1284 results about "Template based" patented technology

The invention discloses a cross-border e-commerce compliance intelligent auditing platform and a multi-language contract analysis method, and relates to the field of cross-border contract compliance auditing. In the multi-modal data access step, customs codes, laws and regulations and other multi-source data are collected, and 18 kinds of language contract texts are analyzed; in the cross-language semantic alignment step, a knowledge graph is constructed, and multi-language legal concept mapping is achieved; in the compliance risk reasoning step, a rule engine and an agent cooperatively check a contract, and the compliance conclusion confidence is calculated; the dynamic risk assessment step adopts an LSTM network to analyze historical data and predict a risk trend; in the multi-language report generation step, a multi-format bilingual or multilingual report is generated based on a template engine, encrypted and archived. According to the invention, cross-border contracts are audited efficiently and intelligently, dynamic adaptation laws and regulations are analyzed in multiple languages, compliance risks are identified accurately, and a multi-language report is generated quickly; therefore, the checking efficiency is improved, the manual workload is reduced, the compliance risk is reduced, and the enterprise cross-border business competitiveness and the risk response capability are enhanced.

The invention discloses an electrical work ticket intelligent generation method and device, a medium and equipment in the technical field of power systems, and aims to solve the problems of serious module decoupling, dependence on manual connection and insufficient intelligent generation capability in the prior art. The method comprises the following steps: generating a required digital knowledge base and an electrical work task description generation work ticket based on a pre-constructed work ticket by utilizing a multi-model collaborative generation architecture; the multi-model collaborative generation architecture comprises a rule driving module used for calling a corresponding template based on task element matching; the task execution unit is used for executing a specific subtask according to a pre-deployed lightweight model or rule engine; and the large language model is used for performing semantic understanding and reasoning according to the electrical work task description, calling the rule driving module and the task execution unit according to a semantic understanding and reasoning result, and generating a work ticket in combination with a digital knowledge base required by work ticket generation. The method has both the accuracy of structured knowledge recognition and the flexibility of natural language generation.

The invention provides a Text2SQL generation method and system driven by a large language model, and the method comprises the steps: recognizing key entities and relationships in a natural language question through the large language model, and carrying out the construction to obtain a query graph; constructing a hierarchical graph representation model based on the database mode of the target database; searching candidate sub-image sets which have the same structure as the query graph and are in semantic association with the query graph from the constructed graph representation model; and constructing a structured Prompt template based on the candidate sub-image set and the user question, generating an initial SQL statement, and outputting a final query result after grammar and semantic detection correction. According to the method, a traditional database is converted into the graph knowledge base, so that the SQL generation accuracy and performance are improved; guiding the large model to generate an SQL (Structured Query Language) meeting business requirements through knowledge graph storage and retrieval table and column information; and the accuracy of the SQL is continuously optimized by utilizing a self-adaptive feedback mechanism, so that the method is particularly suitable for a large-scale complex query scene, and self-improvement and customization of the model are realized.

The invention discloses a human resource data natural language query and SQL generation method and system, and relates to the technical field of SQL generation, and the method comprises the steps: preprocessing a natural language query text input by a user, and constructing a query semantic tree; traversing the query semantic tree to generate a candidate entity set, determining an unambiguous entity through a three-layer ambiguity resolution mechanism of semantic scoring, service verification and cross validation, identifying a composite intention, disassembling the composite intention into a sub-intention sequence, and generating an SQL operation instruction set in combination with a preset SQL operation mapping rule; based on the SQL operation instruction set and the human resource data association model, determining a data table set and an association path, generating a dynamic calculation logic and structured condition expression, and constructing a structured query skeleton; according to the method, the personalized SQL template is dynamically generated according to the query skeleton, after filling, grammar verification, strategy optimization and logic consistency verification are performed, and the optimized SQL statement is output, so that the query accuracy and performance are remarkably improved.

