225 results about "Intelligent verification" patented technology

The invention relates to the technical field of material verification management, and discloses a government affair material intelligent verification method and system based on machine learning, and the method comprises the steps: obtaining the text information data and verification rules of historical materials; multi-modal feature extraction is carried out; establishing a dynamic verification rule knowledge graph, and verifying the multi-modal features and the target feature points of the text segments to generate a primary verification strategy; performing deep verification processing on the material text fragment to generate a secondary verification strategy; performing third-time verification on the material text fragment subjected to the second-time verification by triggering cross-page feature matching to realize cross-page text fragment association and multi-modal feature fitting so as to generate a third-time verification strategy; performing iterative comparison on the results of the three rounds of verification to generate a credibility score; and the comparison result is adjusted according to the credibility score in combination with the verification risk abnormity assessment, so that a final verification decision strategy can be obtained, and efficient, accurate, dynamic and comprehensive intelligent verification can be realized.

The invention relates to the technical field of operation and maintenance control, can be applied to business scenes of financial science and technology, medical health and the like, and discloses an intelligent equipment configuration changing method and device, equipment and a medium. Generating a preliminary equipment configuration instruction sequence based on the change intention information; rechecking the configuration instruction through the intelligent checking component, and generating a rechecked configuration instruction sequence; sending the rechecked configuration instruction to the target equipment and executing the rechecked configuration instruction; and verifying whether the equipment state meets the expectation, and if not, executing a rollback operation. Configuration accuracy is ensured through knowledge representation, configuration errors are automatically detected and corrected through intelligent verification, configuration efficiency and safety are improved through automatic issuing and state verification, abnormity is quickly recovered through automatic rollback, and reliability and stability of configuration change are improved.

The embodiment of the invention provides a method and system for automatically generating a document based on a template and a large model, and relates to the technical field of document generation, the method comprises the following steps: step S1, a user inputs information through a browser interface and uploads a to-be-reviewed file; step S2, analyzing the uploaded multi-modal file and extracting structured data; s3, outputting a standardized template instance file according to the decision tree dynamic combination template; s4, calling a large model to generate a project background and a file content abstract; s5, the generated content is rendered and combined with the attachment to form a complete conference review file; s6, executing cross-document consistency intelligent verification and executing intelligent error correction; and S7, generating and storing a final document with version traceability information. According to the method, on the basis of the document template and the large model capacity, document formats are unified, content is accurately generated, and the document writing efficiency is remarkably improved.

The invention relates to the technical field of block chains, and discloses a block chain and privacy computing collaborative verification system, which comprises a data fragmentation module, a privacy fusion module, a collaborative verification module, a consensus correction module and a fragmentation graph optimization module. The data fragmentation module constructs a multi-stage data collaborative topology through a preprocessing node and a dynamic fragmentation protocol; the privacy fusion module realizes privacy protection by using a ciphertext analysis unit to switch links in a multi-state manner and a zero-knowledge verification unit; a collaborative verification module generates a reference verification strategy through a consensus modeling node multi-dimensional fusion model, and a state optimization unit dynamically aggregates and sorts fragmentation states; the consensus correction module corrects the fragmentation state through an isolation verification unit and a delay compensation unit and calibrates ciphertext parameters; and the fragment atlas optimization module constructs a stability evaluation network monitoring synchronization rate and performs closed-loop adjustment on a verification strategy. The system realizes dynamic fragmentation, privacy fusion and intelligent verification, and improves the efficiency, security and stability of block chain data processing.

