156 results about "Rule checking" patented technology

The invention discloses a multi-agent dynamic arrangement method based on multi-modal analysis and adaptive retrieval, and relates to the technical field of artificial intelligence and information retrieval. Comprising the steps of S1, converting a text, an image, structured data and voice content input by a user into a unified multi-mode semantic representation, S2, converting the unified multi-mode semantic representation into a specific execution process, and S3, automatically scheduling a reasoning agent, a knowledge obtaining agent and an execution agent according to DAG nodes, task elements and available resources, and obtaining the task elements and the execution agent according to the reasoning agent, the knowledge obtaining agent and the execution agent. S4, after task process construction and agent arrangement are completed, dynamic retrieval, evidence convergence and strategy optimization are carried out on information requirements related to a user task, so that a reasoning agent obtains complete knowledge support with consistent context, and S5, knowledge evidence is combined with a task process, so that the task process is completed. The method comprises the following steps: step S6, implementing problem solving, strategy generation and task closed-loop execution through a reasoning agent, step S6, performing actual operation on a target task by an execution agent according to an executable instruction sequence output by the reasoning agent, and outputting a result, and step S7, performing result verification according to an output result returned by the execution agent, and the correctness, integrity and consistency of an output result are examined through rule verification, model evaluation and evidence alignment.

Methods and systems for training a prediction model to predict a mask image in which mask rule check (MRC) violations or process violations (e.g., edge placement error, sub-resolution assist feature (SRAF) printing) are minimized or eliminated. The prediction model is trained based on a loss function that is indicative of (a) a difference between the predicted mask image and a reference image, and (b) at least one selected from: an MRC evaluation of the predicted mask image or an evaluation of a simulated image of the predicted mask image.

The invention discloses a ground engineering construction quality supervision digital delivery system, which relates to the technical field of engineering supervision, and comprises the steps of generation and multi-source data checking, activity record structuring and anti-verification before hiding, space-time reference unification and point cloud fusion playback, rule checking and differential rectification, and object-level marshalling delivery and asset authority management. According to the method, a unified data pool, activities, events and evidence chains are constructed through object codes to achieve time-space consistent association, image, point cloud and detection consistency check is conducted before hiding, blocking difference and unified reference fusion point cloud are generated, indexes support three-dimensional playback, rule base batch check is conducted, and issuing rectification is conducted. And the object-level delivery list and fingerprints support cross-platform identification and auditing to form a traceable link.

The invention discloses a structured data quality evaluation and optimization system using a large language model, which comprises a data access module used for formatting and preprocessing data, a data quality detection module used for establishing data quality evaluation indexes, performing statistical analysis and rule verification to detect the data and calculating the overall quality grade, and a big language model, the semantic analysis and SQL generation module is used for analyzing a database structure through a large language model, converting a natural language instruction into an executable SQL statement and is based on the large language model, and the anomaly detection and optimization suggestion module is used for positioning anomaly by utilizing a mixed detection algorithm and generating natural language interpretation and optimization suggestions in combination with the large language model. And the user feedback and dynamic adjustment module is used for absorbing adjustment suggestions through a feedback loop mechanism, and optimizing a prompt project and an SQL generation strategy. According to the method, semantic analysis is carried out on a database structure by adopting a large language model, and high-precision SQL query is automatically generated.

The invention belongs to the technical field of electric power engineering digitization and intelligent drawing auditing, and particularly relates to a dynamic rule engine and multi-target auditing task decomposition method oriented to electric power drawings. Obtaining a power rule file, analyzing and verifying to generate qualified rules, and screening the qualified rules to obtain an effective rule pool; the method comprises the following steps: reserving candidate areas by preprocessing an electric power engineering drawing, generating structured cells through line segment classification and combination and table detection, extracting and cleaning a text, and affiliating the text to the corresponding cells to form a structured result; screening candidate rules from the effective rule pool, extracting auditing objects from the structured result, generating auditing points, calculating the priority of the auditing points, and packaging the auditing points into an assignment unit set capable of being executed in parallel; on the basis of the dispatching unit set, optimizing task distribution by adopting a dynamic model and a greedy algorithm in an execution environment with the maximum concurrency, and doubly optimizing task execution by quantifying benefits and verifying rules; and performing rule judgment and result measurement on a task execution result.

