1423 results about "Tree structure" patented technology

The invention discloses a time sequence knowledge graph reasoning method based on a large language model, which comprises the following steps of: performing vectorization expression on query entities and relationships by utilizing an embedded model, and generating vectors containing structural features and semantic information in combination with adjacent entities, relationships and time information; a candidate entity set most relevant to query is screened out from the large-scale entity set by calculating the conditional probability; constructing an event evolution tree, and performing multi-hop sampling on adjacent nodes of a query entity and a candidate entity in a time window to generate a tree structure capable of completely reflecting a historical event evolution path; the method comprises the following steps: designing a structured prompt template, and performing instruction fine tuning on a pre-trained large language model by adopting an LoRA (Low Rank fine tuning technology), so that the model better follows a task instruction to generate a reasoning result. And efficient and accurate time sequence knowledge graph reasoning is realized.

The invention discloses an integrated verification and test system and method for complex rules of a substation monitoring system, and the system comprises a rule editing module which provides a visual interface to support a user to edit the complex rules containing various types of variables and time sequence constraints; the analysis and verification module is used for performing grammar, variable conflict and business compliance multi-level verification on the rules; the intelligent test case generation module is used for automatically generating test cases covering normal, boundary and abnormal conditions based on the rule tree structure; the simulation test interface module converts the use case into a standard test script, submits the standard test script to a simulation tool for execution, and outputs the standard test script to a monitoring system through protocol conversion; the result analysis module is used for comparing an execution result with an expected result and generating a structured test report; according to the invention, full-process automation of rule verification and testing is realized, the verification efficiency is remarkably improved, and the test requirements of various transformer substation business scenes are met.

The invention discloses an intelligent crawler generation method and system based on a large language model and an MCP protocol, belongs to the technical field of network data collection, and solves the problem that the capability of LLM in dynamic webpage analysis and anti-crawling strategy generation links cannot be fully exerted due to the fact that LLM and browser interaction protocols cannot be effectively integrated in the prior art. The method comprises the steps of analyzing an acquisition demand based on a large language model and generating a standardized demand description document, realizing interaction between the large language model and a browser based on an MCP protocol, analyzing a page complete DOM tree structure through a crawler script generation system, and performing quality verification and intelligent repair on a generated crawler script. According to the method, the complete DOM tree and the dynamic data rendered by the browser are obtained through the MCP, and the large language model can be called to automatically analyze the element positioning strategy, so that the collection script is adaptively generated, and high efficiency, intelligence and automation of webpage data collection are ensured.

The embodiment of the invention provides a dynamic page rendering method and system based on a front-end framework, electronic equipment and a storage medium, and belongs to the technical field of page rendering. According to the scheme, rule expansion processing is conducted on JSON structure specifications, a metadata structure model is obtained, and the metadata structure model is used for defining page rendering rules; obtaining JSON configuration data, and performing data preprocessing on the JSON configuration data based on the metadata structure model to obtain structure data; dynamic structure analysis is conducted on the structure data through an analysis engine, a virtual document object model tree structure is obtained, and the analysis engine adopts a layered architecture; and performing difference rendering according to the virtual document object model tree structure to obtain a target page. According to the method, seamless connection between a low-code platform and professional development can be realized, the development efficiency is improved, and the page rendering dynamic capability is enhanced.

In one implementation, point cloud data for a point cloud is decoded. The decoder obtains features representing voxels in a tree structure, where feature for a current voxel is representative of at least a set of voxels that are still to be reconstructed. The decoder then determines an occupancy probability of the current voxel based on the feature, and decodes occupancy information of voxels in the tree structure, where whether a current voxel is occupied or not is decoded based on the occupancy probability for the current voxel. The point cloud can be reconstructed based on the occupancy information. On the encoder side, the feature for the current voxel is obtained from the voxels that are still to be encoded and encoded into a bitstream.

According to the long-tail human movement prediction method based on adaptive hierarchical learning, coarse-grained semantic grouping is introduced through a hierarchical tree structure based on the Maslow human motivation theory, and the optimization process is rebalanced in a framework-independent mode. Firstly, thinking chain cues are designed based on the Maslow human motivation theory, a hierarchical structure for city customization is constructed by applying a large language model, and knowledge in human mobile data is fully developed through hierarchical learning. Secondly, exploring hierarchical position prediction through Gumbel interference and adaptive weight, so as to fully capture complex space-time semantics; wherein Gumbel interference is used for rebalancing learning of head and tail positions, adaptive weight performs node-level adjustment on head categories and tail categories in each layer, and these components effectively promote exploration of mobility knowledge. The invention further comprises a method adaptive to the advanced mobile prediction algorithm, and the effectiveness and applicability of other methods in long-tail mobile data are improved by embedding the adaptive hierarchical learning loss into other mobile prediction methods.