The invention discloses a medical inquiry logic chain generation and verification method and system based on a large language model, and relates to the technical field of artificial intelligence, the method comprises the following steps: S1, generating a logic chain framework, constructing a medical inquiry logic chain generation model, and embedding a structured logic template and professional knowledge constraints by taking the large language model as a core engine; s2, designing a two-dimensional multi-level verification framework, and performing automatic verification on the consistency and medical rationality of the generated corpus logic chain; and S3, designing an evaluation index system and a dynamic optimization strategy, carrying out grading marking on the problem corpus identified in verification, carrying out corresponding correction, feeding back a correction result to a model training link, and optimizing a logic chain generation rule. Through an NLP technology, a language model generation mechanism, medical knowledge structure analysis and an intelligent verification algorithm, the quality and the structuring degree of a medical inquiry data set and the application value of the medical inquiry data set in an intelligent inquiry system are improved, and high-quality and controllable professional corpus support is provided.

The invention discloses an integrated power supply test method and system integrating fault prediction, and relates to the technical field of power supply test. A comprehensive power supply test system integrating fault prediction comprises a test parameter acquisition module, a reference state updating module, a data fusion module, a fault prediction module and a retest recording module. According to the method, the first prediction channel and the second prediction channel are arranged, and the model path is flexibly selected in combination with the initial anomaly judgment result, so that the prediction accuracy is improved while the prediction efficiency is ensured, and operation requirements in different complexity scenes are met; by setting a circulation analysis mechanism and a dynamic circulation limit value and based on weight increasing operation of a maximum influence data item, intelligent verification and self-adaptive adjustment of model result consistency are realized, and the stability and robustness of a fault judgment process are enhanced.

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 an intelligent verification system and method for full-process review based on multi-modal analysis, and belongs to the technical field of intelligent review. Comprising a processing analysis module, an experiment extraction module, a risk early warning module, a reproduction verification module, a chart comparison module, a dispute tracing module, a feedback analysis module, a load monitoring module, a report generation module and a preference analysis module. According to the invention, comprehensive and multi-angle intelligent review can be realized, more detailed risk early warning and positioning information can be generated, the experiment reproducibility can be quickly verified at low cost, the manual verification burden is greatly reduced, the innovation and risk of the thesis viewpoint are scientifically evaluated, the fatigue of a manuscript reviewer is relieved, the manuscript review efficiency and quality are improved, and the method is suitable for popularization and application. And dynamically adjusting the review content recommendation sequence.

The invention provides a data security management method and device based on a large model and a storage medium, relates to the field of data security management, and obtains access request information and identity information of a data requester and performs identity verification and auditing. Specifically, firstly, deep fusion and joint verification are carried out through an intelligent verification module so as to understand and process a complex relationship between an identity and a request intention; then, dynamically generating an NFT which has uniqueness and represents specific data access authority, and sending the NFT to a requester; when a requester subsequently initiates an actual data access operation, the authenticity and validity of the NFT are strictly verified, and all access attempts (whether the access attempts are successful or not) and permission changes are recorded on a non-tampering block chain, so that dynamic, fine and highly-credible data access authorization and full-process tracing are realized.

The invention relates to the technical field of power systems, and discloses an automatic checking and correcting system and method for relay protection setting values of a booster station, and the system comprises a configuration analysis module which is used for analyzing an SCD configuration file of a transformer substation, extracting parameters of a protection device, and importing a setting value list to establish a mapping relation table; the data acquisition module is used for acquiring a constant value, a soft pressing plate state and a communication message of the IED equipment in real time through an MMS protocol; and the intelligent verification module is used for executing constant value comparison, pressing plate state verification and communication abnormity responsibility judgment. The invention develops a handheld intelligent inspection system, and solves the three major problems of low efficiency, high error rate and prominent safety risk in the checking operation of the relay protection constant value of the traditional transformer substation. According to the scheme, full-process automation of configuration analysis, data acquisition, intelligent verification, safety correction and report generation is realized, so that the routing inspection of the secondary equipment is upgraded from an extensive mode to a precise operation and maintenance normal form, and a guarantee is provided for safe and stable operation of a power grid.