The invention discloses a trusted data sharing method based on a block chain consensus mechanism. The method comprises the following steps: S1, constructing an alliance chain network; s2, completing KZG polynomial commitment generation, ML-KEM algorithm encryption storage and pointer registration; s3, the data provider medical institution completes an evidence storage transaction of the FROST threshold signature; s4, the target medical institution completes the access request transaction; s5, the data provider medical institution sends a KZG unpacking proof and a data item, the target medical institution obtains a storage pointer and a commitment value, KZG verification check is executed, and after verification is passed, an ML-KEM algorithm is executed for depacking to obtain a session key; and S6, the target medical institution completes the audit transaction, and after the alliance chain network broadcast, the consensus node executes rule verification of the access control contract and the audit contract. The multi-node electronic medical record sharing and tamper-proof evidence storage method is high in performance and traceability, and is suitable for credible circulation of sensitive health data among multiple medical institutions.

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

The invention discloses a power distribution network semantic analysis and intelligent number asking method and system based on NL2DSL, and relates to the technical field of power distribution network data query. The method comprises the following steps: receiving a natural language question of the power distribution network, clarifying fuzzy terms through multiple rounds of asking, and outputting a clarified question; based on the historical dialogue and the terminology library optimization problem, generating a standardized and optimized problem; taking a semantic layer of the power distribution network as a unique true phase source, and converting an optimized problem into an initial DSL (Digital Subscriber Line) by combining RAG and Prompt engineering; a compliance DSL is output through double-layer protection of static rule verification and dynamic service verification; and analyzing the compliant DSL and associating the pre-calculation model to generate an optimized SQL, and outputting a structured result after execution. The method can improve the query accuracy and the data security, reduces the maintenance cost, and is suitable for the full-scene intelligent number asking demand of the power distribution network.

The invention relates to the technical field of project cost, in particular to a water conservancy and hydropower project cost achievement quality inspection method and device based on VSTO. Preprocessing the cost achievement document in the Excel format to form a file in which a bill of quantity, a project unit price and a basic price are associated with each other; performing quality inspection on the file formed after preprocessing, wherein the quality inspection comprises form inspection, rule inspection, unit price inspection and index inspection which are sequentially performed; and integrating quality inspection results by using a large language model and an intelligent agent technology to generate an inspection report in a unified format. Excel serves as a uniform interface to be compatible with multi-source data, a large language model is introduced to achieve intelligent generation of a check report, the defect of compatibility of file formats and check logic in the prior art can be overcome, and key technical support can be provided for digital transformation of water conservancy and hydropower project cost management.

The invention relates to a circuit testability-oriented design rule checking method and device and a storage medium, and the method comprises the steps: calculating simulation values of all time sequence elements in a circuit netlist under different signal excitation scene information; acquiring a clock signal corresponding to each time sequence element, and determining a driving clock of each time sequence element based on the simulation value and the clock signal; under the driving clock, according to the judgment result of whether the simulation values of the time sequence elements are constant values or not, binding elements with constant output port values are determined from all the time sequence elements, and the time sequence elements except the binding elements are determined as elements to be detected; based on the scanning test rule and the violation level, performing rule inspection on the to-be-inspected element to obtain a violation element; generating a violation result based on the binding element and / or the violation element; and if the binding element and the violation element are not detected, generating an inspection passing result. According to the invention, efficient and customizable design defect detection is realized.

The invention discloses a drug clinical trial contract management system, which comprises a contract text structured knowledge base for storing contract structures, field terms and hospital basic data and supporting standardized construction. The contract processing engine module is used for receiving test parameters and driving contract intelligent matching, budget automation and text dynamic splicing; the intelligent auditing module is used for performing automatic comparison, rule checking, difference detection, compliance examination and clause conflict early warning, so that manual errors and workload are remarkably reduced; the electronic signing module is used for providing multi-mode identity verification and block chain evidence storage, and ensuring the signing effectiveness and non-tampering property; a database is recorded and tracked, full-life-cycle management of contracts is achieved, state changes and version history are recorded, and tracing and auditing are facilitated. According to the invention, all the modules cooperate, the contract generation efficiency and accuracy are significantly improved, the customization and compliance are enhanced, budget transparency is realized, safe and efficient signing is provided, and the operation cost and legal risks are effectively reduced.