The invention relates to a signal equipment fault diagnosis rule automatic generation method, system and equipment, and the method comprises the steps: a demand cleaning processing process: carrying out the semantic analysis of an original fault diagnosis demand of signal equipment, and generating a structured output containing a demand pseudo code and a dependency graph based on a recognition result of the demand; the demand searching process is used for constructing a demand vector and a knowledge graph; performing similarity search on the vectorized query demand to obtain similar demand nodes for a user to select a root demand, and performing deep search in the knowledge graph based on the root demand to generate a fault tree structure and fault tree data; and an intelligent rule automatic generation process: generating prompt words based on the fault tree data construction rule, and generating a signal equipment fault diagnosis rule code by using a large language model. Compared with the prior art, the method has the advantages that the signal equipment fault diagnosis rule is automatically generated, and the development efficiency is improved.

The invention discloses a question answering method based on structured document retrieval enhancement, and belongs to the technical field of artificial intelligence. The method comprises the following steps: performing structured information analysis and blocking processing on a structured document to construct a tree structure reflecting a hierarchical relationship of the document; based on a cross-document association relationship, combining the tree structures corresponding to the plurality of structured documents to form a multi-document tree structure network; and when a question request is received, generating corresponding retrieval enhancement information through the tree structure network, and inputting the retrieval enhancement information into the question and answer model to obtain answer information matched with the question request. According to the method, the multi-document tree structure network which takes the tree hierarchical relationship of the structured document as a core and fuses cross-document topic clustering and reference mapping is constructed, so that efficient retrieval enhanced questions and answers oriented to the structured document are realized, and the accuracy, context consistency and traceability of answers are remarkably improved.

A medical code allocation method based on hierarchical association and diversity enhancement comprises the following steps: S1, data preprocessing and graph construction: based on a tree hierarchical classification architecture of ICD codes, adopting a hierarchical graph model to perform visual representation on the tree hierarchical classification architecture, and constructing a co-occurrence matrix of the clinical record text and the ICD codes for the clinical record text; s2, applying a Graph-BERT graph neural network structure to perform graph structure conversion on a tree structure of an ICD code system, and learning based on an encoder structure of a graph transformer to obtain embedded representation of ICD codes; s3, performing word segmentation processing on a clinical text, inputting the processed clinical text into a bioBERT model to obtain a feature vector of the clinical text, and unifying semantic features of clinical records, hierarchical features of ICD codes and related association information between the semantic features and the hierarchical features through a multi-modal fusion mode; s4, after the final feature vector of the clinical record text is obtained, correlation enhancement prediction is performed by using a CorNet network, so that a related probability matrix is generated, a binary cross entropy loss function is expanded, the binary cross entropy loss function, hierarchical diversity loss and semantic diversity loss jointly form a diversified loss function, and the diversified loss function and a classic model are subjected to comparative analysis, so that the final feature vector of the clinical record text is obtained. Therefore, the accuracy and effectiveness of the method are verified.

The invention provides a lithium ion battery health state estimation method and system based on a dual-drive interpretable integrated model, and belongs to the field of lithium ion battery health state estimation. The problems that an existing lithium battery health state monitoring method is single in feature source, insufficient in model generalization ability and poor in interpretability are solved. According to the method, based on an incremental capacity curve and a first-order RC equivalent circuit model, IC peak value features and ohmic internal resistance features are extracted, and a multi-source health feature space is constructed in combination with voltage statistical features; an integrated learning model based on Stacking is established, three basic models of a random forest, kernel ridge regression and an interpretable enhancement machine are integrated, and collaborative optimization of model hyper-parameters is realized by adopting a tree structure-based Bayesian optimization algorithm.

The invention relates to the technical field of intelligent retrieval, in particular to an engineering knowledge base construction and deep retrieval method, which comprises the following steps of: in a knowledge base construction stage, performing knowledge level identification on an engineering knowledge document to form a multi-level tree structure taking chapter titles and corresponding contents as nodes; performing analysis processing on the heterogeneous content of each node to generate knowledge fragments; and generating embedded vectors of knowledge fragments by adopting a way of combining path embedding and content embedding, and storing association relationships among knowledge, vector data and original information to complete knowledge base construction. In the deep retrieval stage, after a user question is received, a knowledge blank question list is generated through query and rewriting, a knowledge base is retrieved through traversal of the list, the retrieval process is optimized through knowledge grouping, correlation sorting and loop termination judgment, and finally reply content subjected to traceable verification is generated and output based on existing knowledge accumulated in a circulation mode. According to the method, the reuse efficiency and the retrieval accuracy of the engineering knowledge can be improved.

