108 results about "Traversal algorithms" patented technology

The invention relates to a brain inspired data service system and a brain inspired data service method, which are characterized in that a layered architecture is constructed, the layered architecture comprises a data node cluster deployed in a mixed manner, the data node cluster specifically comprises a core node, an acquisition node and a gateway node, and the core node, the acquisition node and the gateway node are respectively used for processing core service data, real-time edge data and cross-domain connection; the small-world connection layer realizes same-domain efficient communication through high-clustering local connection, and breaks a data island through dynamic long-range cross-domain connection; the intelligent control layer integrates a DMN control center, a collaborative state monitoring engine, a prediction analysis module and a reinforcement learning driven resource scheduler. The system initializes a topological structure through a small-world network manager, and when the communication frequency of a cross-domain node exceeds a threshold value, long-range connection is dynamically inserted to ensure that the hop count of a cross-domain path is stably not higher than a preset value. The DMN control center realizes dual-mode switching based on a system load threshold; in an idle period, data pre-cleaning, knowledge graph construction, predictive pre-fetching and resource pre-allocation are executed; and optimizing routing in combination with a graph traversal algorithm in a task period.

The invention provides an application environment and version management method and system suitable for a low-code platform, and relates to the technical field of platform management.The application environment and version management method comprises the steps that a directed dependency graph is constructed by obtaining change records, and a dependency loop is detected and intelligently decomposed through a depth-first traversal algorithm; and packaging the node clusters into micro-services based on a function relevancy model to form an acyclic directed dependency graph, constructing a version backtracking index and a difference analysis matrix to determine a change influence range, executing incremental deployment according to a topological sequence, and recording deployment information. According to the method, the problem of version management and environment dependence in a low-code platform is solved, and the application deployment efficiency and the system stability are improved.

The invention relates to the technical field of ship manufacturing, and discloses a ship block assembly man-hour matching method based on multi-modal process feature recognition. Multi-modal process data including structured process parameters, unstructured process documents and the like are collected, each modal process feature vector is obtained through feature extraction, and then a fusion feature vector is generated through a multi-modal feature fusion algorithm. And constructing a man-hour matching knowledge base according to historical assembly order data, and determining an assembly process sequence and a man-hour allocation scheme by using a dynamic matching algorithm. According to the method, a process set can be optimized through a graph traversal algorithm, real-time sensor data are analyzed to deal with abnormal fluctuation, and process compliance is verified by means of a process rule knowledge graph. According to the method, multi-modal data can be effectively fused, the man-hour matching precision is improved, the assembly process is optimized, the ship block assembly efficiency and quality are improved, and the cost is reduced.

The invention relates to the field of wisdom education, and particularly discloses a teaching strategy optimization model and grammar error early warning method based on data mining, and the method comprises the following steps: S1, obtaining original code data in a student code library in real time, and preprocessing the original code data to obtain a structured data matrix; s2, for the structured data matrix, generating a grammar parse tree through a grammar parser, positioning error nodes and extracting context features by using a node traversal algorithm, and constructing a single-error multi-dimensional feature vector; meanwhile, an error association rule base is constructed based on historical error data, a causal relationship across error types is identified, and dynamic knowledge graph data is formed. According to the technical scheme, association analysis and deep mining can be carried out on the multi-source learning data, dynamic solution suggestions for student individual errors or group generality errors are formed, and teachers are assisted to quickly adapt to dynamically changing learning requirements of the students.

The invention relates to the technical field of network security, and discloses a security vulnerability AI positioning method and system based on log files. The method comprises the following steps: firstly, analyzing user feedback describing open source component security vulnerabilities to extract fault key entity information, screening related log entries based on the fault key entity information, and constructing a vulnerability propagation graph; identifying a vulnerability triggering initial point set by using a graph traversal algorithm and a graph neural network, calling a component vulnerability case library to deduce a vulnerability utilization propagation chain and calculating a matching degree with a known open source component vulnerability utilization chain feature, and obtaining a maximum probability vulnerability utilization propagation chain and an associated vulnerability triggering initial point set; and generating a root cause positioning report, and updating the knowledge base or model training data according to a user verification result. According to the method, the initial vulnerability point and the complete vulnerability propagation chain of the security vulnerability of the open source component can be accurately and efficiently positioned, and the positioning accuracy and timeliness are improved.