The embodiment of the invention discloses a process template generation method and device, electronic equipment and a storage medium. The method comprises the steps of obtaining a process generation demand of a user, and determining structured process logic description information based on the process generation demand, a preset process design cue word and a preset large language model; generating cue words and a preset large language model based on the process logic description information, a preset process template, and determining a first process template required by the user; performing rule verification on the first process template based on a preset verification plug-in, and determining a verification result; and if the verification result is that the verification is not passed, adjusting the first process template by utilizing a preset large language model, and determining a second process template required by the user. Through the technical scheme of the embodiment of the invention, the executable process template can be directly generated according to the demand described by the natural language, the node attribute and the logic relationship do not need to be manually configured, and the generality, the efficiency and the accuracy of the process template generation are improved.

The invention provides a posture recognition method and system based on a posture recognition neural network, and relates to the technical field of posture recognition, and the method comprises the steps: constructing a standard library containing safety and dangerous posture types, and marking a plurality of key points to generate a soft label sample data set; defining the key points as graph nodes, and constructing a feature matrix and an adjacent matrix; a double-branch fusion network model is designed, key point topological structure features are extracted through image convolution branch, image global context features are extracted through global visual branch, and attitude similarity spectral vectors are output after fusion; and finally, the attitude state is judged by calculating the geometric difference degree between the image to be analyzed and the most similar attitude template on the key point distance and the joint angle and comparing the overall difference between the image to be analyzed and the safety / danger camp. According to the method, the dual advantages of data driving and rule verification are combined, the recognition robustness and decision interpretability of dangerous postures are remarkably improved, and the safety risk is effectively reduced.

The invention discloses a mask pattern repairing method, device and product, and relates to the technical field of semiconductor integrated circuits. The mask plate graph repairing method comprises the following steps: carrying out photoetching simulation on a mask plate graph by adopting a photoetching model to obtain a prediction graph corresponding to the mask plate graph; performing photoetching rule inspection on the prediction graph to obtain the position and the type of a defect point violating a photoetching rule in the prediction graph; according to the position of the defect point, determining a to-be-repaired area of the defect point on the mask plate graph; identifying a pattern edge in the to-be-repaired area, and calculating the influence degree of the position change of the pattern edge on the geometric deviation between the predicted pattern and the design layout by adopting the photoetching model; determining an adjustment parameter of the graph edge according to the type and the influence degree of the defect point; and adjusting the pattern edge according to the adjustment parameter to obtain a repaired mask plate pattern. According to the method, the defects in the mask plate graph can be repaired more efficiently.

The invention discloses a model-based English translation personalized comment and ability improvement direction recommendation system. The system comprises a large language model comment engine, a rule verification layer, an ability map updating layer, a learning path recommendation layer and a feedback closed loop module. The large language model commenting engine is used for receiving Chinese-English bilingual results input by a user; gt; generating personalized comment content including an overall score, a fine item score, an error positioning and correcting example and forward feedback; the rule verification layer is used for performing fact consistency verification on the content generated by the large language comment engine, and triggering content regeneration if a factual contradiction is detected; the method has the advantages that deep comments including fine item scores, error positioning and error correction examples can be generated, learners can be clearly informed of'which error is in and how to change ', the crossing from'knowing'to'knowing'is achieved, and the feedback guiding value and learning efficiency are greatly improved.