The invention relates to an industrial vision adaptive illumination compensation system and method based on Bayesian optimization, and the system comprises an environment perception module which is used for collecting the multi-dimensional environment state data of an industrial site in real time, and collecting an original image; the intelligent preprocessing module is used for enhancing the original image according to the parameter combination output by the Bayesian optimization module to generate an enhanced image; the model reasoning module is used for identifying and detecting the enhanced image through a bimodal algorithm to generate a detection result; the Bayesian optimization module is used for performing objective function calculation to generate an optimization objective score, performing iterative optimization according to the optimization objective score and a historical observation data set, generating a candidate parameter combination, and generating a global optimal parameter and a configuration template based on the candidate parameter combination and a current environment feature; and the industrial interface module is used for transmitting the global optimal parameter, the detection result and the multi-dimensional environment state data to an industrial control system. According to the invention, the efficiency and adaptability of illumination compensation are improved, and the data calculation amount is reduced.

The invention discloses a short message template intelligent identification method and system based on semantic similarity calculation, relates to the technical field of information and communication, and realizes automatic matching of a request short message and a template library through semantic vectorization and similarity calculation; semantic extension, structural constraint and a dynamic feedback mechanism are combined, so that the matching accuracy and robustness are improved; an optimization process driven by a multi-level model and category features is introduced, and an identification-feedback-optimization closed-loop system is formed; the system structurally comprises a semantic modeling module, a similarity calculation module, a dynamic feedback module and a template optimization module, automatic and efficient short message template recognition and updating can be achieved, and the requirements for real-time performance and accuracy in a large-scale application scene are met.

The invention relates to the technical field of computer data processing, provides a cross-border data compliance processing method, device and equipment, and is used for solving the problems of relatively low cross-border data processing efficiency and data processing strategy errors in related technologies. According to the embodiment of the invention, the multi-method domain and regulation knowledge graph is established in advance, laws and regulations of a plurality of regions are summarized, the multi-method domain and regulation knowledge graph can be updated in real time, and the cross-border scene template library and the data label template base library are established according to the multi-method domain and regulation knowledge graph. The cross-border scene template library and the data label template base library can be dynamically updated along with updating of the knowledge graph, and a cross-border gateway can process data by adopting a compliance strategy according to a data cross-border scene through the cross-border scene template library, so that related data management enterprises and institutions efficiently manage data outbound in a compliance manner; through the data label template library, the cross-border gateway can rapidly and accurately carry out data marking work, and the efficiency of data classification processing is improved.

The invention relates to the technical field of building templates, and particularly provides a building template flatness threshold partition detection method based on normal vector constraint RANSAC, which comprises the following steps: performing three-dimensional laser scanning on a building template to obtain high-density point cloud data; preprocessing operations such as denoising and downsampling are carried out on the collected point cloud data, so that the data quality is improved; fitting a reference surface of the template based on the preprocessed point cloud data by using an improved RANSAC algorithm, and introducing a unit normal vector to ensure the correct direction of the reference surface; calculating the vertical distance from each point cloud point to the reference surface to obtain a deviation value; independently setting a deviation threshold value according to a building specification, dividing the deviation value into different grades, and distinguishing and displaying the deviation value on the three-dimensional point cloud model through colors; and a visual result containing the three-dimensional point cloud model and the color identification is output, the flatness condition of the template is visually displayed, and the method has the effects of automatic measurement, high efficiency and high precision.

The invention provides an OCR (Optical Character Recognition) method and system for high-precision table data structuring. The method comprises the following steps: converting an original image into a grayscale image and preprocessing the grayscale image; extracting a table edge structure line and filling a fracture part; detecting longitudinal and transverse straight lines in the preprocessed image, calculating intersection points, and determining a table row-column structure; dividing a cell region and positioning to generate a cell coordinate matrix; pixels in the cells are divided into a frame influence area and an effective data area, and the frame influence area executes neighborhood mean filtering and weighted fusion operation; performing end-to-end detection on characters and symbols in the effective data area, and outputting an OCR recognition result with coordinates; and dynamically generating a table structure template based on the cell coordinate matrix and an OCR recognition result, speculating a strategy matching field type through a rule, processing and merging cell missing data based on adjacent cell information, and outputting structured data. The reliability and accuracy of the OCR technology are improved, and the requirement of automatic information processing for high-precision data extraction is met.

