752 results about "Tree architecture" patented technology

A system for adaptively caching network communication protocols enhances efficiency across heterogeneous device environments through a multi-level cache architecture with device-capability-based tiers. The system collects endpoint telemetry data including device capabilities and operational constraints to classify endpoints and generate context-aware protocol variants optimized for specific device types. Protocol optimization opportunities are determined through structural analysis of message patterns and state transitions. The system performs protocol deduplication by identifying functionally equivalent variants and maintaining canonical representations to reduce cache redundancy. Cache synchronization across distributed nodes uses enhanced Merkle tree structures with protocol normalization processing. The system predicts communication needs based on historical patterns, network context, and endpoint constraints, enabling proactive cache management tailored to device capabilities. Integration with event-driven data communication systems enables seamless protocol selection and translation while maintaining compatibility between diverse endpoint types, from high-performance servers to resource-constrained IoT devices.

The invention discloses an intelligent document analysis method and system, the method is executed by the intelligent document analysis system, and the method comprises the following steps: carrying out layout analysis on a PDF page by adopting a deep learning model; merging the block list from bottom to top by adopting a recursive algorithm; carrying out balance optimization on the binary tree structure; and outputting a result of the processed binary tree structure by adopting a preorder traversal mode. Layout analysis is carried out by adopting a deep learning model, various complex typesetting formats such as multi-column layout, image-text mixed typesetting, tables, lists and the like can be effectively identified and processed, and semantically continuous text blocks are ensured to keep continuity in a tree structure through a tree structure optimization module; a global semantic error correction module is added to carry out global document semantic representation learning and carry out adaptive adjustment and error correction on a preliminary structure, so that deep ambiguity is eliminated, logic errors are repaired, and the consistency of a final analysis result and human reading logic on the semantic level is maximized.

The invention provides a distributed storage method based on source code semantic partitioning, and particularly relates to the technical field of cloud data distributed storage. The method comprises the steps of performing semantic partitioning on a source code, and segmenting the source code into a plurality of semantic blocks according to dimensions such as functional semantics, an abstract syntax tree structure, author information and version information; generating metadata containing information such as grammar type tags, file paths, line number ranges, author identifiers, version identifiers and access popularity for each semantic block; constructing a weighted directed acyclic graph (DAG) based on the semantic chunks and the dependency relationship thereof; superposing a metadata layer in the DAG structure, and recording information such as function call dependency, inter-block reference relationship and version evolution chain; blocks with relatively high access frequency and close semantics are aggregated into super blocks, the traversal depth is reduced, and meanwhile, hot data and cold data are differentiated for hierarchical storage by adopting a cold and hot data management strategy; and evaluating a parent block aggregation degree through a BDS algorithm, determining a block sorting priority, and optimizing super block boundary division. Compared with the prior art, the method has the advantages that the semantic retrieval efficiency, the incremental updating capability and the distributed query performance of the source code storage system are improved.

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.

A method is provided for constructing decision trees. The method includes analyzing a dataset to determine data distribution metrics; calculating feature importance scores for features in the dataset; dynamically adjusting tree depth and node pruning criteria based on the determined data distribution metrics and feature importance scores; initializing a decision tree structure based on the adjusted tree depth and node pruning criteria; and iteratively refining the decision tree by applying heuristic adjustments to improve splits based on updated data distribution metrics and feature importance scores.

The invention discloses a data ownership verification and authorization control method based on zero knowledge proof. The method comprises the following steps: constructing a traceable Merk tree structure on a block chain or a distributed account book; a data owner calculates data fingerprints and packages the data fingerprints into declaration nodes to be inserted into the traceable Merk tree; storing the ownership zero knowledge proof and the traceable Merk tree root hash into a block chain together; the verification party executes the zero-knowledge verifier contract on the chain to complete ownership verification without reading original data or identity plaintext; access control is realized after on-chain verification of the service party; triggering local heavy hash to update the traceable Merk tree root hash, and broadcasting a revocation event on a chain; and confirming legality of evolution and authorization change of all nodes. According to the method, the historical traceability and structural consistency of the data ownership and authorization relationship are ensured, and efficient traceability and anomaly detection of the node evolution chain are also realized.

The invention discloses a structured remote sensing report generation system, method and device based on a syntax tree and a medium, the system comprises a user input layer, a core processing layer and an output and verification layer, the system receives user demand parameters and input data, automatically analyzes the demand parameters and standardizes the input data; generating a syntax tree structure conforming to industry specifications, and driving the large model to obtain a first draft of a report under the constraint of the syntax tree; and performing automatic verification and manual intervention correction on the first draft of the report to form a professional remote sensing report. According to the method, the multi-dimensional syntax tree architecture is constructed, and the hierarchical syntax analysis algorithm and the domain knowledge graph are combined, so that semantic association of the multi-modal remote sensing data and accurate mapping of terminologies are realized, automatic generation of a long document report meeting remote sensing geographic industry specifications is supported, the structured degree and logic continuity of text generation are improved, and the text generation efficiency is improved. The method can be widely applied to the fields of geological monitoring analysis, environment evaluation report generation and the like.