The invention relates to a simulation method for a semiconductor device, electronic equipment and a computer readable storage medium. The method comprises the steps that a multi-way tree structure is constructed based on grid data of a gridded semiconductor device, the multi-way tree structure at least comprises a root node, a plurality of layers and a plurality of leaf nodes, and each leaf node represents a corresponding polyhedron in a plurality of polyhedrons in the gridded semiconductor device; in response to the determination of the first spatial position of the particle in the semiconductor device, determining a first search path from the root node to a first leaf node in the plurality of leaf nodes based on the corresponding relationship between each leaf node and the corresponding polyhedron; and in response to the particle moving from the first spatial position to a second spatial position within the semiconductor device, determining a second search path in the multi-way tree structure based on the first search path to determine a second leaf node representing the polyhedron where the second spatial position is located. According to the method, the ion implantation simulation performance is effectively improved.

The invention discloses an invalid code automatic elimination method and device, a medium and a product, and the method comprises the steps: carrying out compiling analysis processing on each program file in a to-be-processed target program item, generating a syntax tree model, and testing the compiled program file to obtain a program test result; unused variables in all the variables are identified through a syntax tree model, and uncovered code lines are positioned in combination with a test result; analyzing logic judgment conditions of uncovered code lines based on the syntax tree structure, and judging the code lines which cannot be triggered as unreachable codes; unused variables and unreachable codes in the program files are removed, new program items are obtained, and when the new program items are correctly compiled and executed, the new program items are used for replacing the target program items. Program redundancy is reduced, and execution efficiency is improved.

The invention relates to a method, a device, equipment and a medium for dynamically configuring a window control and layout, and the method comprises the following steps: firstly, obtaining and analyzing an XML configuration file to generate a data model tree of a structured window interface in a memory; then, objects are dynamically created based on a Qt reflection mechanism, attributes and signal slots are set, Qt reflection characteristics are fully utilized, object creation and attribute processing are flexible and efficient, hard coding interface elements in the compiling stage are not needed, needed controls and layouts can be dynamically generated according to a data model tree, and the dynamic nature and expandability of interface configuration are greatly enhanced; establishing a set membership tree between the controls and the layouts in the recursive traversal process to obtain a complete interface tree; and finally, performing layout calculation and rendering to generate a display interface, so that automation of interface layout is realized, interface element layout can be automatically adjusted according to a data model tree structure, and efficient dynamic configuration of window controls and layout is realized.

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 relates to the technical field of natural language processing, and discloses a question retrieval method and system, electronic equipment and a storage medium. The method comprises the steps of performing semantic understanding and decomposition processing on an original question to obtain a plurality of candidate sub-questions; constructing an initial problem tree structure by taking the original problem as a root node and the candidate sub-problems as sub-nodes; rationality scores of the child nodes are determined, and the rationality scores represent rationality of candidate sub-problems corresponding to the child nodes; determining a relevance score between the nodes, the relevance score representing a semantic repetition condition between the nodes; based on the rationality score and the relevance score, optimizing the initial problem tree structure to obtain a target problem tree structure; and performing retrieval based on the target question tree structure to obtain answer data for the original question. By means of the method, rationality and relevance evaluation can be conducted on the problem tree nodes, and architectural disassembly and semantic hierarchical management of complex problems are achieved.

The invention discloses a knowledge question-answering method and system based on a large language model and a semantic abstract. The system comprises a tree structure abstract generation subsystem which comprises a knowledge base configuration module, a file management module, a document analysis module and a knowledge block management module and is used for automatically generating tree structure hierarchical knowledge blocks for large manual documents or multi-chapter manual documents; the dual-channel retrieval engine subsystem comprises a question rewriting module, a semantic abstract retrieval module, a detail knowledge block retrieval module, a father-son retrieval module and a prompt word construction module, and all the modules work cooperatively to ensure that semantic abstract knowledge blocks and detail knowledge blocks related to the question of the user are retrieved. According to the method, by introducing the semantic abstract based on the tree structure and the two-channel retrieval, perception of global knowledge and accurate extraction of local fine-grained knowledge can be achieved at the same time, and then the ability of a knowledge base question-answering system in processing the general and inductive problems is improved.