The invention discloses a code change influence analysis method and device, equipment and a storage medium, and relates to the technical field of software, the method comprises the following steps: performing grammar analysis on a multi-programming language code to obtain a back-end abstract syntax tree and a front-end abstract syntax tree, and converting the back-end abstract syntax tree and the front-end abstract syntax tree into a uniform syntax tree structure through a front-end and back-end calling mapping chain; a cross-language dependency graph is constructed according to the unified syntax tree structure, the cross-language dependency graph is composed of nodes and edges, the nodes represent code entities, and the edges represent dependency relations; and when the code change of the bank business is detected, traversing the cross-language dependency graph through a graph traversal algorithm to obtain a code change influence result. Due to the fact that the back-end abstract syntax tree and the front-end abstract syntax tree of the multi-programming language codes are constructed and connected in series, the perfect cross-language dependency graph is constructed, the front-end link and the rear-end link are connected, cross-language tracking can be achieved when the codes of the banking business are changed, and the influence of code change can be accurately analyzed.

The invention provides a two-hop incremental interface consistency verification method and system based on a knowledge graph, and the method comprises the steps: 1, carrying out the language analysis of a modified source file, and extracting an interface entity; 2, mapping the interface entity into a language-independent meta-model, and writing the language-independent meta-model into a knowledge graph; 3, executing a two-hop breadth-first traversal algorithm by taking a modified node in the knowledge graph as a starting point to obtain an affected sub-graph; 4, a hot-pluggable rule set is operated on the affected subgraph for verification, the rule set comprises a parameter number matching rule, a type compatibility rule, a version number increasing rule and a field deletion forbidding rule, and if verification is illegal, an error report is generated, and a blocking instruction is output; and if no violation exists in the verification, merging the affected sub-graphs back to the knowledge graph cache. According to the method and the device, online faults caused by field missing during operation are avoided, and the influence of back-end change on the front end is automatically detected and blocked.

The embodiment of the invention provides an authority control method and device based on fine granularity, and the method comprises the steps: carrying out the node relation extraction of a mapping database, obtaining a role node and a product node, and introducing a user node and a context node; the method comprises the following steps: constructing a hyperedge structure, performing hyperedge linking on role nodes, product nodes, user nodes and service context nodes, determining a corresponding hyperedge relationship, performing dynamic weight endowing on the hyperedge relationship according to a time decay factor and a context risk coefficient, determining a dynamic graph structure, and constructing a directed acyclic graph based on the role inheritance relationship. Fusing the dynamic graph structure and the directed acyclic graph according to a graph algorithm, and determining a corresponding product permission layer graph database; the method comprises the steps of receiving a user operation instruction, performing context-aware query based on the operation instruction according to a graph traversal algorithm, determining a user permission, and performing permission control on a user according to the user permission. The method can improve the efficiency and the refinement degree of permission allocation.

The invention discloses a multi-source property right data verification method, and relates to the technical field of data processing. The method comprises the following steps: acquiring property right data from different data sources, and converting the property right data into a unified field according to semantics of the property right data and a preset mapping rule; after the knowledge graph is constructed based on the uniform field, the business rule vectors are coded into node attributes of the knowledge graph; and traversing nodes and edges in the knowledge graph through a preset graph traversal algorithm, and verifying the property right data according to the business rule vector to obtain a verification result. According to the method, the association relationship between the knowledge graph integration entities is constructed, and the service rule is encoded into the knowledge graph for verification, so that verification is not limited to single node data any more, cross-node verification can be performed in combination with the association information, and the verification accuracy is improved.

The invention relates to the technical field of industrial data management, in particular to a supply chain data real-time integration processing method and system based on multi-source heterogeneous data, and the method comprises the steps: obtaining an external compliance data document, calling a document layout analysis model based on a multi-modal converter, extracting a text semantic vector, fusing the text semantic vector with a two-dimensional space coordinate feature to generate a composite index key, and carrying out the real-time integration processing of the supply chain data. Executing clustering analysis to recognize the text blocks and generating structured metadata; carrying out discretization processing on the business transaction data flow, and constructing an associated database with production environment and logistics data as attributes; executing cross-modal entity alignment by using the structured metadata, and establishing a bidirectional pointer link between the unstructured document index and the associated database; receiving a query vector, executing a recursive traversal algorithm based on a bidirectional pointer link, calculating a cascade influence probability as a correlation sorting score, and outputting a retrieval result; through multi-modal feature fusion and cross-modal entity alignment, deep integration and risk linkage retrieval of supply chain heterogeneous data are realized.