A cloud misconfiguration remediation application (“remediation application”) has been created that generates a remediation action for a resource misconfiguration detected with a CSPM policy. The remediation application includes a conversation agent that interacts with the foundation model according to a chain of prompts / input sequences. The conversation agent constructs the chain of prompts based on a template, the CSPM policy, metadata about the CSPM policy and the misconfigured cloud resource, and responses from the foundation model. The foundation model is implemented with retrieval augmented generation (RAG) that uses an embedding database built with remediation documentation of the CSP. Prompts from the conversation agent are augmented based on the implemented RAG. The remediation application aggregates the responses into a remediation action that can either be automatically performed or presented for consideration by a user.

According to the automatic software development method and device and the computer program, intelligent demand analysis is achieved through a natural language processing technology, dynamic task arrangement is conducted through a finite state automaton, collaborative development is completed by means of a multi-specialized role agent, intelligent verification is implemented based on a template matching mechanism, and the development efficiency is improved. And a complete automatic closed loop from demand to delivery is constructed. According to the scheme, full-process automation is realized, manual intervention is greatly reduced, and the development efficiency is remarkably improved; through division and cooperation of multiple agents, the professionality and decision-making quality of each link are ensured, and the capability limitation of a single agent is overcome; flexible and reliable process control is provided based on state machine management, and development state changes are dynamically adapted; and the standard consistency of the delivery result is ensured by combining template verification. According to the method, the problems of long development period, large quality fluctuation and the like caused by chain splitting, low intelligent level and excessive dependence on manpower of an existing development tool are effectively solved, and a feasible path is provided for comprehensive intelligence of software development.

The invention discloses a low-altitude flight intelligent decision-making method based on atlas retrieval enhanced generation and digital flight rules. The method comprises the following steps: firstly, preprocessing and translating a digital flight rule (DFR) text, extracting entities and relationships through a large language model, constructing a structured knowledge graph, and storing the structured knowledge graph in a vector database; and secondly, circularly calling the large model for three times: calling an optimization cue word to generate a template for the first time, calling a template-based analysis DFR text to complete atlas construction for the second time, and calling a combination atlas retrieval capability to execute compliance verification and route intelligent decision-making of a low-altitude flight task for the third time. In addition, when an airspace rule is changed or a temporary announcement exists, real-time updating of knowledge is achieved by inserting a new node into the knowledge graph or modifying edge attributes. According to the method, GraphRAG and DFR combination is generated through map retrieval enhancement, the interpretability, accuracy and dynamic adaptability of large model decision making are improved, and the problem of complex decision making in a low-altitude environment is solved.

The invention discloses a medical question-answering method, device, equipment and program product, and is applied to the technical field of medical question-answering. The method comprises the following steps: acquiring a disease image and disease chief complaint information; performing feature extraction on the disease image and the disease chief complaint information to obtain pathological visual features and chief complaint text features; performing feature fusion on the pathological visual features and the chief complaint text features to obtain target fusion features; determining a dynamic cue word template based on the information type of the target fusion feature; and inputting the dynamic cue word template and the disease image into a preset large language model, and generating a medical question and answer result by the large language model. According to the method, a complete, dynamic and adaptive cue word template is generated according to the consistency or conflict fuzziness embodied by the multi-modal information, so that the dynamic cue word template can further put forward a more complex task with question and answer guidance to a large language model, the pertinence and depth of medical question and answer are improved, and the medical question and answer efficiency is improved. And the precision of medical questions and answers is effectively improved.

An approach is provided for large language model (LLM) map feedback reporting. The approach involves, for example, processing an input specifying a map error / feedback using an LLM to classify a map error type. The approach also comprises determining a map error template based on the map error type that specifies structured data fields for the map error type. The approach further involves using the template to construct prompts for the LLM to generate questions to collect data items for populating the data fields, and providing the prompts to the LLM to generate the questions and collect the data items from the user. The approach further involves using template to generate additional prompts to generate a map error report of the data items in a structured data format, and providing the additional prompts to the LLM to generate the map error report for transmission to a map feedback system.