The invention relates to a query optimization method and device based on agent planning, electronic equipment and a medium. The method comprises the following steps: pre-retrieving a target tree structure index based on a user query request to obtain a pre-retrieval result set; generating a retrieval-reasoning double-stage directed acyclic graph task chain comprising a task type, a retrieval / reasoning target and a dependency relationship; executing each task according to a topological sequence, and obtaining a target text fragment through query rewriting and expansion; and performing multi-hop logical reasoning in combination with the task chain and the target text fragment, and outputting a final answer. Therefore, dynamic task planning of environment perception is carried out by constructing a retrieval-reasoning dual-stage directed acyclic graph task chain and combining a knowledge base tree structure index; the problems that when an existing retrieval enhancement generation system processes a multi-hop question and answer task, logic association understanding ability among retrieval fragments is insufficient, semantic matching precision is low, and a reasoning path is prone to deviation are solved, and the retrieval recall rate and the answer accuracy under a multi-hop question and answer scene are improved.

The invention discloses a multi-language data analysis-oriented extensible system, method, equipment and medium, and relates to the technical field of multi-language analysis, the multi-language data analysis-oriented extensible system comprises a grammar analysis module used for analyzing a query language and generating a language-specific syntax tree structure after analysis; the grammar adaptation module is used for converting a language-specific grammar tree structure into an abstract grammar tree AST in a uniform format; the abstract syntax tree processing module injects a permission control strategy, a field desensitization rule and an alarm exception expression into the AST; the business processing module is used for executing business-related rule check and label injection; the query plan generation module is used for constructing a logic query path and a corresponding distributed execution scheme; and the task scheduling module issues the distributed execution scheme to the corresponding execution node. According to the method, by constructing a unified multi-language grammar analysis framework and a standardized abstract syntax tree AST representation mechanism, compatibility and fusion of multiple query languages such as SQL, SPL and natural language are achieved.

The invention discloses a complex table question-answering method based on a tree structure, electronic equipment and a medium, and the method comprises the following steps: responding to header information of a complex table, and outputting a header tree structure by a large language model; decomposing the question into a plurality of keywords through a large language model, and aligning the keywords with the header tree structure to obtain a keyword-tree structure; and in response to the keyword-tree structure, guiding the large language model to carry out iterative reasoning through a React-Style prompt method to retrieve from the complex table, and outputting an answer. According to the method, the multi-level titles of the table are organized into the tree structure, so that the large language model can more clearly understand the hierarchical relationship of the table, and related information can be more accurately positioned when questions are answered.

The invention belongs to the technical field of data processing, and particularly relates to a fingerprint generation method of a virtual evaluation model based on Hash operation, which comprises the following steps of: firstly, constructing a dependency tree by taking a main model file specified by a user as a root node, and initializing an access record table; establishing a static keyword protection area containing a core parameter rule base, scanning a dynamic file operated by a user, and comparing parameter definitions to generate an early warning; reading the binary data of the current node file, and generating a character string through SHA-256 after standardization; recursively processing the sub-nodes to obtain a node tree hash value, sorting the sub-nodes, splicing the sub-nodes according to a fixed format, and generating a character string through SHA-256 operation; then, a current node standardized path is spliced and generated through SHA-256 operation; and finally, by taking the root node as a starting point and the DFS as a sequential serialization tree structure, executing SHA-256 operation after adding a global collision salt value, and outputting a global unique fingerprint of the model. The problems of poor stability, low efficiency and high generation risk in a model fingerprint generation technology in the prior art can be solved.

The invention provides an elevator part full-period traceability management method and system based on a block chain, and the method comprises the steps: firstly collecting working condition time sequence data and metal fatigue crack ultrasonic signals during the operation of an elevator, extracting damage quantitative feature data from the ultrasonic signals, and then, carrying out the traceability of the elevator part; fusing the two types of data in a timestamp alignment mode to construct an elevator component health index model; then performing block processing on the original data and generating block hash values, organizing the hash values into a tree structure, only uploading the root node hash value to the block chain, and storing the original data in an under-chain distributed system; the integrity of data under the chain is verified through a zero-knowledge proof technology, and when verification is passed and management conditions are met, full-life-cycle traceability management of elevator components from production to scrapping is achieved in combination with a health index model and a block chain system. According to the method, the accuracy of elevator part health state evaluation and the non-tampering property of the traceability data are improved.

