131 results about "Tree generation" patented technology

The invention discloses an archive digitization full-life-cycle encryption integrity verification method and system, relates to the field of digital archive safety management, and is used for solving the problem of integrity and safety guarantee in archive digitization management. Logic units are divided through a semantic analysis engine, non-uniform blocks are generated based on sensitivity dynamic partitioning, local hash values are calculated, and a multi-level verification tree is constructed to generate root hash and a hash path mapping table; acquiring visitor identities, terminal environments and timestamps in each stage of an archive life cycle, generating state snapshots in combination with a hash path, and constructing a life cycle state snapshot chain; reconstructing a target logic unit verification path according to the access request, analyzing the structural difference between a current path and a historical snapshot chain through a path reconstruction type difference verification algorithm, and identifying structural offset, node tampering or path loss; and response control is triggered for abnormal verification, including session key updating and permission freezing, so that the security integrity guarantee of the digital archive in the full life cycle is improved.

The invention relates to the technical field of enterprise data processing, and discloses an intelligent analysis system for enterprise operation data based on artificial intelligence. The system comprises an operation data acquisition module, an operation state analysis module, a decision tree generation module, a data compensation module and an execution parameter generation module. The operation data acquisition module acquires enterprise finance, supply chain logistics and market dynamic data in real time, integrates and cleans multi-source heterogeneous data, and generates an operation state data set; the operation state analysis module identifies a deviation degree between the key business index and a preset threshold value, and calculates a multi-dimensional abnormal value by means of a dynamic weighting strategy to obtain an abnormal feature set; a decision-making tree generation module constructs a multi-layer decision-making path according to the multi-layer decision-making path, matches an optimal branch in combination with a historical case library, and generates a visual decision-making tree; the data compensation module analyzes the influence of missing data and automatically supplements an external data source to generate a compensation parameter set; and the execution parameter generation module analyzes node priorities, quantifies resource configuration and time window parameters, and generates a strategy execution parameter packet.

Provided are a method and device for parsing a database query statement, and a storage medium. A query statement for a database table to be queried is obtained, and an empty database table corresponding to the database table to be queried is created; the query statement is executed in the empty database table, and a parser installed in a database is called to parse the query statement to obtain a syntax tree, and an execution plan is generated based on the syntax tree for execution in the empty database table; and the syntax tree is obtained from the parser in an execution process of the query statement, and a syntax tree serialization result is generated and output as a parsing result of the query statement.

The invention provides a front-end code evaluation method and system, electronic equipment and a program product, and the method comprises the steps: obtaining a front-end code, carrying out the compiling and rendering of the front-end code, and obtaining a generated front-end page and a target front-end page; performing code extraction processing on the generated front-end page and the target front-end page, and performing redundant node cleaning and code structure tree generation processing on extracted markup language codes to obtain a generated code tree and a target code tree; performing tree structure and element content error calculation processing on the generated code tree and the target code tree to obtain a content structure error; performing visual structure error calculation processing on the generated front-end page and the target front-end page to obtain a visual structure error; and according to the content structure error and the visual structure error, determining and obtaining an evaluation result for generating the front-end code. The scheme can improve the generation accuracy of the front-end code, and can be widely applied to the technical field of artificial intelligence.

To generate a summary that holds causal relationship for a plurality of images.SOLUTION: A summarization apparatus includes: a rhetorical structure tree generation unit configured to generate a rhetorical structure tree for a plurality of images regarding a certain event related in time series; an event relation generation unit configured to generate a tree structure that represents a relationship between events related to the images, using the images as nodes, based on the rhetorical structure tree; and a summary generation unit configured to extract subtrees from the tree structure so as to satisfy the constraints for the summary of the images.SELECTED DRAWING: Figure 2

The invention relates to the technical field of natural language processing and artificial intelligence, and discloses a large-model complex instruction-oriented fine-grained intention recognition method, which comprises the following steps of: constructing a candidate analysis forest of an input instruction, and executing entity alignment of each node and a domain knowledge graph; performing semantic compatibility verification on the candidate dependency trees by utilizing entity relationships in the atlas, and screening an optimal analytic tree in combination with syntactic probability and knowledge consistency scores; if the analytic tree meeting the threshold value does not exist, a semantic conflict edge is positioned, and candidate mounting points are searched by using a map neighborhood relation to reconstruct a dependency structure; and finally, generating standardized data containing a structured analytic path based on the optimal analytic tree, and performing fine adjustment on the large model. According to the method, logic constraint and dynamic repair are carried out on the syntactic structure by introducing the knowledge graph, analysis errors caused by multiple modification or structural ambiguity in a complex instruction are effectively solved, and the accuracy and robustness of intention recognition of a large model in the vertical field are improved.