The invention discloses a page generation method, system and device and a medium, and the method comprises the steps: obtaining page demand content and target page configuration through responding to a page generation instruction of a target field; obtaining a component knowledge base of the target field and a layout rule base configured by the target page; extracting a target component demand set, a target layout demand and a target priority demand from the page demand content; matching in a component knowledge base according to the target component demand set to obtain a corresponding candidate component set; matching in a layout rule base according to the target layout requirement to obtain a corresponding layout template; generating a target layout scheme according to the candidate component set and the layout template based on the target priority demand; the target page is generated according to the target layout scheme, automatic configuration and generation of the page can be achieved through natural language analysis and intelligent matching logic, and then page configuration and deployment are rapidly completed.

The invention discloses an intelligent legal contract generation method and device based on a contract template and contract term semanteme, and belongs to the technical field of intelligent contracts, and the method comprises the steps: analyzing a legal contract text in combination with a plurality of natural language processing technologies, and constructing a contract meta-model; dynamically generating an intelligent legal contract template based on the contract meta-model; an executable intelligent legal contract code is generated through the contract template; and finally carrying out consistency check on the generated code and the original contract. Therefore, the problems of unclear structure, difficulty in semantic mapping, poor universality, law compliance and the like in the traditional process of converting the contract into the intelligent contract are solved, structured expression of the law text, automatic generation of the contract code and logic consistency verification are realized, and the generation efficiency and reliability of the intelligent law contract are improved.

The invention provides a communication protocol consistency test method and system. Key function points are extracted by analyzing a target protocol document; based on the key function points, a predefined first prompt template is applied to generate a test case prompt, a large language model is guided to generate a standardized test case corresponding to each key function point, and the first prompt template comprises k few-sample examples; dynamically retrieving a related code context from a pre-constructed long-term memory library through a retrieval enhancement generation mechanism, generating a code generation prompt by applying a predefined second prompt template based on the standardized test case and the related code context, and generating an executable test code based on the code generation prompt; and performing iterative optimization on the executable test code through the large language model, and generating a new code generation prompt based on a code execution result of the previous iteration and the retrieved related code context in each iteration. The test case can be automatically generated and dynamically adapted, and the test coverage rate, efficiency and flexibility are improved.

Provided is an image decoding method performed by a decoding apparatus, the image decoding method including receiving image information including at least one of decoder-side intra mode derivation (DIMD)-related information or template-based intra mode derivation (TIMD)-related information from a bitstream, deriving an intra prediction mode of a current block on the basis of the at least one of the DIMD-related information or the TIMD-related information, generating prediction samples of the current block on the basis of the intra prediction mode, and generating reconstructed samples of the current block on the basis of the prediction samples of the current block. The image information includes matrix-based intra prediction (MIP) flag information, the DIMD-related information includes DIMD flag information indicating whether a DIMD mode is applied to the current block, the TIMD-related information includes TIMD flag information indicating whether a TIMD mode is applied to the current block, and the DIMD flag information or the TIMD flag information is parsed after the MIP flag information.

According to the statement conversion method based on the fine tuning model, semantic information and query intention of the query text are analyzed from two aspects of slot positions and operation types through the multi-task model, so that the accuracy of the query statement is improved, and semantic completion is performed on the query statement by reconstructing the slot position relation graph, so that the accuracy of the query statement is improved. Therefore, a relation topology basis is provided for subsequent template matching, and the semantic analysis integrity of the complex query statement is improved. And finally, according to the slot position relation graph, an SQL template conforming to the query intention and semantic information corresponding to the original query statement is determined, and the target SQL statement is obtained by splicing and assembling the target SQL template based on the slot position relation graph, so that the writing difficulty of the query statement is reduced. When the method is applied to a data query function of a system in the financial business field or the medical field, the input convenience of query statements can be improved, and the statement conversion accuracy is improved.