The invention discloses an intelligent verification method for multi-dimensional scene perception, and the method comprises the steps: obtaining the field service data, edge calculation environment information and network state information of a power supply station, and constructing a multi-dimensional scene feature vector; based on the multi-dimensional scene feature vector, constructing a meta-confidence model by adopting a feature progressive strategy, and based on the meta-confidence model, generating initial confidence, decision suggestions and decision context information of an edge calculation result; a cloud verification result is received, decision context information is combined, a time sequence memory module and an error propagation graph are constructed, and a verification feedback optimization instruction and predictive feedback buffer data are generated; and updating the meta-confidence model based on the verification feedback optimization instruction and the predictive feedback buffer data, and executing a final decision in combination with the initial confidence and the decision suggestion to generate a service execution report. The problem of cold start and the problem of low efficiency of asynchronous verification are solved through a feature progressive structure and a predictive feedback buffer mechanism.

The invention discloses a safety evacuation compliance verification method, device and equipment and a storage medium, and the method comprises the steps: building a station BIM three-dimensional information model based on integrated multi-specialty design data, and the multi-specialty design data comprises design data of buildings, structures and equipment; and intelligently comparing the spatial layout information in the BIM model with a preset specialty standard database and a safety evacuation standard database to verify whether a safety evacuation scheme coordinated by each specialty accords with a standard index or not. According to the invention, intelligent verification of subway station safety evacuation design is realized, the examination efficiency of the design scheme is obviously improved, the design period is shortened, the manual examination cost is reduced, and reliable technical guarantee is provided for subway fire safety.

The invention discloses an intangible cultural heritage traceability system, and relates to the technical field of intangible cultural heritage protection. Comprising an authentication module used for non-abandoned inheritors' qualification auditing and non-abandoned artwork multi-dimensional feature evidence storage, and generating a production certificate containing a block chain traceability code; the traceability comparison module is used for realizing intelligent comparison of artwork images, process parameters and evidence information and three-in-one consistency verification of real objects, certificates and packages on the basis of a large model algorithm; and the sharing feedback module is used for non-perpetual culture sharing and anti-counterfeiting data iterative optimization. According to the non-abandoned artwork traceability system, decentralized evidence storage of non-abandoned inheritors' qualification is realized through a block chain technology, manual auditing and intelligent verification are combined, it is ensured that a'person-art 'relationship cannot be tampered, authoritative and credible identity binding is established from a creation source, and the core problem of lack of production subject authentication in the prior art is solved.

The invention discloses a model intelligent verification and parameter correction method, which comprises the following steps of 1, building an unmanned ship task high-value verification point set based on expert experience and a large model collaboratively, screening boundary points and extreme points, and performing simulation-actual measurement data consistency verification; if the normalization error of the simulation data and the actual measurement data exceeds a threshold value, triggering correction; step 2, constructing a sensitive factor set according to global sensitivity analysis and a parameter association relationship mining result, screening high-sensitivity parameters as a priority correction target, and avoiding redundancy optimization; and step 3, optimizing the high-sensitivity parameters, and forming a verification-correction-update closed loop by verifying and iteratively updating the priority of the factors to realize the intelligent correction of the parameters of the unmanned ship model.

The invention provides a high-precision telemetering terminal data acquisition system and method based on multi-source sensor fusion. A high-precision telemetering terminal data acquisition system based on multi-source sensor fusion comprises a multi-source sensor module which is composed of a water level sensor, a flow sensor, a water quality sensor, a meteorological sensor and a vibration sensor, and all the sensors are connected with a main control unit through standardized interfaces; the system comprises a data fusion processing unit, a dynamic priority scheduling module, an edge computing unit, a multi-channel communication module and an anti-interference power management module. The high-precision telemetering terminal data acquisition system and method based on multi-source sensor fusion have the advantages that the centimeter-level precision of hydrological data can be achieved through multi-source dynamic fusion and intelligent verification, the availability of communication is improved, and meanwhile the operation and maintenance cost can be reduced.