The invention provides a digital main line processing method based on an industrial data atlas, a medium and a system, and belongs to the technical field of the industrial data atlas. Unified access of cross-system data is realized by constructing a multi-source data acquisition adapter, cleaning and standardization processing are performed on heterogeneous data, an integrated data set is constructed, and the data collection efficiency is improved. Data entities are abstracted as nodes, cross-system association relationships are abstracted as edges to construct an industrial data graph, a graph index optimization strategy and a hierarchical storage architecture are adopted to improve cross-system query performance, a graph adaptive evolution model is utilized to realize dynamic adjustment of a graph structure, and a cross-system deep association analysis function is realized through a graph traversal algorithm. And an access control and data security mechanism is established to complete system protection, so that the technical problem that the industrial data processing system is difficult to realize cross-system deep correlation analysis is solved.

The invention discloses a network fault prediction method, and relates to the technical field of fault prediction. The method comprises the following steps: constructing a cross-level semantic topology model; screening a key link by using a node importance algorithm and extracting a structural fingerprint vector; calculating the deviation degree between the current link and the structure fingerprint vector, and judging that the structure is abnormal if the deviation degree is smaller than a threshold value; constructing an anomaly propagation rule base according to historical faults and operation and maintenance data; when a plurality of structure anomalies appear at the same time, the conflict resolution algorithm determines an anomaly dominant factor; potential signals are collected according to the abnormal dominant factors, weights are given according to a rule base, and weighting is carried out to obtain comprehensive potential signals; based on this, a fault propagation path is constructed, and a path weight is calculated by using a Pearch ranking algorithm; a fault chain is rehearsed through a depth-first search graph traversal algorithm; and verifying the rehearsal chain by using a preset test statistic circumstantial evidence to obtain a fault prediction result. According to the invention, on the basis of the fault prediction result, cross-level network fault prediction in network propagation is realized.

The invention discloses a software supply chain risk detection method and system, a medium and a product, and relates to the technical field of risk detection. The method comprises the following steps: acquiring multi-source heterogeneous data of a software supply chain, and constructing the multi-source heterogeneous data into a multi-dimensional software supply chain relation graph; querying nodes and attributes associated with the target asset node based on the multi-dimensional software supply chain relation graph to extract risk features; obtaining an initial risk score of a vulnerability node associated with the target asset node from the public vulnerability library, calculating the shortest propagation path depth between the vulnerability node and the target asset node by using a graph traversal algorithm, and adjusting the initial risk score in combination with code reachability analysis to obtain a corrected technical risk feature; and calculating a comprehensive risk score based on the corrected technical risk characteristics, and executing automatic safety examination and approval, interception or manual reexamination operation. By implementing the technical scheme, the software supply chain risk can be comprehensively and accurately detected.

The invention discloses an electric energy meter and terminal logic reliability verification method and system, and relates to the technical field of electric power, and the method comprises the steps: constructing a software state machine model of an electric energy meter or a terminal; generating an optimal verification traversal sequence; converting the traversal sequence into a verification scene instruction set; running the verification scene and collecting whole-course state change and resource use data; and judging and generating a structured inspection report. According to the method, the formal state machine model of the electric energy meter and the terminal software is constructed, and the verification sequence with complete coverage is automatically generated based on the optimal traversal algorithm, so that the logic coverage rate is remarkably increased, state change, service data and resource information can be collected in real time, deep defects such as deadlock, data damage and migration abnormity can be effectively identified, and the method is suitable for popularization and application. And a quantized structured inspection report is generated based on the multi-dimensional rule set, so that the verification process is automatic, reproducible and quantized, and the verification efficiency and accuracy of the logic reliability of the electric energy meter and the terminal software are integrally improved.

The invention discloses a front-end project performance comprehensive optimization method based on artificial intelligence, and the optimization method comprises the steps: carrying out the comprehensive scanning of a project directory through employing a depth-first traversal algorithm, and collecting project data; reading data from the temporary database, distributing the data to each sub-module and unit for special analysis, and storing the data in an analysis result database; reading optimization suggestions from the analysis result database, and automatically executing the optimization suggestions according to preset priorities and rules; performing special optimization on the large project and the migration project; and reading data from the analysis result database and the optimized project database, and displaying the data in a visual form. The defects that in the prior art, manual analysis is low in efficiency and prone to omission, and a tool cannot automatically recognize the code logic problem are overcome, and automatic detection and analysis of the code logic problem are achieved.