The invention relates to the technical field of data processing, in particular to a financial contract online editing system based on multi-person collaboration, and the method comprises the steps: capturing an operation feature vector with a space-time mark in real time through an acquisition unit; the analysis unit generates a regional operation intention set in combination with the contract semantic tag library; the conflict probability calculation unit fuses the space overlapping degree, the logic association chain and the time sequence overlapping window to quantify the conflict risk; the dynamic partition response unit triggers area locking, operation confirmation or background monitoring according to probability value grading; the legal rule verification unit implements compliance interception and outputs a forced interrupt signal; the business logic serialization unit reconstructs an instruction sequence; the multi-strategy synchronous execution unit carries out atomic broadcasting, transaction binding and batch asynchronous updating by differentiating a core term channel, a dependency group channel and a common term channel; and the closed-loop audit tracking unit aggregates full-link data to generate a verifiable influence chain. The risk of data inconsistency caused by concurrent operation of financial contracts is systematically solved.

An auto reviewer system designed to execute required rule checks, extract information of interest to human reviewers, and generate a final report with the results. The auto reviewer system operates by checking that an order satisfies a pre-defined set of conditions and raising a flag for each condition not satisfied. The flags considered pertinent to a user's understanding of the final report are then combined into order notes, and the order notes are automatically entered into the internal note fields of the corresponding orders in one or more workbenches. Additionally, flags raised that correspond to order issues requiring manual intervention trigger automatic support request notifications such as emails, which are sent to a user to be resolved. If an order has no issues requiring manual intervention, then the note generated for that order includes a complete statement and is passed for final report generation.

The invention provides a system-level design generation method and system based on AI-Agent. The method provided by the invention comprises the following steps: receiving design demand information input by a user; carrying out system-level architecture design and system segmentation on the design demand information based on the AI-Agent, generating a system architecture scheme, design prompt information and a constraint file, and carrying out feasibility verification on the system architecture scheme by generating a rule checking mechanism to obtain the system architecture scheme, the design prompt information and the constraint file which pass verification; matching a corresponding path generation method based on the design prompt information passing verification or a Python algorithm code input by a user, and generating a hardware description language code based on the path generation method; and performing function verification on the hardware description language code, connecting the hardware description language code passing the function verification and the constraint file passing the verification with a back-end tool, performing layout wiring, and outputting a GDS-II layout file.

The invention relates to the field of integrated circuit design and photoetching manufacturing simulation, in particular to a layout violation repair guidance method, layout violation repair guidance equipment, a medium and a product. The layout violation repair guidance method comprises the following steps: inputting an initial layout and a physical design rule to be checked, dividing the initial layout into a plurality of layout blocks, and carrying out physical design rule checking on each layout block; if the design rule violation exists, analyzing graphic attributes around the violation to obtain the cause of the violation; and outputting violation repair guidance information according to the violation cause. And outputting violation repair guidance information of each layout block until all the layout blocks complete rule check. Wherein the graph attributes comprise fixed graphs, access paths of pins and ports, and a wiring network. The electronic equipment, the computer storage medium and the computer program product have the same beneficial effects as the layout violation repair guidance method.

The invention discloses a service monitoring data enhancement method, system and device based on LLM and retrieval enhancement generation and a storage medium, and relates to the technical field of service monitoring and exception handling. The method comprises the steps that user exception description is received, a webpage is retrieved through semantic expansion, and triple output structured data is extracted; and comparing with a local knowledge base, processing and storing the new content classification vector, and updating the index. Performing preliminary screening and reordering by combining exception description and an update library, taking a front list as a context to enable a large language model to generate analysis, evaluation and a strategy, and performing rule check and output; a result is verified, scene variants are generated according to exception types, after duplicate removal, the scene variants, strategies and metadata are structurally stored in a knowledge base, and continuous learning of a closed loop is completed; according to the method, high-quality and high-timeliness service exception training data and processing strategies can be automatically generated, the illusion problem of a large language model in actual operation and maintenance is effectively solved, and the fault response speed and the decision accuracy are improved.