The invention discloses a Multi-Point CTS-based chip clock design optimization method, and relates to the technical field of chip clock design optimization, and the method comprises the following steps: using a hardware description language VHDL to compile RTL codes describing circuit behaviors, using a DC EDA tool of Synopsys to convert the RTL codes into a logic netlist, using a standard algorithm H-Tree to construct a preliminary clock tree structure layout, and using the standard algorithm H-Tree to construct the logic netlist. Obtaining a primary clock tree topological graph; a Multi-Point CTS method is introduced, a plurality of clock sources are adopted to optimize the initial clock tree topological graph, and an optimized clock tree topological graph is obtained; a static time sequence analysis tool PrimeTime is adopted to analyze the optimized clock tree topological graph, and a time sequence analysis result is obtained; identifying the longest path from a clock source to a register in the optimized clock tree topological graph according to a time sequence analysis result, marking the longest path as a critical path, and finding the optimal position for placing a buffer in the critical path by adopting a heuristic search algorithm; and calculating a difference value between the actual delay and the maximum allowable delay of the optimized clock tree topological graph by using PrimeTime again.

The invention provides a knowledge base construction method and an intelligent question and answer method based on a large language model. The knowledge base construction method comprises the steps of dividing multi-granularity texts, recursively merging the texts and then extracting feature vectors, and constructing a tree-shaped / net-shaped structure of the texts with different theme / abstract levels from a bottom layer to the top. According to the method, the problems of semantic depth and association in reading are solved by constructing a recursive tree structure, and granularity information of details is considered while wide subject understanding is kept; the nodes are allowed to be subjected to grouping optimization based on semantic similarity, and then the context association problem is solved in a mode of organizing text data in a tree-shaped / net-shaped structure; in the retrieval stage, the large model recall the multi-granularity text from the tree-shaped / net-shaped structure, and recall information is integrated.

The invention discloses a natural language intention recognition system based on rule and large model dynamic collaboration, and relates to the technical field of artificial intelligence, and the method comprises the following steps: an input preprocessing layer is used for converting a user dialogue voice stream into text information; the complexity judgment module is used for judging whether the text information is complex or not, and the matching module is used for performing rule matching on high-priority rule base rules under a multi-level rule tree architecture; the rule engine module is used for performing intention recognition on the text information based on the rule matching method selected by the matching module under the condition that the text information is not complex so as to obtain an intention recognition result, and the large model processing module is used for performing intention recognition on the text information under the condition that the text information is complex so as to obtain an intention recognition result; and the output layer is used for outputting an intention recognition result. The intention recognition method is beneficial for solving the problems of relatively low intention recognition accuracy, relatively slow response speed and relatively poor processing capability for services in a specific field in the prior art.

The invention provides a multi-agent construction method and device and related equipment, and relates to the technical field of artificial intelligence, and the method comprises the steps: according to a first target instruction input by a first user, obtaining a plurality of sub-tasks corresponding to the first target instruction and a logic relation between the sub-tasks; obtaining at least one target agent from an agent capability library based on the first target instruction, wherein the target agent is an agent matched with the subtask in the agent capability library; determining a behavior tree structure according to the plurality of subtasks and the logical relationship, wherein the behavior tree structure is used for mapping a connection relationship between the at least one target agent; and adjusting a connection relationship between the at least one target agent based on the behavior tree structure to obtain a target multi-agent. The ability to understand complex business contexts and user intentions is enhanced, and accurate construction of a multi-agent system is realized.

The invention discloses a code vulnerability detection method based on multi-dimensional feature fusion and edge semantic enhancement, and the method comprises the steps: carrying out AST sub-tree structure compression based on a sub-tree folding rule on the basis of retaining an AST high-level grammar framework, fusing a PDG data flow and control flow dependency relationship, and constructing a lightweight program semantic graph; extracting node multi-dimensional features from the program semantic graph, extracting program-level global features in combination with an edge semantic enhancement mechanism, and performing vectorization representation; and inputting the program semantic graph features into a full connection layer, identifying potential vulnerabilities and outputting a detection result. According to the scheme, a context modeling mechanism based on a scope path is introduced, a semantic subtree, a grammar structure and scope information are combined, multi-dimensional features are extracted, multi-dimensional information fusion is realized through a dynamic attention mechanism, local and global feature splitting is prevented, and the edge semantic enhancement module is constructed to realize multi-dimensional information fusion. And the distinguishing capability and the feature expression capability of the model on heterogeneous edges are 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.

