67results about How to "Ensure traceability" patented technology

The invention discloses a power production event type identification and grade evaluation method based on artificial intelligence, and belongs to the field of power safety production, and the method comprises the steps: receiving event description information inputted by a user, extracting event key elements through a natural language understanding model, converting the event key elements into query vectors, and obtaining the query vectors; searching related knowledge fragments in a pre-constructed electric power professional knowledge base, combining the event description information, the key elements and the knowledge fragments into enhanced cue words, inputting the enhanced cue words into a large language model subjected to field fine tuning, and finally, performing comprehensive analysis by the large language model to obtain the enhanced cue words. And generating a structured research and judgment result containing the event type, the level, the research and judgment basis and the submission requirement. According to the method, accurate and efficient research and judgment of the electric power security event are realized by fusing the retrieval enhancement generation technology and the field fine tuning large model, and interpretability and traceability of a conclusion are ensured by outputting research and judgment basis through the requirement model.

The invention discloses a generative AI operation decision-making system based on an organization strategy and a vehicle context. A multi-source situation data access module, a strategy knowledge graph construction module, a multi-modal situation fusion module, a generative AI decision module, a digital twinborn simulation verification module, a strategy compliance arbitration module, a decision optimization and explanation generation module and a decision execution and monitoring module are integrated into a closed-loop system. A candidate decision is dynamically generated by structuring an organization strategy and deeply fusing the organization strategy with real-time data, then feasibility and risk are predicted through high-fidelity simulation, high consistency of the decision and a rule is ensured through automatic compliance verification, and finally a reliable decision which is subjected to multi-objective optimization and attached with natural language explanation is output. Therefore, the illusion problem of application of the generative AI to vehicle operation is solved, the defects of lack of constraints and unpredictable output are overcome, and safe, reliable, compliant, controllable, stable and explainable intelligent operation decision is realized.

The invention discloses a remote data management platform for security operation and maintenance service, and belongs to the technical field of computer network security and data operation and maintenance management. The platform comprises a data acquisition module, an access control module, a remote operation and maintenance control module, a data isolation and encryption module, a security auditing and tracing module, an intelligent risk identification module, a strategy decision engine and a visual management interface module. The system adopts a layered deployment architecture, and realizes multi-layer protection, dynamic strategy adjustment and traceable auditing of the whole remote operation and maintenance process through encryption transmission, block chain type log chain, deep learning risk identification and knowledge graph strategy optimization. The platform has the functions of multi-factor authentication, log chain tampering prevention, intelligent risk early warning and strategy self-learning, can effectively prevent unauthorized access and data leakage, improves the safety, intelligence and verifiability of remote operation and maintenance, and is suitable for multi-scene safety operation and maintenance management of medical treatment, energy, government affairs, industrial control and the like.

The invention discloses a full-process visual monitoring and intelligent management method for a glass bracket production line, and relates to the technical field of industrial quality control, and the method comprises the steps: carrying out the continuous image collection of all stations of the glass bracket production line through an image collection unit, and constructing a full-process image data sequence; detecting the size of the glass bracket by using the qualified glass bracket size image database, and judging whether the size is abnormal or not; further performing defect detection on the glass bracket with the normal size, and determining whether an abnormal defect exists or not through pixel value difference analysis; and finally, summarizing the glass brackets with abnormal sizes or defects and related information thereof, and generating a visual quality report, so as to quickly position problems and optimize the production process. The comprehensive monitoring and intelligent management of the glass bracket production process are realized, and the production efficiency and the product quality are improved.

The invention provides a data rule management method and system, electronic equipment and a medium, and the method comprises the steps: obtaining operation information of a user on rule dimensions through a visual editing interface, and obtaining an initial combination rule; performing forward disassembly on the initial combination rule to obtain a normalized atomic item set; performing coverage and conflict detection on the standardized atomic item set to obtain a detection result; and if the detection result is normal, generating an atomic item change set based on the detection result, storing the atomic item change set to an atomic item database, and performing reverse analysis based on the atomic items in the atomic item database to obtain a target combination rule. According to the method, the consistency and the traceability of the data rules in the editing, storing and issuing processes can be ensured.