The invention belongs to the technical field of spacecraft product quality and reliability analysis modeling, and particularly relates to a fault tree generation method and device based on a knowledge graph and a large model fusion technology. The method comprises the following steps: constructing a spacecraft product fault domain ontology model, establishing a tag system comprising entity tags and relation tags, and extracting related knowledge from a technical document, a SysML model and an FMEA table by using a large language model to form a triple; according to entity types and relation types of different source knowledge, fusion is carried out, and a fault knowledge graph is constructed; obtaining a function dependence sub-graph, a fault behavior sub-graph and a redundant sub-graph of a function or a composition structure from the fault knowledge graph, and retrieving a specific sub-graph from the fault knowledge graph according to a user question; analyzing fault propagation relation and redundant structure information based on function dependence in the specific sub-graph to construct an OR gate and an AND gate, and mapping nodes in the specific sub-graph to a basic event, an intermediate event, a top event and a gate to generate a fault tree.

The invention discloses a document processing method and related equipment, and belongs to the technical field of data processing.The method comprises the steps that in response to a document input instruction, a to-be-processed target document is obtained; performing structure analysis on a to-be-processed target document to generate a directory tree of the target document; calling a dynamic recursive slicing algorithm, traversing and analyzing the directory tree of the target document, and generating a plurality of text slices with dynamic lengths; and vectorizing the plurality of text slices with the dynamic lengths, and uploading and storing the vectorized text slices to a database of a retrieval enhancement generation system. By constructing the directory tree and traversing the directory tree by adopting the dynamic recursive slicing algorithm, the document structure can be more accurately understood, the semantic integrity of the document slices is improved, and the retrieval accuracy and the answer generation quality of the retrieval enhancement generation system are further effectively improved.

The embodiment of the invention provides a page style code generation method and device, a medium, equipment and a program product. The method comprises the following steps: updating a current page element code to obtain a target page element code, and determining a style name and a hierarchical relationship of a target page element according to a first abstract syntax tree corresponding to the target page element code; updating a target object based on the style name and the hierarchical relationship of the target page element, wherein the target object is used for storing the style name and the hierarchical relationship of the current page element corresponding to the current page element code; and updating a second abstract syntax tree corresponding to the current page style code according to the updated target object, and generating a target page style code according to the updated second abstract syntax tree. According to the embodiment of the invention, the second abstract syntax tree of the existing page style code is updated based on the style name and the hierarchical relationship in the target object, a complete abstract syntax tree of the page style code does not need to be regenerated, and the generation efficiency of the page style code is improved.

The application relates to an object classification method and device, computer equipment, a storage medium and a computer program product. An initial decision tree is generated based on training operation data and a training label corresponding to a training object, and the initial decision tree is used as a current decision tree; the training operation data is input into the current decision tree to obtain a current round prediction result, a prediction error is generated based on the training label, the current round prediction result and a historical round prediction result; a backward decision tree of the current decision tree is generated based on the training operation data and the prediction error, the backward decision tree is used as the current decision tree, the step of inputting the training operation data into the current decision tree to obtain the current round prediction result is returned to be executed until a first convergence condition is met, and a plurality of backward decision trees are obtained; and an object classification model generated based on the initial decision tree and each backward decision tree is used to obtain a prediction label corresponding to a target object by fusing prediction results of target operation data of the target object of each decision tree, so that the object classification accuracy can be improved.

This invention discloses a method and system for multi-robot collaborative operation in oil and gas fields based on a large language model, relating to the fields of robot collaboration and intelligent planning. The method acquires oil and gas field operation task information, pre-sets task construction rules, uses a large model to parse task instructions and form a hierarchical task tree, and then writes oil and gas field operation constraint information to form a constrained hierarchical task tree. Simultaneously, it acquires robot capability information and constructs a skill library, matches and selects execution robots, and thus determines the multi-robot collaborative operation arrangement to complete the oil and gas field operation task. The system includes a task acquisition module, a task rule pre-setting module, a task tree generation module, a constraint writing module, an execution subject determination module, and a collaborative execution module. This invention, through the collaborative design of the method and system, enhances the understanding and collaborative stability of multi-robot systems for complex tasks, improving their collaborative efficiency and task completion quality in oil and gas field scenarios.