A content channel generation device includes: a splitting circuit for generating resource units according to resource assignments; a resource unit assignment circuit for generating a full binary tree according to the resource units; a node computing circuit for generating a minimum full binary tree according to the full binary tree; a load balance circuit for generating user field numbers corresponding to content channels according to the minimum full binary tree and a load balance function; a merging circuit for generating a traversal result of the minimum full binary tree according to a traversal algorithm, and for generating a merged traversal result according to the traversal result; and a common field generation circuit for generating a resource assignment indicator according to the merged traversal result to generate a common field.

A three-dimensional measurement method based on spatial coding includes the following steps: S1. Designing a spatially coded projection pattern in the form of a three-dimensional honeycomb structure and saving a set of intersection coding results; S2. Calibrating the intrinsic and extrinsic parameters of the camera and projector in a structured light system, projecting the spatially coded projection pattern using the projector, and synchronously capturing images using the camera; S3. Extracting an image skeleton from the captured image, extracting intersections based on the image skeleton, and classifying the intersections into two categories of intersection sets; S4. Drawing a bipartite graph based on the captured image and the intersection set using a connecting line traversal algorithm, and calculating an intersection neighborhood decoding result set based on the bipartite graph; S5. Using a matching algorithm, calculating an intersection pairing set based on the intersection neighborhood decoding result set and the intersection coding result set; and performing three-dimensional measurement of the intersection pairing set using a triangulation method, combined with the intrinsic and extrinsic parameters of the camera and projector, to generate a point cloud. This method solves the problem of non-uniform intersections caused by distortion in traditional grid coding and accelerates decoding speed.

The application relates to the technical field of software engineering, in particular to an iJTAG network module wiring design method, which comprises the following steps: analyzing network structure information described in an ICL text; obtaining quantity information and ID information of modules in the network structure, and recording input and output ports of the whole network as preset modules with ID Port; obtaining interconnection constraint information of each module in the network structure, and outputting a position information table according to the interconnection constraint information; encoding position coordinates of each module and the preset modules in the network structure according to the position information table, and numbering each module and the preset modules in the network structure; and automatically wiring according to the interconnection constraint information and the position coordinate coding; according to the traversal algorithm principle of a directed graph, in combination with ICL text analysis, information of the modules and connection relationships among the modules are extracted, automatic wiring of each module of the iJTAG network is realized, and efficiency is improved.

The invention discloses a large model lightweight reasoning method and device, computer equipment and a storage medium. The method comprises the steps that a target large model is unfolded into a computational graph, and a semantic path dependency graph is constructed based on intermediate representation; defining a semantic contribution degree index, and calculating the semantic influence degree of each node in the semantic path dependency graph on final output; screening a low-influence path according to a graph traversal algorithm, and performing path pruning in combination with structure limitation to obtain a pruned model; and carrying out structure completion on the pruned model, and carrying out semantic alignment distillation by taking the original model as a teacher model to obtain a lightweight model. The embodiment of the invention relates to the field of artificial intelligence model reasoning optimization, and solves the problems that a pruning method in the prior art depends on structural information, lacks semantic perception and is easy to lose performance. The semantic graph is constructed in the middle presentation layer, task related paths are identified, redundant branches are cut off, the reasoning process is remarkably accelerated on the premise that the precision of the model is kept, and the deployment efficiency is improved.

The invention relates to the technical field of data analysis, in particular to a code vulnerability reachability analysis method based on a vulnerability database, which comprises the following steps: acquiring keywords in each vulnerability code snippet in the vulnerability database and keywords of each node code extracted by a CPG code attribute graph; extracting a node feature vector of each node in the CPG code attribute graph and a vulnerability feature vector of each vulnerability code snippet, obtaining an adjacency anomaly degree and vulnerability triggering performance of each node, and obtaining a vulnerability confidence coefficient of each node in combination with a difference degree of vulnerability triggering performance between different nodes in the CPG code attribute graph; identifying vulnerability nodes in the CPG code attribute graph; and performing reachable path identification on vulnerability nodes in the CPG code attribute graph by adopting a DFS depth-first traversal algorithm to obtain a code vulnerability reachability analysis result. According to the method, the code vulnerability reachability analysis accuracy can be improved.