The invention discloses a communication chip layout defect automatic identification method based on artificial intelligence. The method comprises the following steps: analyzing a communication chip layout design file; executing design rule check and parameter extraction; an improved NCA model is constructed, state initialization is completed, and a fast-scale update parameter set and a slow-scale update parameter set are generated; executing iterative evolution based on the fast-scale updating parameter set and the slow-scale updating parameter set, and outputting an evolution intermediate representation set; conditional modulation is carried out on an update function of the improved NCA model; constructing a graph neural network topology consistency verification mechanism, and generating a verified defect region set; and performing defect discrimination and labeling, and outputting a defect type set, a defect distribution heat map and a defect coordinate set. According to the method, the communication chip layout defect identification accuracy is improved, and the cross-layer connectivity verification capability is enhanced.

The work ticket intelligent checking method based on multi-modal large model knowledge graph and large model reasoning belongs to the field of power system application technology, first extracts text feature vectors and image feature vectors through an OCR module and an image encoder, forms a comprehensive semantic representation after multi-modal fusion. Extract entities and relationships from power safety regulations and historical operation data to generate a power safety knowledge graph. Check the format and integrity of the basic fields on the ticket, use LLM to combine context and graph nodes for semantic reasoning to generate semantic judgment results. Fuse three layers of results to calculate a comprehensive checking score and output an intelligent determination result. The present application introduces multi-modal input analysis, knowledge graph construction and large model semantic reasoning technology to construct a structured, interpretable and iteratively optimized intelligent work ticket checking system that realizes the full-process intelligentization from ticket image recognition to semantic understanding and from explicit rule checking to implicit logical reasoning.

The application discloses a meteorological department intelligent mail processing method and device based on a large language model. The method analyzes the mail body, attachments and mail header fields, extracts meteorological business semantics, time sequences and multi-modal elements, constructs a meteorological event causal graph MECCG and associates the mail event thread, calculates a dynamic priority in combination with a causal path, time effectiveness and department responsibilities, generates a main responsibility, collaboration and carbon copy routing, calls a large language model enhanced with meteorological field knowledge to generate an abstract, suggestion or reply, and performs fact checking, rule checking and manual review triggering, and optimizes distribution, reminder and review strategies through reinforcement learning according to processing feedback. The application can improve the timeliness, accuracy and controllability of meteorological business mail processing.

The invention discloses a method for explaining an error alarm. The method comprises the following steps of: presenting description information of a plurality of alarm records output by analyzing a code file of a detected item to a user; according to the description information of the multiple alarm records, extracting target code snippets associated with the multiple alarm records and rule description of a target rule; retrieving at least one of a description text of a defect code, a description text of a misinformation scene or an example code snippet identified by the target rule from a knowledge base according to the rule description; according to the description text of the defect code, the description text of the false alarm scene or the example code snippet and the rule description and the target code snippet of the target rule, generating a false alarm conclusion and reason explanation of the multiple alarm records through a language model; and presenting a false alarm conclusion and reason explanation to the user. According to the method, the rule check principle is interpreted through the language model, the program execution process is analyzed and deduced, the reason explanation for generating the misinformation is generated, evidence is provided for the misinformation conclusion, and high availability and reference are achieved.

The application relates to the technical field of offline data collection, and discloses an offline data collection method, system and terminal device, the method comprising the following steps: classifying information contents to be collected, and configuring standardized form templates; meanwhile, corresponding association relationships between different information column categories in the form templates are configured; corresponding form templates are exported according to user categories to be distributed and corresponding permissions of the user categories; offline data files after data collection of respective form templates by the user are subjected to form rule checking and form format checking respectively; form data information of the offline data files is split into information column areas, data column areas and cell areas, and the information of the areas is subjected to rule checking; for data meeting the checking rules, the data is respectively organized according to the divided areas, and the data is stored to a background. The application can realize efficient, reliable and flexibly configurable large-scale data collection and warehousing in an offline scene.