The invention relates to a system development method and device, computer equipment, a computer readable storage medium and a computer program product. Obtaining a system model constructed based on a first language; the first language is a semi-formalized modeling language; analyzing the system model to obtain an abstract instantiated syntax tree corresponding to the system model, and performing system analysis at least including system resource budget analysis based on the abstract instantiated syntax tree to obtain an analysis result; under the condition that the analysis result meets a preset condition, generating a target code of a second language matched with the system model based on the abstract instantiation syntax tree; the second language is a programming language. By adopting the method, the model development efficiency and quality can be improved.

The present application relates to the technical field of electronics, and discloses a DOM tree generation method and an electronic device. The method is applied to an electronic device. When a Web application loads a webpage comprising a Web component, the Web component is a file in a target format, the file in the target format is a file recognizable by the electronic device, and thus, when a rendering engine invokes the Web component, the file in the target format can run directly in the rendering engine. In addition, the rendering engine comprises a function set used for creating a DOM tree of the Web component, the rendering engine can generate a rendering context used for indicating an entry of the function set, and thus, the rendering engine can invoke a function in the function set via the Web component and the entry of the function set, thereby directly acquiring, within the rendering engine, the function used for creating the DOM tree, and then completing the creation of the DOM tree within the rendering engine. Thus, interaction between the rendering engine and a node on the DOM tree of the Web component no longer needs to be performed via an execution engine, thereby significantly saving data binding overhead and conversion overhead.

The invention discloses an intelligent fault tree generation method based on cooperation of a multi-modal large model and a large language model, and relates to the field of fault tree analysis. In order to solve the defects of low tree building efficiency, insufficient cross-modal information processing and incomplete fault causal chain reasoning in the prior art, the technical scheme provided by the invention comprises the following steps: carrying out topological structure analysis on a system flow chart by adopting a multi-modal large model to obtain an equipment network table; taking the equipment network list as input, and performing fault mode directional retrieval on the equipment information base by adopting a large language model to obtain a fault mode list; taking the equipment network list and the fault mode list as input, performing failure reason reasoning by adopting a large language model, and establishing a fault causal chain from a system layer to an equipment layer; and taking the fault causal chain as input, constructing a fault tree by adopting a large language model, and generating a complete fault tree structure from a system top event to an equipment basic event. The method is suitable for safety and reliability analysis work of a complex industrial system.

The present invention uses an error cause inference device including: a data preprocessing section that generates training data having a format suitable for input to a machine learning model using processing target data; and a model tree generation section that generates a learning model for detecting an error, i.e., an error detection model, with the training data as input, and generates a model tree that expresses relationships between error detection models using a tree structure with error detection models as nodes. Thereby, even without adding labels to error causes in advance, it is possible to generate learning models that detect errors by various types of errors that occur.

A system for inducing taxonomy based on a data sample and an inference classification of raw data (506A) using the induced taxonomy (IT). includes processing arrangement (PA) (106) using set of modules selected from: a segmentation module configured to segment data sample into ontological segments a clustering module configured to cluster ontological segments into ontological clusters (206); a subtree generation module configured to large language model to generate subtree (208, 302) for each ontological cluster; and a taxonomy construction module configured to induce taxonomy comprising root node (210A, 302A, 304A, 702) and combination of subtrees. The PA includes a classification module configured to map IT to set of label configuration objects (504A, 602A-D); and classify raw data using a set of label configuration objects derived from mapped IT. Included is computer-implemented method for inducing taxonomy based on data sample and inference classification of raw data using IT.

The embodiment of the invention provides a clock tree generation method and a chip, and relates to the technical field of integrated circuits, and the method comprises the steps: determining a plurality of groups of sub-clock trees according to the node position of a clock tree and a preset grouping rule; and performing clock wiring based on the multiple groups of sub-clock trees and the selectable driving units to obtain a clock tree, the number of clock tree nodes in each group of sub-clock trees being determined according to the driving capability and the driving distance of the selectable driving units. Therefore, the problem of large clock skew caused by the fact that nodes in a clock tree deviate from a symmetrical structure due to the fact that various devices exist in a chip in a traditional Htree clock can be solved, and the effect of high-speed and stable transmission of clock signals is achieved.