Disclosed is an AI-based automated circuit generation method. The method includes obtaining design metrics; capturing a dependency relationship among design metrics by using an attention mechanism, extracting features by using a multi-layer Transformer structure to obtain an overall structure and a high-level feature representation of a circuit, and matching the high-level feature representation with a standard circuit netlist template based on the overall structure of the circuit to obtain a current circuit netlist; simulating the current circuit netlist to obtain a simulation report, and extracting error information from the simulation report; and correcting the current circuit netlist based on the error information, simulating a corrected circuit netlist again, looping until there are no errors in the simulation report, and outputting a final circuit netlist. The present invention solves the problems that the existing method has limitations and is difficult to quickly, automatically and flexibly design a complex circuit.

The invention discloses an identification and verification method and system for a secondary drawing of a transformer substation, and belongs to the technical field of image identification, and the method specifically comprises the steps: analyzing a CAD vector diagram, obtaining four-corner references and pixel coordinates of a scanning graph, building initial mapping of pixels and engineering millimeter coordinates by taking an engineering millimeter coordinate system as a reference, and generating a unified intermediate representation model; constructing a terminal strip parameterization template based on the vector anchor point set and the visual anchor point set; a composite deformation field is calculated through vector-bitmap-vector closed-loop rendering calibration, terminal row alignment and terminal sequence binding are completed in the composite deformation field, and a terminal pixel position-terminal sequence-engineering millimeter coordinate consistent mapping table is formed; comparing the topological netlist to obtain an electrical node corresponding table; and performing source decomposition on the terminal position residual error based on the composite deformation field and generating a self-adaptive tolerance band, and finally executing wiring verification by taking the self-adaptive tolerance band, the electrical connectivity and the serial number consistency as criteria and outputting a verification report.

The invention relates to the technical field of enterprise informatization and process automation, and discloses an intelligent process construction and dynamic optimization method based on low codes, and the method comprises the steps: selecting a process category based on preset process classification; an initial process template is generated based on the process category, the initial process template is output in a visual mode, and the initial process template comprises an initial task node, an initial process branch and an initial gateway; adjusting an initial task node, an initial process branch and an initial gateway for the initial process template through visual dragging to form a basic process; executing the basic process, recording the execution condition of the basic process, and generating an optimization suggestion according to a preset optimization model; the user selects an optimization scheme according to the optimization suggestion and outputs an optimization process; and adjusting the initial process template based on a preset process adjustment strategy. The method has the advantages of reducing a process construction technical threshold, realizing process dynamic optimization and improving compliance control capability.

The invention relates to the technical field of operation and maintenance, and discloses an equipment fault processing method and system. The method comprises the following steps: acquiring alarm messages of a plurality of devices in real time, identifying associated alarm messages caused by the same fault according to an alarm association rule, and compressing the associated alarm messages and an existing fault group to obtain new alarm messages; determining the work order type and the circulation process of the new work order according to the alarm type of the newly sent alarm message, and carrying out order dispatching priority configuration on each process link based on the alarm level of the newly sent alarm message and the pre-configured authority information of each process link; and calling a corresponding work order template based on the work order type, configuring the work order template to generate a new work order, monitoring the full life cycle of the new work order, and synchronously updating the processing state of the new work order. According to the method, the fault processing efficiency of the machine room intelligent connection equipment is effectively improved, resource configuration is optimized through real-time monitoring and data analysis, and the method can meet the fault troubleshooting requirements of equipment of different scales and types.

The invention provides a legal text generation proofreading method and system based on a large model, and relates to the technical field of computer information processing. The method comprises the following steps: firstly, acquiring an input case text, and matching a corresponding target legal instrument template based on a preset legal instrument template library; secondly, calling a pre-trained large language model according to a format requirement, and generating a first-edition legal document; based on a pre-stored legal knowledge graph, performing internal logic and legal basis consistency verification on the first-edition legal document to obtain a consistency verification result; and finally, according to a consistency verification result, locating conflicts and errors existing in the first-edition legal document so as to generate a proofreading report containing targeted modification suggestions. According to the technical scheme provided by the invention, the legal document with a standard format can be automatically generated, logic and legal reference errors in the legal document can be intelligently detected, and specific modification suggestions are provided, so that the document quality and the generation efficiency are improved.