The invention discloses a standard information physical examination table intelligent verification method and system based on data automation, and the method comprises the steps: generating standard candidate data of a target field through a data collection step and data standardization processing, and carrying out the screening, and obtaining a standard data set; determining the dependency relationship between the fields of the physical examination table, mapping the standardized data values to the corresponding positions of the fields of the physical examination table through a field mapping function, and generating the physical examination table through data verification and automatic correction; analyzing the relationship between the fields of the physical examination table to predict and generate a filling suggestion value, and generating a filling suggestion list through regularization item correction and verification; inputting the physical examination table data input and modification of the doctor, and generating a final physical examination table draft; and performing consistency verification and medical compliance verification on the final physical examination table draft to generate a formal physical examination table. Through data integration, structured mapping and context reasoning filling, the filling efficiency, data integrity and medical compliance of the physical examination table are improved, and the workload of doctors is relieved.

The invention relates to a simulation method and device for a hydraulic support column descending and support moving dust production migration rule, and belongs to the technical field of coal mine dust control. In order to solve the problems that the prediction error of an existing model exceeds 40%, the migration path deviation exceeds 50%, the side seam adjusting precision of the device is + / -20 mm, and the dust falling efficiency fluctuates by 35%, a multi-factor coupling modeling and intelligent dynamic regulation and control technology is provided. The method comprises the following steps: constructing a dust production prediction model of coal rock hardness, water content, roof pressure bearing and side seam spacing coupling, monitoring dust distribution in real time by adopting a laser scattering sensor and a particle size spectrometer array, designing a high-precision electric push rod to adjust the side seam spacing to + / -0.5 mm, and dynamically correcting an error in combination with Kalman filtering. The device comprises an adjustable support assembly, a triaxial pressure loading module and an intelligent verification system. The dust production prediction error is 9.8%, the migration deviation is 14.6%, the adjusting efficiency is improved by 3.2 times, the dust falling fluctuation is compressed to 7.9%, and the respiratory dust inhibition rate reaches 85.4%.

The invention discloses a bank and medical interface adaptation method, system and device based on multi-protocol adaptation and intelligent verification and a medium, mainly relates to the technical field of interface adaptation, and is used for solving the problem that a traditional interface adaptation scheme lacks a unified configuration management and protocol adaptation mechanism, and the configuration management and protocol adaptation are not uniform in the parameter transmission process. And calling failure is often caused by the problems of non-standard format, field missing and the like. Comprising the steps of configuring a corresponding communication protocol based on an interface definition of a target system; constructing a standardized request body according to the interface definition; obtaining a verification rule corresponding to the standardized request body, and verifying the field integrity and format requirements of the standardized request body through the verification rule; when an interface calling request is triggered, transmitting a standardized request body meeting field integrity and format requirements to a target system corresponding to interface calling through a communication protocol; obtaining return data of the target system; performing formatting analysis on the returned data to obtain analyzed data; and extracting a return result from the analyzed data.

The embodiment of the invention discloses an interface verification method and device, equipment and a program product. The interface verification method comprises the steps of obtaining an interface request parameter of a to-be-verified interface and an interface response parameter output after the to-be-verified interface processes the interface request parameter; the interface request parameters are input into an interface verification model obtained through pre-training, expected response parameters are output through the interface verification model, and the interface verification model is obtained through training on the basis of sample data sets covering different service scenes and different types of interfaces; and the verification result of the to-be-verified interface is determined based on the difference between the interface response parameter and the expected response parameter, so that intelligent verification of the interface can be realized, and the interface verification efficiency and the accuracy of the interface verification result can be improved.