The application discloses a kind of deep feature bayesian verification electronic evidence comparison method, it is related to electronic data forensics technical field, including, obtaining multi-source electronic evidence data, carries out structured reorganization and feature enhancement to multi-source electronic evidence data, generates enhanced evidence data;Enhanced evidence data is extracted using deep neural network to multi-dimensional deep feature, forms high-dimensional evidence feature vector;By bayesian inference method, the difference probability comparison of high-dimensional evidence feature vector is carried out, and the similarity confidence value is output;Similarity confidence value, deep evidence feature and high-dimensional evidence feature vector are block chain and traceability anchor are stored, and the output tamper-proof verification voucher;Based on tamper-proof verification voucher, similarity confidence value is carried out and is traced back to the grade mapping and verification of acceptance, and generates electronic evidence comparison report.The application is extracted by multidimensional deep feature and bayesian verification double mechanism cooperation, realizes the high-precision comparison of electronic evidence and uncertainty quantification.

The invention provides a manufacturing decision system-oriented modular functional architecture and a collaborative mechanism thereof, and the structural organization and reusable collaboration of a manufacturing decision process are realized by constructing a multi-layer capability system, a functional module system and a standardized behavior interface. The architecture comprises a data interface module, a decision-making target module, a disturbance response module and a fusion decision-making module, and defines a data flow, a control flow and a trigger relationship among the modules. The system completes target expression, constraint analysis, disturbance identification and collaborative decision generation through standardized access of multi-source data such as orders, productivity, materials and processes, and forms an interpretable and executable decision link. According to the invention, modularization, interpretability and intelligent cooperation of the manufacturing decision-making system are realized, and multi-scene and multi-industry manufacturing decision-making application is supported.

The application provides an air traffic control primary radar signal processing automatic test method and system, relates to the radar test field, and solves the technical problems of fragmentation of the prior art process, single evaluation dimension and poor traceability. The method specifically comprises: obtaining radar test data and structured test configuration; recursively analyzing the test configuration to generate an instruction set; loading data and executing signal replay according to the instructions to drive the software; synchronously collecting video data and processing results of each stage to form a multi-dimensional feature sequence; correlating and analyzing the two and extracting features to generate a holographic feature vector sequence; progressively comparing the sequence with a baseline determination model in layers to obtain a test determination result; integrating test item identifiers, video data, multi-dimensional feature sequences, holographic feature vector sequences and test determination results to record and generate a final test log report. An end-to-end automatic, multi-dimensional deep analysis and full-link evidence tracing radar automatic test method is realized.

The invention discloses a TBM double-track tunnel trackless transportation cross-line bypassing cushion layer rapid construction method, and belongs to the technical field of tunnel construction. According to the method, a construction area is divided into a plurality of construction sections in the longitudinal direction of a tunnel, construction and transport vehicle framing and side alternate operation is organized, and parallel cushion layer pouring and trackless transport are achieved; the method comprises the following steps of: performing radar detection and scabbling treatment on the top surface of an inverted arch block during construction preparation; installing a steel plate water stop belt, and penetrating through the ground beam and the drainage blind pipe; a detachable steel pipe is adopted for shaping and constructing a cushion drainage ditch; after a reinforcing mesh is laid, concrete pouring, multi-pass surface finishing, steam and heat preservation curing and temperature and humidity monitoring are conducted; by optimizing the construction organization and technology, the problems that transportation is interrupted, the construction period is long and cracking is prone to occurring in a traditional method are solved, efficient, high-quality and low-interference cushion layer construction is achieved, optimal construction parameters can be scientifically screened by setting a contrast test section, and adaptability is high.