The invention relates to the technical field of audio loading, and discloses a USB media file loading method and system, a storage medium and equipment, and the method comprises the steps: detecting equipment connection and initializing a pre-scanning process when USB storage equipment is inserted into the system; the method comprises the following steps: quickly pre-scanning a USB storage device, acquiring basic information of media files through a lightweight file system traversal algorithm, and counting the number and types of the media files; based on a pre-scanning result and historical loading data, establishing a time prediction model to estimate loading time, and formulating a loading priority strategy; in the loading process, multi-level progress information including the overall progress, the classification progress and the real-time state is displayed to the user, and dynamically updated remaining time estimation is provided; according to the method, the loading of the media file is executed according to the loading priority strategy, and result verification and cache management are performed after loading is completed, so that intelligent pre-scanning and optimized loading of the USB media file are realized, and the practicability and user satisfaction of the system are improved.

The application discloses a service migration method and system considering reputation and fault-tolerant mechanism, and relates to the field of service migration in a mobile edge environment.The method comprises the following steps: obtaining a starting edge node and a target migration node corresponding to a service, and calculating the total reputation score of the edge nodes in the edge node set; screening the edge nodes based on the total reputation score and the edge node reputation threshold, constructing a path network topology graph, obtaining a migration path set by using a depth-first traversal algorithm, and screening a candidate path set; evaluating the resource redundancy performance of each candidate path and screening a candidate reliable path set; implementing a fault-tolerant redundancy strategy on each candidate reliable path, establishing a fault-tolerant feedback adjustment mechanism, and adjusting the fault-tolerant strategy according to the feedback result; calculating the transmission delay of each candidate reliable path, and selecting the candidate reliable path with the highest comprehensive score as the service migration path.The application effectively improves the stability, reliability and efficiency of the service migration process.

The invention discloses an electric power drawing connection relation extraction method and device based on a graph structure and a storage medium, and relates to the technical field of image processing methods. The method comprises the following steps: detecting non-text layer elements of an electric power drawing, generating element objects of equipment primitives, equipment frames and intersection points, and classifying the intersection points; processing the electric power drawing to obtain a skeletonized binary image, and then performing connected domain segmentation to extract a connecting line object; according to jump point splicing judgment, dynamic splicing is conducted on the connecting line objects, and the incidence relation between the element objects is established through the spliced connecting lines; and establishing an index list pointing to directly connected objects for each element object according to the incidence relation, constructing a topological relation of the whole electric power drawing, and then extracting a required end-to-end connection relation by adopting a depth-first traversal algorithm of the drawing. According to the method, the topological relation of the non-text layer can be automatically and accurately extracted from the electric power drawing.

This invention relates to the field of equipment maintenance and scheduling technology, specifically to an equipment fault reporting and management system, comprising: a dependency identification and modeling module, a fault status analysis module, a task priority evaluation module, a work order scheduling generation module, and a resource scheduling execution module. In this invention, a multi-level dependency topology between equipment is constructed using a directed graph traversal algorithm; the triggering relationship between physical connections and work processes is quantitatively analyzed; a classification and labeling model is established using dynamic parameters such as performance degradation rate; scalar superposition calculation is used to fuse the influence range and dependency factors; a priority scoring matrix is ​​dynamically generated; and a sorting algorithm is used to optimize the task queue structure, forming a data-driven maintenance decision-making mechanism. This improves fault location accuracy, reduces response delays caused by manual intervention, avoids maintenance lags in critical node equipment, optimizes resource allocation efficiency, strengthens the synergy between fault handling and the production system, and supports the formulation of preventative maintenance strategies.

The invention discloses a mass defense and mass governance efficiency optimization method based on big data analysis, and relates to the technical field of public security big data analysis, and the method comprises the steps: matching continuously updated real-time event data as a seed node in a mass defense and mass governance dynamic affair graph, deducing a high-probability event chain set through a graph traversal algorithm, and carrying out the optimization of the mass defense and mass governance efficiency; performing graph topological structure analysis on the high-probability event chain set, and identifying an intervention node list; and performing matching calculation on the ability portraits corresponding to the intervention strategy task set and the natural community set, assigning the intervention strategy task to the natural community with the highest matching degree for execution, and collecting execution feedback data to update the personnel cooperation relationship network map. According to the method, the corresponding capability portrait is created for the natural community set, so that intelligent grouping and efficiency quantitative evaluation of mass defense and mass treatment power are realized, distribution and utilization of human resources are optimized, and team cooperation capability and task execution efficiency are enhanced.

