracting target information in original network security alarm data as nodes, and constructing a time sequence relationship graph based on the nodes and the directed edges between the nodes; enumerating a plurality of resolutions in a preset resolution interval, performing a preset community discovery algorithm on the time sequence relationship graph according to the plurality of resolutions to obtain corresponding community division results, and determining an optimal community division result based on the normalized mutual information between the community division results; subdividing or merging the sub-communities in the optimal community division result to obtain a target community division result; identifying a core attack node in the target community division result; performing a depth-first search on the target community division result starting from the core attack node to extract a path set having a causal association with the core attack node, and generating a security event report based on the path set.

The application relates to a blockchain cryptocurrency fund flow searching method and a control system. The method comprises the following steps: acquiring transaction detail data information, preprocessing the transaction detail data information, and generating a materialized view; presetting a search condition of a query address, and acquiring the query address from the materialized view according to the search condition; traversing the query address, obtaining a first result graph, saving a target address in the first result graph, and searching from the target address in sequence through breadth-first search and depth-first search to obtain a target path list. The breadth-first search and the depth-first search are combined, the searching efficiency is effectively improved, the requirement of fast searching a feature address is met, the data searching speed and precision can reach an optimal level, and the calculation pressure of a server is reduced.

This invention discloses an automated optimization design method for the flow field of a PEM electrolyzer based on multidimensional physical mapping, comprising: Step 1, continuously generating different one-dimensional flow paths based on a Hamiltonian topology search engine using depth-first search; Step 2, filling the one-dimensional flow paths into a two-dimensional flow field geometric image, and then automatically converting the two-dimensional geometric image into a three-dimensional geometric model that can be used for subsequent computational fluid dynamics simulations; Step 3, introducing a flow field management library to automatically manage and store the flow field. This invention, through a high-performance improved depth-first search algorithm, can construct millions of flow fields in a short time, which is faster than traditional design schemes. The single flow channel design eliminates reaction dead zones, significantly improving hydrogen production efficiency.

A collaborative fault handling system and method for provincial and local power grids based on multi-source data includes: a multi-source data processing unit that collects heterogeneous data from multiple sources, and forms a power grid state feature vector through normalization processing and knowledge graph construction; a topology construction unit that generates a power grid operation topology map through a depth-first search algorithm; a fault intelligent diagnosis unit that uses wavelet transform and graph theory search algorithms to locate fault nodes and uses the Newton-Raphson method to calculate the fault impact range; and a collaborative handling decision-making unit that optimizes fault handling plans through a case-based reasoning model to obtain an operation instruction sequence, and then relies on instant messaging and a workflow engine to achieve collaborative handling by provincial and local multi-level dispatching agencies. This invention, through multi-source data integration and multi-algorithm collaborative application, fully leverages the complementary value of real-time power grid operation, management, fault recording, and external environmental data compared to traditional fault diagnosis methods that rely on single data or simplified algorithms.

The application discloses a fault positioning method and system of an integrated circuit, and belongs to the technical field of integrated circuit testing and fault diagnosis. The method comprises the following steps: obtaining an initial circuit dependency mapping relationship from an integrated circuit design database, generating a potential fault propagation sequence set, and determining the matching accuracy of each sequence starting node; acquiring a preliminary fault source set by using the frequency characteristics, amplitude range and abnormal trigger time window of an abnormal signal; refining the fault source list according to the downstream abnormal count, abnormal propagation level depth and influence range boundary to calculate the influence strength value; generating a fault propagation influence chain in combination with the node influence weight; simulating the propagation path by using a depth-first search to verify the circuit stability by matching the abnormal trigger time window; and finally updating the path delay and topological structure to realize closed-loop iteration optimization. The scheme can accurately distinguish the initial fault source and the secondary propagation effect, model the dynamic dependency relationship between nodes and the signal propagation timing constraint, and improve the fault positioning precision.

The application discloses a substation secondary circuit path identification method, device, equipment and medium, and belongs to the field of power systems, the method is: obtaining the first connection relationship of each screen cabinet and each element to construct the first connection relationship matrix, determining the simplified judgment result according to the element quantity and the connection density corresponding to the screen cabinet and simplifying the first connection relationship matrix to obtain the second connection relationship matrix, and then performing bidirectional search in the second connection relationship matrix according to the positive power supply node and the negative power supply node by using a bidirectional depth-first search algorithm to obtain the secondary circuit path, so that the problem of low path identification efficiency of the substation secondary circuit in the prior art can be solved by implementing the application.

This invention discloses a method and apparatus for evaluating medical language models based on dynamic cost graph matching and inference path logic review, belonging to the interdisciplinary field of artificial intelligence and medical informatics. The proposed technical solution includes: constructing a knowledge graph; receiving the output content of the medical language model under test and parsing it into a test graph; vectorizing and optimizing the node text information of the knowledge graph and the test graph; calculating the graph edit distance between the test graph and the knowledge graph based on a graph edit distance algorithm, using dynamically calculated node replacement costs, converting it into a similarity score, normalizing it, and then calculating the local and global similarity scores between the test graph and the knowledge graph; using a depth-first search algorithm to detect logical loops, or detecting semantic coherence by calculating the embedding vector similarity of adjacent nodes on the path; and finally generating an evaluation report. This invention achieves automated, multi-dimensional, and in-depth evaluation of the output content of medical language models.