The invention relates to the technical field of data processing, and provides a log data alarm prompting method and device, electronic equipment and a readable storage medium. The method comprises the steps of performing analysis processing on to-be-processed abnormal log data to obtain an attribute field corresponding to the to-be-processed abnormal log data; performing standardization processing on the attribute field to obtain standardized abnormal data; based on a preset alarm template, performing frequency control duplicate removal processing on the standardized abnormal data to obtain a target alarm text; and performing queue transmission on the target alarm text, so that the target alarm text is displayed to the terminal equipment, thereby improving the accuracy and real-time performance of alarm information, enhancing the processing capability of abnormal logs, improving the reliability of alarm notification, improving the operation and maintenance efficiency and the fault repair speed, and improving the user experience. The timeliness and the traceability of the alarm information are ensured through a standardized format and a reliable transmission mechanism, and the service relevance and the system collaboration of the alarm information are enhanced.

The invention discloses a multi-mode operation and maintenance data processing method and device, electronic equipment and a storage medium. The method comprises the following steps: in response to each task request initiated by front-end equipment, generating a task identifier of each task request, the task identifier being a globally unique user experience session identifier; obtaining task operation data of a plurality of modes associated with the task identifier of each task request, wherein the task operation data of each mode is correspondingly acquired from one data source; and with the task identifier of each task request as a main key, aggregating the task operation data of the multiple modals belonging to the same task identifier into the user interaction conversation object corresponding to the task identifier of each task request. According to the technical scheme, the problems of low operation and maintenance data utilization efficiency and low problem positioning efficiency in the prior art can be solved, the scientificity of operation and maintenance decision and the problem troubleshooting efficiency can be improved, and optimization and upgrading of a digital platform and improvement of service quality are promoted.

This application discloses an adaptive inventory management method and apparatus for multi-tenant environments. The method includes: receiving an inventory operation request from a target tenant, the request carrying a target tenant identifier and an operation type; obtaining a target control mode corresponding to the target tenant identifier, including a forced source mode, a weak source mode, and a source-and-no-source coexistence mode. The forced source mode allows the creation of documents associated with upstream orders, the weak source mode allows the creation of multi-source documents and automatically adjusts process nodes, and the source-and-no-source coexistence mode allows both source-based and source-less operations; adjusting the operation permissions of preset business process nodes according to the target control mode to obtain the target business process node adapted to the request; and updating the inventory status based on the operation type and the target business process node to obtain the inventory operation execution result. Using this application, the needs of medium-sized enterprises of different sizes and business models can be adapted to the differentiated requirements of two types of documents under multi-tenant environments.

The invention is applicable to the technical field of information processing, and provides a design consultation service system based on case similarity comparison, comprising: a case database module for storing multi-dimensional design case data including text description, images, 3D models, user feedback data and metadata tags; according to the method, high-precision matching of multi-modal cases is achieved through the similarity comparison module, the accuracy and efficiency of design consultation services are remarkably improved, an embedding extraction unit of the similarity comparison module adopts a multi-modal embedding model, texts, images and 3D models are uniformly converted into vector representation, cross-modal matching is supported, and the accuracy and efficiency of design consultation services are improved. Limitations of traditional keyword retrieval are overcome, a similarity calculation unit applies a weighted cosine similarity algorithm, different modal information is fused, it is ensured that a matching result meets design requirements, and a dynamic weight adjustment sub-module automatically optimizes weight parameters according to historical preferences of a user and provides a personalized matching strategy. And the cross-domain transfer learning subunit realizes transfer of knowledge in the field of building design to the field of product design through fine tuning of a pre-training model.