The invention discloses an automatic verification excitation generation method based on a backtracking thinking tree, and the method comprises the steps: constructing a backtracking thinking tree frame based on a self-feedback mechanism based on a thinking tree for a to-be-verified processor function; under the backtracking thinking tree framework, decoupling a to-be-verified function from top to bottom through a large language model, and recursively decomposing the whole to-be-verified function into function points capable of being independently verified layer by layer through a tree structure; according to each function point, determining a normal function and a boundary of each function point, and for each function point, generating verification excitation layer by layer in a tree structure; after the verification excitation is generated, self-verification and self-backtracking are carried out layer by layer through a tree structure, and finally, the generated verification excitation is executed on the processor design to verify the correctness of the processor function. According to the method and the system, the function verification efficiency and the verification coverage rate of the processor are remarkably improved.

The invention discloses a user risk coefficient calculation process visualization method and system. The method comprises the following steps: acquiring user behavior data, and constructing a risk assessment dimension system; determining node types of non-leaf nodes, and constructing a rule tree structure; performing risk assessment on behavior characteristics of the user behavior data by using the risk prediction model, and extracting risk factors; analyzing the risk factors by using an SHAP model, determining feature influence relation data and a high-risk rule combination between the risk factors, and filling non-leaf nodes with non-leaf node attributes; determining node weights of non-leaf nodes to update attributes of the non-leaf nodes; based on leaf node attributes and updated non-leaf node attributes, breadth-first traversal is carried out on the rule tree structure, and a risk scoring result of a traversal path is calculated by adopting a bottom-up backtracking mechanism; and carrying out visual display on the risk scoring result of the rule tree structure and the traversal path. The risk identification accuracy can be improved.

The invention discloses a graphical interface automatic control code generation method based on a large model agent, which comprises the following steps of: firstly, generating a task execution track through interaction between a ReAct agent based on a large language model and a graphical interface environment, and translating a hard coding action in the track into a soft coding action based on a semantic positioning page element; constructing a track library of a tree structure; then, on the basis of information in the trajectory library, a retrieval enhancement mechanism is adopted to generate an RPA function capable of being independently executed, and the RPA function is synthesized on the basis of soft coding actions and is automatically injected into robustness control logic; then executing the RPA function, if execution fails, triggering breakpoint analysis, and optimizing the RPA function through a mixed trajectory; and finally, testing the generated RPA function, and selecting to execute the RPA code or back to the ReAct agent for execution according to a verification result. According to the method, an automatic generation process from an intelligent agent interaction track to a robust and reusable RPA function is realized.

The invention provides a quantum measurement and control system supporting global feedback. The quantum measurement and control system comprises a plurality of measurement and control devices which are connected in a tree structure. The measurement and control equipment in the tree structure comprises feedback board cards and a control chip, the feedback board card located at a root node obtains board card configuration parameters through a first transmission port, and the feedback board card located at a child node receives the board card configuration parameters from a second transmission port of the feedback board card of an upper-level node through a second transmission port; the feedback board card is used for sending a feedback signal to the control chip based on the board card configuration parameters and generating board card configuration parameters associated with the child nodes; the control chip is used for responding to the feedback signal to generate a regulation and control waveform signal of the quantum bit, providing the regulation and control waveform signal to the quantum computer, receiving a quantum state signal fed back by the quantum computer, processing the quantum state signal and providing a processing result to the feedback board card; and the feedback board card is also used for receiving a processing result provided by the control chip and a processing result provided by the measurement and control equipment of the next node.

The invention discloses an SQL (Structured Query Language) statement review method, system and equipment based on a large model and a storage medium, which are applied to the technical field of SQL statement review, after a to-be-reviewed structured query language statement is obtained, the to-be-reviewed structured query language statement is reviewed according to the type of a to-be-reviewed structured query language statement database; the method comprises the following steps: selecting a corresponding analysis tool to analyze a to-be-audited structured query language statement to obtain a syntax tree structure, extracting a table object dependency graph on the basis of the syntax tree structure, and forming an examination cue word by utilizing a constructed multi-dimensional cue word framework and combining the table object dependency graph and metadata. The review prompt words are input into the preset large model for risk identification, the review result is obtained, semantic analysis of context awareness is achieved, according to the method, after deep semantic extraction is conducted on the SQL statements, the large model is used for logical reasoning and identification of potential logic defects, and the review accuracy is effectively improved.