This application discloses a method and system for intelligently stripping operating circuits from a substation electrical digital model. The method includes: converting substation electrical operating circuit design drawings into a digital model of operating circuit groups based on XML; constructing a feature rule base for target functional circuit groups based on the digital model of operating circuit groups; determining the start and end points of circuits in the digital model of operating circuit groups based on the feature rule base; and traversing and filtering the digital model of operating circuit groups based on the start and end points using a depth-first search algorithm to obtain the target functional circuit groups. This application achieves automatic, fast, and accurate identification and stripping of target functional circuits from complex electrical circuits, overcoming the problems of low efficiency and error-proneness of traditional manual analysis. It has good scalability and engineering applicability, improves the intelligence level and operation and maintenance efficiency of electrical drawing search and analysis, and can be widely applied in the field of digital power grid technology.

This invention discloses a system for assisting decision-making and impact assessment of valve closure in water supply network bursts, belonging to the field of smart water management technology. It includes a network data extraction module, a loop detection module, a valve status check module, a redundant path identification module, a topology sorting module, and a conflicting path verification module. By extracting node and edge relationships from network data, an initial path set is generated using a depth-first search algorithm. Through loop detection, duplicate path filtering, valve status checks, and path truncation, the path set is progressively optimized to form an uninterrupted and unique upstream path. A topology sorting algorithm is applied to determine the path hierarchy, verifying and adjusting conflicting branches to ensure the accuracy and uniqueness of the path description. Through multi-step path optimization and hierarchical sorting, accurate tracing from the burst point to the water source and rapid location of the valve closure position are achieved, effectively assisting decision-making, assessing the impact range of the burst, and significantly improving the efficiency of emergency response and the scientific nature of water supply network management.

The application provides a DTU distribution layering method, medium and system for fast isolation of power distribution network faults, and belongs to the technical field of power distribution network fault processing.The electrical parameters are collected, principal component analysis dimension reduction is performed on the collected data to extract a fault feature vector, the fault feature vector is input into a fault identification model in which a layered communication delay optimization algorithm module based on a Floyd multi-source shortest path is embedded, a fault type label and a fault confidence score are output, a fault section boundary node pair is determined by a fault section recursive positioning algorithm based on a depth-first search, wavelet packet energy spectrum features and Hilbert-Huang transform time-frequency features are extracted to distinguish between instantaneous faults and permanent faults, and when the fault type is a permanent fault, layered isolation operation is performed according to a time priority matrix, thereby solving the technical problem of fault isolation instruction timing mismatch caused by communication link delay fluctuation in the DTU layering architecture.

The application discloses a kind of instrument design identification methods for optical surgical navigation, it is related to optical surgical navigation technical field, it includes generating source point set and the template point set of instrument;According to the distance between the distance between any two mark points of the template point set of instrument calculation first one-dimensional vector;According to the distance between any two three-dimensional coordinates of source point set calculation and constitute second one-dimensional vector;The distance difference of all data between first one-dimensional vector and second one-dimensional vector is calculated, and distance matching pair is constituted;By mapping matching the three-dimensional coordinate layout of mark point to source point set through depth-first search recursion, obtain multiple feasible candidate solutions;Optimal solution is selected from multiple feasible candidate solutions, realize the position identification of instrument in three-dimensional space.The application can realize the design of high-differentiation instrument and the rapid identification of multiple instruments under complex conditions.

This application provides a method and apparatus for cross-modal geophysical data governance, relating to the field of geophysical exploration technology. The method includes: extracting entities and relationships using a natural language processing model; clustering entity and relationship types to generate a knowledge graph ontology; mapping cross-modal geophysical data to the knowledge graph ontology; using a graph building engine to mine and reason about concepts and attributes to achieve automatic knowledge extraction and fusion; constructing a knowledge graph corresponding to the knowledge graph ontology; combining the knowledge graph with a pre-set machine learning algorithm; using a natural language processing model to parse user query requests; performing depth-first search or graph query in the knowledge graph to achieve knowledge query and analysis of cross-modal geophysical data; and based on a pre-set real-time data stream processing pipeline, when geophysical data is detected to arrive, performing a similarity comparison between the newly arriving geophysical data and the geophysical data corresponding to the current node, and performing knowledge graph evolution and maintenance, significantly improving exploration efficiency and accuracy.

The application provides a satellite interactive verification mode task planning method based on depth-first search and a double time matrix, and comprises the following steps: step 1, constructing an interactive verification task planning problem mathematical model, describing the interactive verification task planning problem, interactive verification task constraints and interactive verification task optimization targets; step 2, constructing an interactive verification task candidate window combination by using a depth-first algorithm; and step 3, solving the interactive verification task planning to obtain an interactive verification task planning result. The application satisfies the basic premise of collaborative observation from the root; can ensure that each candidate window combination is a feasible solution satisfying the basic collaborative constraints in the generation stage, greatly improves the quality of the candidate solution set and the efficiency of subsequent planning; prevents overconsumption of satellites, globally guides load balancing and improves the long-term sustainable utilization ability of space resources.

The application provides a kind of urban drainage pipe network risk rapid assessment method, belongs to the technical field of urban flood control and drainage, aims at solving the problems of existing pipe network risk assessment modeling complexity, low calculation efficiency, unable to adapt to rain and sewage mixing scene. The method first constructs a directed graph of drainage pipe network, determines the representative flow area of node and local catchment area; rain and sewage mixing points are automatically identified by reverse graph depth-first search, and the tracking and superposition of upstream non-sewage source catchment load are completed; then, based on the reverse graph traversal calculation of total catchment area of sewage node, the design flow is calculated combined with the design rainfall intensity, and finally the node risk index negatively correlated with overflow risk is quantitatively obtained. The application is based on graph theory algorithm instead of traditional hydraulic simulation, which completes the global pipe network risk assessment in seconds, without manual correction of model and online monitoring data, and is suitable for pipe network planning preliminary screening, old pipe network reconstruction and flood control emergency risk prediction.