The invention discloses a multi-modal multi-hop question and answer method, device and system and a storage medium, a reinforcement learning teacher is combined with an implication tree, a student model is distilled to improve the generation quality of the implication tree, and multi-path generation is introduced to improve the generalization ability; and further performing iterative reasoning on the sub-questions in the implication tree by using multi-modal expert iteration, and continuously updating the intermediate answers. By the adoption of the technical scheme, the multi-modal multi-hop question and answer accuracy and the implication tree generation quality are improved.

The application provides a message conversion code generation method, related device and computer storage medium, the method comprises the following steps: respectively analyzing an XML schema definition source file and a target XML schema definition file to obtain an XML schema definition source file object tree and a target XML schema definition file object tree; generating a first hypertext markup language tree according to the XML schema definition source file object tree in a preset format; generating a second hypertext markup language tree according to the target XML schema definition file object tree in a preset format; showing the first hypertext markup language tree and the second hypertext markup language tree to a user; receiving a mapping relationship group of nodes in the first hypertext markup language tree and nodes in the second hypertext markup language tree edited by the user; and generating a message conversion code according to the mapping relationship group of the nodes in the first hypertext markup language tree and the nodes in the second hypertext markup language tree. Thus, the development work is assisted.

The application provides a code templating generation method and system based on an annotation markup language, and relates to the technical field of code development. The generation method comprises the following steps: creating a project framework template; constructing a meta object; reading a global template file; parsing annotation marks in the global template file to form a global template syntax tree; executing the global template syntax tree to traverse a code template file; reading the code template file; parsing annotation marks in the code template file to form a code template syntax tree; executing the code template syntax tree to generate code; creating a code file and writing the code; and the generation system comprises a meta object, an annotation markup language, a framework template specification, a meta object controller, a generator, a dialect controller, a file reader, an annotation markup language parser and an annotation markup language executor. The application has the beneficial effects that a project framework template is provided, unified research and development standards are provided, the efficiency and quality of code writing are improved, and the application is suitable for various computer languages.

A fault tree in which causes for failure events are appropriately developed is generated. A fault tree generation device according to the present invention includes a formula database that stores formulas related to physical phenomena, a formula base causal model generation unit that generates a causal relationship of failure events based on the formulas, a formula base fault tree generation unit that generates a formula base fault tree that is a combination of the causal relationships of the failure events, and an output unit that outputs the formula base fault tree.

This invention provides a method, device, and storage medium for generating and utilizing a multimodal discourse tree (MMDT). [Solution] The method generates an Extended Discourse Tree (EDT) from a text corpus (e.g., from a Discourse Tree (DT) or Communication DT (CDT)), links data records (e.g., records containing numerical data) to the Extended Discourse Tree, and generates a Multimedia Discourse Tree (MMDT). The MMDT links any suitable text / records from heterogeneous sources. For example, entities identified from the basic discourse units of the EDT are matched with entities in the data records. The method also identifies causal links between EDTs and / or between data records, identifies rhetorical relationships for each entity match / causal link match, and merges the data records with the EDT to generate the MMDT.

The application discloses a power supply reliability full-service intelligent retrieval method and system, and the method comprises the following steps: storing power supply reliability management system data into a graph database; preprocessing natural language to obtain a standardized input sentence; performing word segmentation on the standardized input sentence, performing word segmentation screening on the word segmentation list, and generating a corresponding cypher query statement based on a rule matching principle and a decision tree; generating a cypher query statement based on rule matching and a decision tree for the user input sentence, respectively, performing consistency calculation on the coded results of the two, when there is consistency, querying the corresponding data through the cypher query statement, and when the two are inconsistent, converting the cypher query statement generated by the decision tree into corresponding natural language to ask the inputter for confirmation; the application has the advantages that the query accuracy is improved, and retrieval failure is avoided.

The application relates to the technical field of anomaly detection, in particular to a rule extraction method and device of a network security anomaly detection model, electronic equipment and a storage medium, wherein the method comprises the following steps: based on a root regression tree generation method, using an anomaly probability value output by an original model as a label to train a regression tree model, and generating a root regression tree; performing positioning processing on the root regression tree to obtain a low-confidence area; performing data augmentation processing on the low-confidence area to obtain augmented data; generating a root regression tree subtree based on the augmented data, performing merging processing on the root regression tree and the root regression tree subtree to obtain a merged tree; and performing rule extraction processing on the merged tree to obtain a complete rule set. The method is independent of a specific anomaly detection learning mechanism and is suitable for various anomaly detection models; the extracted rules can effectively assist security experts in model verification, knowledge discovery and decision support, and the transparency and trustworthiness of the anomaly detection system are improved.