The invention discloses a service starting sequence optimization method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining a multi-mode data set of at least one service in a substrate management controller, creating a target function, taking each service in the at least one service as a node to construct a target tree structure, and obtaining a target tree structure; the optimization objective of the objective function is to minimize the total start time of at least one service; and based on the target function and the target tree structure, determining a target node corresponding to the optimal evaluation index in each layer of structure, and finally starting the service corresponding to each target node in sequence according to the hierarchical relationship between the determined target nodes. By means of the method, the technical problem that in the related technology, flexibility is poor when all services in the baseboard management controller are started in a predefined static sequence is solved, and the technical effect of optimizing the service starting sequence through the self-adaptive dynamically-changed operation environment is achieved.

The invention discloses a complex table semantic understanding method and device based on a large language model, and the method comprises the steps: firstly carrying out the preprocessing of a document through a table detection model and a table structure recognition model, and extracting the structure information of a table in the document; secondly, reconstructing the structure of a complex table through a large language model, and constructing two tree structures according to row and column information; and on the basis, semantic translation is performed on the reconstructed table through a preset rule, and a sentence which most conforms to logic is screened out through a large language model, so that deep understanding and accurate expression of complex table contents are realized. The invention provides a new method for processing complex table semantics, the table processing efficiency and accuracy are improved, and valuable references are provided for practical application scenes such as data mining, information retrieval and intelligent questions and answers.

The invention relates to a large model adaptive reasoning method based on Monte Carlo tree search. The method comprises the following steps: organizing a reasoning process of a large language model by adopting a tree structure; selecting a node to be expanded by using a UCT algorithm; when a new node is expanded, all information on the current reasoning path is used for the currently selected node to generate a next reasoning step; simulation is executed, reasoning is continued based on the existing reasoning steps until a final answer is obtained, and whether the final answer is correct or not is judged; carrying out back propagation according to the correct final answer, carrying out reward updating on nodes on the current reasoning path, taking a tree structure before new nodes are generated as cue words, and taking the nodes generated according to the cue words as generated data; finely adjusting the large model according to the generated data; and carrying out reinforcement learning on the large model by using a PPO algorithm. According to the method, the father node can be automatically selected according to the current reasoning state, the new reasoning node is added into the nodes, and finally an accurate and reasonable answer is generated.

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 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 provides a mechanical arm path planning method based on mixed sampling and dynamic step length, and relates to the technical field of mechanical arm motion planning. The method comprises the steps that working environment information of the mechanical arm is obtained, a tree structure is established according to an initial joint angle and a target joint angle, and the extension step length is initialized; selecting a sampling strategy according to the random probability; adjusting the extended step length according to whether the sampling point shortens the distance between the two trees, carrying out collision detection and adding a new node; performing greedy expansion on the target tree; updating the operation tree and the target tree; and if the two trees are connected, returning to plan the path, entering a path post-processing stage, and performing path optimization by using redundant point removal and triangular interpolation. According to the mechanical arm path planning method based on mixed sampling and dynamic step length provided by the invention, a high-quality motion path can be quickly planned for the mechanical arm in a high-dimensional complex space.

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 network information, in particular to a training method and device based on online tree search, equipment and a medium, and the method comprises the steps: carrying out the initialization processing of given prompt information based on entropy guide tree search, and generating a guide tree root; selecting a bifurcation point of a guide tree root according to the entropy value, and performing extension processing on the bifurcation point of the guide tree to obtain a tree structure; and calculating a node value in the tree structure by using a Monte Carlo method, calculating a reward signal based on the node value in the tree structure, and strengthening the tree search strategy model. The exploration diversity is enhanced through tree search, the learning efficiency is improved through process supervision, a closed-loop optimization system is formed, the capacity of a large language model on complex reasoning tasks such as mathematics and programming is remarkably improved, and the method has wide application value.

The invention discloses a natural language driven CAD (Computer Aided Design) modeling method based on multi-agent collaboration. According to the method, a collaborative mechanism of a structure planning agent, a parameter completion agent and an execution verification agent is introduced, and the method comprises the steps that firstly, a structure planning agent analyzes natural language description and generates an abstract syntax tree structure meeting a CAD modeling rule; then, on the premise that the structure of the abstract syntax tree is kept unchanged, a parameter completion agent predicts and completes all symbol and numerical parameters, and a complete CAD modeling instruction sequence is generated; and finally, the execution verification agent performs structure and parameter dual verification on the generation instruction by using the geometric kernel, and feeds back and corrects if necessary. According to the method, a strategy of combining field adaptive full-parameter pre-training and task specific fine tuning is adopted in a training stage, and a structure-parameter decoupling modeling and closed loop verification mechanism is introduced, so that the structure accuracy, the parameter matching property and the geometric performability of a generated result are effectively improved.