The invention discloses a logical operation method based on depth-first traversal and stack recursion, and belongs to the technical field of computer logical operation and data processing. The method aims at solving the problems that in the prior art, when a complex nested logic expression is processed, operator priority judgment is complex, short circuit evaluation is difficult to achieve, and code maintainability is poor. The core of the method is that firstly, a nested logic expression to be calculated is abstracted into a tree-shaped or nested array data structure; secondly, a depth-first traversal algorithm is adopted to conduct recursive scanning on the data structure, and in the traversal process, encountered logic operators and basic judgment conditions (calculation factors) or intermediate calculation results of sub-expressions are sequentially pressed into a main stack according to the traversal sequence; when traversal of one sub-expression is completed, an actuator module is automatically triggered; and the executor module pops up a logic operator of the current action range from the main stack.

The application belongs to the technical field of distributed system optimization and scheduling, and particularly relates to a distributed parallel training method of a deep neural network in a dynamic computing environment, comprising: determining a model splitting scheme by minimizing an actual convergence time of an asynchronous pipeline, and distributing each model slice corresponding to the splitting scheme to a corresponding device node, wherein the actual convergence time is a product of an upper limit of an iteration number corresponding to a preset convergence error and an optimal running time of the pipeline required for a single iteration; each device node is configured with a trained lightweight random forest model for evaluating the interference influence of an additional load located at the device node on the training efficiency of a model slice located at the device node. After starting training, interference coefficients corresponding to the interference influence obtained by the random forest models on each device node are obtained in real time, a new splitting scheme is obtained through model search space pruning and traversal algorithms, and efficient training is realized through layer migration.

The application provides a point cloud segmentation method, device and equipment of an angiogram and a medium. The method comprises the following steps: based on the position of each point cloud on the vessel centerline in the vessel binary segmentation image, a plurality of candidate paths of the vessel centerline are determined by using a depth-first traversal algorithm; based on the direction vector of each candidate path in the plurality of candidate paths and a preset reference direction vector, a candidate direction feature list is constructed; for each point cloud, based on the node type corresponding to the point cloud and the candidate direction feature list, the direction feature corresponding to the point cloud is determined, and the position coordinates of the point cloud and the direction feature corresponding to the point cloud are spliced to obtain the point cloud feature of the point cloud; finally, the point cloud feature of the point cloud is input into a pre-trained point cloud segmentation model to determine the point cloud segmentation result of the point cloud in the vessel centerline. Through the method and the device, the segmentation accuracy of the point cloud segmentation network for the vessel image is improved.

The application provides a method for generating self-consistent text based on specific structure and text content and related equipment, and relates to the technical field of natural language processing. A tree structure node set containing hierarchical relationship is constructed through hierarchical identification of a text outline; initial context information is constructed according to obtained knowledge base text content; a recursive traversal algorithm is used to traverse the tree structure node set, and the following is executed at the current node: structured prompt words are generated according to the encapsulated data transmission object, the hierarchical relationship of the current tree structure node, the initial context information and the obtained generation control parameters; a large model interface is called to generate corresponding text segments based on the structured prompt words; at the same time, the current context information including the initial context information is encapsulated into the data transmission object and delivered to all child nodes of the current tree structure node; each generated text segment is received, and each text segment is assembled into a self-consistent target text, so that global structure control and content self-consistency are realized.

The present application belongs to but is not limited to the technical field of shale gas production, and particularly relates to a method and system for ontology graph construction and abnormal cause-effect chain tracing, comprising: S1, well, pry, process, pressure difference, alarm, operation event object and relationship mode; S2, cause-effect chain coding: forming a calculable path of 'upstream equipment-process-downstream abnormality'; S3, realizing bidirectional linkage of ontology graph and detection result. The ontology knowledge graph of different business scenarios in the field of shale gas is constructed, and the well, pry, process, sensor entity and their relationships are defined; when the abnormal detection model outputs the result, the result is mapped to the graph; through graph query or graph traversal algorithm, the upstream and downstream associated entities of the abnormal node are automatically traced, and natural language explanation is generated; an interface supporting semantic query is provided, and the user is allowed to ask questions in an exploratory manner.