The invention discloses an H5 service long-acting touch method and system based on an enterprise WeChat plug-in, and belongs to the technical field of mobile internet communication. The core of the method comprises the steps that a confirmation operation of a user on a temporary H5 service page is responded, the front end sends a request and closes the page after receiving a successful response, and the rear end calls an enterprise WeChat interface to send an initialization message, so that an independent and resident exclusive session entry is instantiated in the WeChat of the user. According to the invention, a bidirectional interaction closed loop is further constructed, and a user can directly return to an original service H5 page through clicking by sending a rich media service message which can be clicked and jumped to the entry, so that complete service circulation from a webpage to a session to a webpage is realized. According to the method, the problem of temporary and interactive fracture of the H5 service entry is solved, and long-acting and immersive access of the service instance is realized. And the control and reliability of the channel can be further enhanced through mechanisms such as message sending rule verification and asynchronous queues.

The invention belongs to the technical field of data processing, particularly relates to a railway main data verification method, system and equipment based on a multi-rule engine and a storage medium, and aims to solve the problems that rule verification in a railway data base is solidified, the expansibility is poor, and the railway data base cannot adapt to complex business scenes in the prior art. The method comprises the steps that a rule base containing multiple rules is configured, input of data to be verified is received, and verification is executed by a verification engine based on preset groups and priorities. When rule conflicts occur, a multi-strategy conflict resolution mechanism is used for processing, and finally a verification report is generated and displayed. According to the method and the system, configurable management and flexible scheduling of the verification rules are realized, the defects of rule solidification, poor expansibility and the like in a traditional hard coding mode are effectively overcome, and the adaptability and the accuracy of data verification in a complex railway service scene are remarkably improved.

The invention provides a low-code platform model generation method and device, equipment, a medium and a product, and relates to the technical field of artificial intelligence and low-code platform development. The method comprises the following steps: taking an interface type keyword; obtaining an association matching result of the first demand description and the keyword, and obtaining a second demand description according to the matching result; key information is taken from the second demand description, and a third demand description is obtained from the information; describing a first query language according to the third demand; splitting the first query language to obtain each minimum grammar unit, and screening to obtain each effective grammar unit; establishing a syntax tree, and when the syntax tree conforms to a pre-stored syntax rule, performing basic semantic check on the syntax tree to obtain a semantic check result; obtaining a second query language according to the check result; verifying the second query language rule according to a preset rule constraint condition to obtain a third query language; and obtaining a visual data model through the third query language and the low-code platform interface. The seamless connection from the natural language requirement to the visual application is realized, and the technical threshold is reduced.

The invention belongs to the field of computer network content security, particularly relates to a text compliance real-time verification method and system based on a two-dimensional knowledge base, and aims to solve the problems that in the prior art, accuracy and adaptability are difficult to consider at the same time, and scene verification capacity is lacked. The method comprises the following steps: acquiring a to-be-verified text and scene information thereof; generating a scene verification strategy based on the scene information and a preset multi-dimensional feature map; based on a two-dimensional knowledge base, executing two-way parallel verification on the to-be-verified text, the two-dimensional knowledge base comprising an explicit rule knowledge base and a semantic context risk knowledge base, so as to obtain a rule verification result and a semantic verification result; and according to a scenarized verification strategy, performing fusion decision on a rule verification result and a semantic verification result, and outputting a final compliance judgment conclusion. According to the method, the rule model and the semantic model are combined, and the scene dimension is introduced for dynamic intelligent decision making, so that the accuracy and the automation level of text content verification are remarkably improved.

The invention discloses an exhibition venue digital data processing and optimizing method based on cloud computing, and particularly relates to the technical field of electric digital data processing.The method comprises the steps that multi-source heterogeneous dynamic data in a venue is collected and fused with static attributes to construct a dynamically-updated digital twinborn model; generating a global resource state view based on the model, receiving a resource use request, and screening an available resource set through matching and coordination rule verification; constructing a multi-objective optimization function including the resource utilization rate, the system energy consumption and the audience movement efficiency, and solving the Pareto solution set by adopting a multi-objective optimization algorithm to generate a data processing scheme; analyzing the scheme into a control instruction, issuing the control instruction to an execution unit, and realizing dynamic adjustment through a rolling optimization mechanism according to actual feedback; a data processing framework of dynamic data fusion, multi-objective optimization solution and instruction real-time issuing is provided, and the response speed, optimization precision and system energy efficiency of the data processing system in coping with multi-source and dynamic data are effectively improved.