The invention discloses a geographic space data search method, a geographic space data transaction method and a related device. The search method comprises the following steps: acquiring a search range; according to the search range and a pre-constructed hybrid tree index, searching a data set A intersecting with the search range from all data sets corresponding to the hybrid tree index; wherein the hybrid tree index is composed of a ball tree index and a KD tree index; and performing multi-dimensional similarity calculation on the search range and the data set A, and determining a search result according to a multi-dimensional similarity calculation result. According to the search method, the mixed tree index composed of the ball tree and the KD tree is adopted for first-stage search, the node access frequency during search is reduced through the complementary advantages of the two tree structures, and the search efficiency is remarkably improved when high-dimensional and large-scale data are processed; and multi-dimensional similarity search is further performed based on the search result of the first stage, so that complex search requirements are met.

A three-dimensional data encoding method includes: encoding information of a target node included in an N-ary tree structure of three-dimensional points included in three-dimensional data; and generating a bitstream including the information of the target node encoded. In the encoding, the target node is encoded based on reference limitation information indicating a referable neighbor node among neighbor nodes spatially neighboring the target node. In the generating, when the target node is encoded by reference to information of a first neighbor node, the bitstream further including encoding processing information is generated, the encoding processing information indicating a processing method in the encoding; and when the target node is encoded without reference to the information of the first neighbor node, the bitstream is generated without including the encoding processing information in the bitstream.

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 pruning optimization-based RAG reordering method for a tree structure document, belongs to the technical field of computer science and information processing, and relates to a pruning optimization-based RAG reordering method for a tree structure document in combination with a machine learning algorithm and a probability theory based on a pruning strategy and an RAG (Retrieval-Augmented Generation) technology. And carrying out node score calculation, pruning optimization and reordering processing on the multi-way tree structure document, so as to improve the reasoning efficiency and response speed of the large-scale language model in knowledge retrieval and generation tasks. The method is suitable for application scenes needing efficient document processing, quick response and high accuracy, such as search engines, intelligent question-answering systems and knowledge base management.

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 field of software engineering, and particularly relates to a code translation method based on a tree instruction large language model, which can be used for converting a source programming language into a target programming language. According to the method, key tree structure information is extracted from a linearized AST, and a similarity model is trained to align a tree structure with a code structure, so that a more accurate instruction data set is constructed, and the understanding ability of a large language model to an AST structure is improved; through combination with a large language model, human intervention is greatly reduced, and the code translation cost is greatly reduced; an additional function evaluation scheme is added, so that the friendliness of a translation result to a user result is improved; in addition, the method has high expandability, different large language models can be easily switched and used, the user experience can be improved, and the professional skill threshold needed by use is lowered.

The invention discloses a verification method and device for a vehicle bill of materials, a medium and a product, and relates to the field of informatization of the manufacturing industry, the method comprises the steps that a to-be-verified bill of materials is acquired, and the bill of materials comprises all material numbers of materials needed by one vehicle type and the hierarchical relation between all the material numbers; generating a tree structure of the bill of materials based on each material number and the hierarchical relationship; based on the tree structure, generating a standard format file for each material number, the standard format file being used for describing basic information of the material number in the tree structure; sending the standard format file to a pre-trained random forest model, so that the random forest model verifies the bill of materials, and outputting a verification result; and when the verification result is that the error exists, determining that the error exists in the bill of materials or the rule in the random forest model is missing. According to the invention, the accuracy and efficiency of vehicle bill-of-material verification are improved.

The invention discloses a substrate management controller firmware integrity verification method and electronic equipment, and relates to the technical field of server management, and the method comprises the steps: building a tree structure layered according to a storage path prefix through obtaining the storage path and content data of each function module, the full-coverage verification of all functional modules of the firmware of the baseboard management controller is realized; according to the method, the security level labels in the structured description information are screened, and the verification path is determined for the target function module, so that the redundant operation of full firmware mirror image hash calculation is avoided, and the calculation amount and time consumption in the verification process are reduced; hash is recalculated based on the target function module and path consistency is verified, whether the target function module is tampered or not can be rapidly judged, all firmware data does not need to be traversed, verification comprehensiveness and efficiency are both considered, and bandwidth resource consumption is reduced; all function modules are associated through a storage path and content data, tree structure verification logic is combined, and refinement of firmware verification from a full mirror image level to a function module level is achieved.