The invention provides a multi-format document analysis and verification method and system and a program product, and relates to the technical field of document processing and intelligent verification. The method adopts a layered modular architecture, and comprises the following steps: a document analysis layer selects an analysis strategy according to document types and complexity, and uniformly converts various formats of documents such as PDF, Word, Excel and the like into a Markdown intermediate format; the index extraction layer uses an abstract base class and a dynamic Prompt optimization mechanism to extract structured data from an intermediate document and integrate the structured data into a unified JSON format to realize complete decoupling of data extraction and rule verification; and the rule verification layer dynamically loads a business rule by scanning an independent file, constructs a rule-dependent directed acyclic graph, and determines an execution sequence by utilizing topological sorting. According to the method, the problems of high data and rule coupling degree, high maintenance cost and poor expansibility in an existing system are effectively solved, hot plugging of the rules, dependency on automatic management and multi-document concurrent processing are realized, and the reusability and execution efficiency of the system are remarkably improved.

The invention relates to the technical field of data management systems and methods of classification numbers G06Q, and provides a traceable management system and method based on an aquaculture industry service platform. Comprising a server, a mobile data anchoring device, a detachable traceability label module, a life cycle state management module, an event hash and anchor verification module and a block chain intelligent verification module. The detachable traceability label module is used for identifying the identity and life cycle state of a breeding individual and triggering a state change event in a disassembly behavior; the mobile data anchoring device collects data of the key node and forms an anchor point record; the life cycle state management module maintains a life cycle logic state diagram of each individual and verifies whether uploading of all events is compliant or not; the event hash and anchor verification module encapsulates all behavior nodes into a structured hash event, and compares and verifies the structured hash event with a current state diagram to form a credible anchor; and the block chain intelligent verification module performs contract-level verification on the event hash and the state path.

The invention relates to the field of construction engineering cost, in particular to a fabricated building-oriented component-level cost intelligent verification method and system, which perform text analysis through a deep learning model, significantly improve the accuracy of component identification, obtain a cost file and component information of a fabricated building project, and improve the verification efficiency of the fabricated building project. Performing text analysis on the cost file based on a deep learning model, and identifying component description and cost data; multi-dimensional feature vectors of the components are extracted, and a multi-dimensional relation graph reflecting the relation between the components is constructed; on the basis of the multi-dimensional feature vectors and the multi-dimensional relation graph, the actual cost and the budget cost of the component are calculated, and according to the difference between the actual cost and the budget cost, a multi-level deviation calculation system is constructed for difference analysis; establishing a hierarchical early warning mechanism according to the difference analysis result, and generating early warning information when the deviation exceeds a preset threshold value; a deep learning model is introduced, and the accuracy of component recognition is improved from about 85% of traditional manual recognition to 95% or above.

A memory device has control circuitry that is configured to perform a smart verify operation on the memory cells of a selected word line to acquire an initial programming voltage for programming subsequent word lines. Following completion of the smart verify operation, the control circuitry is configured to adjust a programming voltage by both a step size or one half of a step size and also an offset and then continue programming the memory cells of the selected word line.

The invention relates to the technical field of bridge monitoring, in particular to a medium and small span bridge strain intelligent verification and diagnosis method and system combined with refined space axle load. According to the method, a space-time distribution matrix of the vehicle axle load of the actual traffic flow on the multi-beam medium and small bridges is established based on a data driving method, an implementation process for converting time-discontinuous discrete dynamic weighing monitoring data into a time sequence of the vehicle axle load is provided, and reference is provided for engineering application. According to the method, the bridge is innovatively divided according to the longitudinal area to achieve linkage calculation of the time sequence of the vehicle axle load and the theoretical strain value of the key section of any main beam of the small and medium-sized bridge, and the strain-based safety condition evaluation index of the small and medium-sized bridges is established by combining the strain monitoring data of the key section of the small and medium-sized span bridge. According to the method, the bridge health monitoring data are effectively mined, the value of the multi-source monitoring data is fully utilized, and the rationality and reliability of bridge safety evaluation are effectively improved.