The application belongs to the technical field of integrated circuits, and provides a clock tree generation method, a medium and an electronic device. The method comprises the following steps: obtaining a netlist file of a circuit; identifying a clock network according to a network identifier in the netlist file. Then, the type of a device is identified according to the identification information of the device in the netlist file, and the pin information of the device is determined. The clock link is determined according to the connection relationship of the device in the netlist file. Furthermore, the flow direction of the clock signal can be determined according to the clock link and the pin information of the device. Therefore, the electronic device can automatically draw a clock tree, and the circuit development efficiency is improved.

The invention discloses a behavior tree generation method and device, electronic equipment, a storage medium and a program product, and relates to the technical field of computers.The method comprises the steps that an initial cue word corresponding to a virtual object and a target game environment where the virtual object is located are obtained; inputting the initial cue word into a pre-trained decision model to generate a first behavior tree corresponding to the virtual object; deploying the first behavior tree to a target game environment to obtain game match data; inputting the game playing data into a pre-trained cognitive model, and generating data description information corresponding to the game playing data; and optimizing the first behavior tree based on the data description information to obtain a target behavior tree of the virtual object in the target game environment. By implementing the technical scheme of the invention, automatic generation and optimization of the game virtual object behavior tree can be realized based on collaborative closed-loop iteration of the decision model and the cognitive model, and the intelligent level and the generation efficiency of the game virtual object are improved.

The invention relates to the technical field of knowledge tree construction, in particular to an intelligent customer service knowledge tree construction method. By introducing an asymmetric self-consistency verification mechanism and an automatic training data set construction method, the problem of high dependence on manual annotation and a data template in a traditional business knowledge tree construction process is effectively solved, full-process automation from text document processing to business knowledge tree generation is realized, and meanwhile, the efficiency of business knowledge tree construction is improved. According to the method, the strong semantic comprehension and generation capability of the large language model is utilized, domain rules or templates do not need to be preset, and the method can adapt to document structures and language characteristics of different industries, so that the universality and cross-domain adaptability of knowledge tree construction are greatly improved, and the method is suitable for popularization and application. The method can be widely applied to intelligent customer service systems in multiple vertical fields of finance, education, medical treatment, law and the like, and the core pain point of insufficient generalization ability of a traditional method is solved; the technical problem that a traditional knowledge tree construction method is poor in automation and universality is solved.

This invention provides a method, apparatus, electronic device, and readable medium for generating unified power format files, relating to the field of chip technology. The method involves obtaining a target description file for a voltage domain design diagram. The voltage domain design diagram includes at least two module levels, each module level including at least one module, each module corresponding to at least one voltage domain, and each voltage domain corresponding to at least one power group. Based on the target description file, directed trees representing the hierarchical relationships between modules and the correspondence between modules and voltage domains, directed trees representing the correspondence between voltage domains and power groups, and directed trees representing the composition of power groups are created. Based on the directed trees of modules, voltage domains, and power groups, unified power format files corresponding to each module are generated. This reduces implementation costs and improves the efficiency of generating unified power format files.

The application discloses a kind of interface code automatic generation method based on syntax tree, first interaction is completed in Unity engine interface prefabricated body production, and each node in interface is named. Subsequently, program is first mounted on the root node of interface UIEntity script, then mounted on the node of the need to export binding relationship UIComponent script, finally click the export button on UIEntity, program inside will be mounted according to UIComponet script first generate syntax tree, then generate final Lua code from syntax tree. When generating code, the structure of syntax tree is used to express the content to be exported, so as to achieve higher degree of freedom code generation, improve development efficiency, reduce a lot of repetitive work, and unify code specification. The application adopts the scheme, which not only speeds up the efficiency of game development, but also facilitates the management of code format.

The application discloses a multi-modal multi-hop question and answer method and device, system and storage medium, which combines a reinforcement learning teacher with an implication tree, distills a student model to improve the generation quality of the implication tree, and introduces multi-path generation to improve the generalization capability; further, a multi-modal expert is used to iteratively reason on sub-questions in the implication tree, and continuously update intermediate answers. By adopting the technical scheme of the application, the multi-modal multi-hop question and answer accuracy and the implication tree generation quality are improved.