The invention discloses a road infrastructure anomaly recognition method based on vision and an AI agent. The method comprises the steps that a multi-agent cooperation framework with a task coordination agent as a core is constructed; a data input agent receives and preprocesses multiple paths of video streams; the visual processing agent fuses a visual model and a language model through a cross attention mechanism to realize deep fusion of image-text features; the knowledge base intelligent agent constructs a dynamic JSON Schema structured template based on a Neo4j graph database; and the data output agent calls the large language model to carry out data enhancement and structured processing, and the data is stored in a database after validity is verified by the knowledge graph. According to the method, through multi-agent cooperation, cross-modal feature fusion and a dynamic template technology, the problems of feature splitting, template stiffness and low calculation efficiency in a traditional scheme are solved, and the efficiency of road anomaly recognition is improved.

The invention provides a method and a device for generating a customized report of an SAAS (Software as a Service) system based on dynamic template configuration. The method comprises the following steps: acquiring a customized visual report template for realizing business data decoupling; editing the report template based on a preset editor, and generating a template configuration file; analyzing a structured marker in the template configuration file to generate a metadata description file; querying a business database through a unified data interface according to a data requirement defined by the metadata description file, and obtaining and assembling customized business data corresponding to the tenant ID; and at least based on the customized business data, controlling a rendering process through a dynamic position calculation algorithm, and dynamically filling the data to a corresponding position of the report template to generate a customized report. According to the method, the problems of code redundancy and difficulty in maintenance of the SAAS multi-tenant report are solved, zero code configuration is realized, and report generation efficiency and tenant personalized adaptation capability are improved.

The invention discloses a VR / AR martial art teaching method, device and equipment based on dynamic time warping and a computer readable storage medium. The method comprises the steps of obtaining a user skeleton point sequence corresponding to a user action and a standard action template; determining a specific weight coefficient of the joint for comparison processing; comparing the user skeleton point sequence with a standard action template based on a specific weight coefficient of a joint by applying a weighted dynamic time warping algorithm so as to generate an optimal warping path; obtaining a sequence matching score and a posture matching score according to the optimal regular path and the key force generation event sequence; inputting the sequence matching score, the posture matching score and the determined existing force application sequence error and / or action posture error into a language generation type model to generate a text feedback instruction; and based on the text feedback instruction, generating and displaying immersive teaching feedback in a VR or AR environment. The method has the advantages of multi-dimensional evaluation, immersive feedback and the like.

The invention relates to a template-based self-adaptive stack type generation method, system and device and a storage medium, a preset stack type layout template and to-be-stacked material information are obtained, and relative position information and stack type information of each material in the stack type layout template are calculated; according to the information of the to-be-stacked materials, the relative position information and the stack type information, the to-be-stacked materials and the stack type layout template are matched, so that the to-be-stacked materials are arranged according to the stack type layout template, and a single-layer stack type is obtained; the multiple single-layer stack types are stacked according to a preset merging rule, and an overall stacking stack type is generated; and a preset material gap is obtained, arrangement of the materials in the overall stacking type is adjusted according to the preset material gap, and an actual stacking type is generated. Through template matching and automatic calculation, new stack types can be generated for materials of different sizes in a short time, repeated programming and debugging are not needed, and the time cost is reduced.

The invention relates to the technical field of intelligent tools, and discloses an intelligent implementation method and device for an intelligent operation assistant, equipment and a medium, and the method comprises the steps: adjusting an internal communication protocol and an external service protocol of unified tool service; analyzing the to-be-processed job task based on a natural language processing technology, and determining a task target and a specific demand; obtaining information release addresses of all callable tools, and constructing a tool service address list; performing service communication with the tools through an internal communication protocol to obtain task description information of each tool; the task description information is sent to a cue word engine, the cue word engine matches the corresponding cue word template based on the current task semantics, and the task description information is optimized. The method can be applied to the development of business systems such as financial science and technology, medical health, old-age care and the like, more accurate tasks of a large model are realized, and planning and execution are more reasonable.