The invention discloses a whole-process intelligent unit testing method driven by a large language model, belongs to the technical field of software testing, and aims to solve the problems of poor testing quality, difficulty in effective understanding of testing intentions and low coverage rate of testing codes in existing unit testing. The method comprises the following steps: intelligently analyzing a to-be-tested code driven by a large language model; automatically generating a test code driven by the large language model; testing code intelligent verification driven by the large language model; error codes driven by the large language model are automatically repaired; and automatic construction of a test suite and intelligent evaluation driven by a large language model. According to the method, the advantages of the large language model in the aspects of natural language understanding and code generation are fully played, so that the large language model can more accurately grasp the test intention and the function requirement, the generation quality and the coverage range of the test code are remarkably improved, and a brand new solution is provided for realizing efficient, intelligent and whole-process automatic unit test generation.

The invention discloses a two-ticket operation ticket intelligent verification execution system driven by AR glasses, and belongs to the technical field of electric power operation and maintenance. The system comprises an operation order verification module, a risk assessment module, an AR task interaction module, an execution confirmation module and a system central control module. The operation order verification module performs format normalization and step sequence logicality verification on the operation order, and after the verification is passed, the operation steps are decomposed into operation sub-steps to be stored in a step library; the risk assessment module performs risk scoring on each operation sub-step to obtain a risk value of each operation sub-step; the AR task interaction module identifies target equipment through AR glasses and presents operation sub-steps and risk values; the execution confirmation module receives the sub-step interaction completion instruction; and the system central control module realizes module asynchronous communication and pushes the next operation sub-step. The AR technology is combined with intelligent verification, the operation ticket execution process is standardized, the operation risk is prompted in real time, and the standardization, safety and efficiency of electric power operation and maintenance operation are improved.

The embodiment of the invention discloses a buried point verification method and device, electronic equipment and a computer readable storage medium, and relates to the technical field of buried points. The method comprises the following steps: acquiring a burying point application form; performing intelligent verification on the burying point application form to obtain a structured parameter table and business metadata; inputting the structured parameters and the business metadata into a semantic analysis engine to obtain a parameter semantic tree of the burying point application form; obtaining a dynamic verification rule generated by a dynamic rule generator; the dynamic rule generator is obtained by training based on a historical burying point log; and verifying the parameter semantic tree of the burying point application form based on the dynamic verification rule to obtain a burying point verification result. According to the scheme, buried point verification can be automatically carried out based on the dynamic verification rule.

The invention belongs to the technical field of concrete, and discloses a concrete proportion automatic checking method, device and equipment and a storage medium. The method comprises the following steps: acquiring original matching parameters of a to-be-checked concrete matching ratio, and acquiring field dynamic interference parameters in real time through a sensor; carrying out field performance test on the actual concrete mixture to obtain actually measured working performance data and initial strength data; performing compressive strength simulation on the original proportioning parameters and the field dynamic interference parameters through a strength prediction model to obtain theoretical strength data; comparing the actually measured working performance data and the initial strength data with theoretical strength data to obtain a strength verification result; calling a corresponding checking rule from a preset checking rule base based on the field dynamic interference parameter; and performing automatic checking based on the strength checking result, the checking rule and the original matching parameters. By means of the method, static manual judgment is converted into dynamic intelligent verification, and the checking efficiency and precision are improved.

The invention provides an automatic data verification method and device based on a dynamic threshold value, and relates to the field of data verification, and the method comprises the steps: carrying out the standardized mapping processing of obtained multi-source to-be-verified data, and obtaining standard to-be-verified data and corresponding feature attributes; matching a corresponding dynamic threshold prediction model according to the characteristic attributes of the standard to-be-tested data; wherein the dynamic threshold prediction model comprises an extreme value matrix prediction model constructed based on multi-source historical data, a year-on-year-on-year prediction model and a graph correlation verification model; and inputting the standard to-be-verified data into a corresponding dynamic threshold prediction model for automatic data verification to obtain an automatic verification result. According to the method, intelligent verification of data quality can be realized by constructing a dynamic threshold learning system and a multi-dimensional verification engine.