The invention relates to the technical field of highway charging piles, in particular to a unified consumption linkage service system for highway charging piles, and the system comprises a user interaction module which is used for receiving user position data and a charging pile operation instruction submitted by a user; the charging pile data acquisition module is used for acquiring real-time operation data of each charging pile in the expressway service area; the scheduling verification module is used for generating a charging scheduling instruction; the order processing module is used for calculating the charging metering data of the charging pile corresponding to the target charging pile identifier; the payment management module is used for updating the payment state of the charging order data based on the payment confirmation information; and the invoice filing module is used for outputting charging pile filing information when the payment state of the target to-be-invoiced order is paid and the invoicing state in the to-be-invoiced order is not invoiced. According to the invention, unified consumption linkage service management can be carried out on a plurality of charging piles in the expressway service area, and the response efficiency to the charging request of the user is improved.

This application discloses a rule-constrained decision generation method for a centralized procurement governance hub based on AI. The method includes: receiving a procurement governance task and obtaining a set of rule constraints related to the task; determining a text generation format based on the rule constraint set and calling a decision content generation model to generate initial decision text under the constraints of the rule constraint set and the text generation format; performing multi-dimensional information verification on the initial decision text based on the rule constraint set, and performing rollback and regeneration operations on initial decision texts that fail verification to obtain corrected decision text; associating and storing the verified and corrected decision text with the corresponding rule application path, data source information, and multi-dimensional verification information to form a traceable decision record; and generating a procurement governance decision report based on the decision record. This method ensures the reliability, auditability, and traceability of the procurement governance decision report, reducing procurement governance risks.

The application relates to an anti-GCDFP-15 monoclonal antibody and a preparation method and application thereof, and belongs to the technical field of immunology. The anti-GCDFP-15 monoclonal antibody provided by the application has the amino acid sequence of a heavy chain variable region as shown in SEQ ID NO. 1 and the amino acid sequence of a light chain variable region as shown in SEQ ID NO. 2. The nucleotide sequences of the heavy chain variable region and the light chain variable region of the monoclonal antibody are also provided, and the monoclonal antibody can be prepared by using genetic engineering technology. The monoclonal antibody prepared by the application has the advantages of stable property, high experimental repeatability and high titer, is suitable for immunological detection, and can specifically recognize the GCDFP-15 protein expressed in human skin and breast tissue.

The invention relates to an AI task asynchronous processing method and device, electronic equipment and a readable storage medium. The method comprises the steps of generating a unique task ID in response to a task request from a client, and persisting task metadata to a preset result database; returning an acceptance response containing the task ID to the client, and pushing a task message containing the task ID to an asynchronous message queue; acquiring corresponding input data from a result database based on the task ID; calling an AI reasoning model to perform reasoning calculation on the preprocessed data to obtain a reasoning result; writing the reasoning result and the updated task state back to a result database; and in response to the query request, returning a corresponding task state and a processing result according to the task ID. According to the scheme provided by the invention, the problem of high delay caused by synchronous blocking can be effectively solved, the traceability and the final consistency of the processing process are ensured, and the maintainability and the expandability of the system are effectively improved.

The invention relates to the technical field of power system frequency modulation auxiliary service markets, in particular to a unit frequency modulation auxiliary service market transaction settlement method and system. The method comprises the following steps: acquiring real-time operation data, quotation data and market node electricity price data of a unit from a power grid dispatching center and an electric power spot market system; based on the processed data, adjusting frequency, response time and adjusting precision are extracted to serve as evaluation parameters, and a subjective and objective combination weighting method is adopted to calculate comprehensive performance indexes; sorting the units from low to high according to the sorting prices, and determining bid-winning units and capacities; and a unified weighted average settlement price is calculated, and final settlement is carried out in combination with opportunity cost compensation. According to the method, the problems of insufficient fairness, low efficiency and lack of transparency in existing frequency modulation market transaction settlement are solved, a high-quality and high-price fair market environment is realized through comprehensive performance indexes and a block chain technology, participation of a high-performance unit is stimulated, and the settlement efficiency is improved.

The application discloses a kind of remote sensing time series data analysis method and system considering the spatio-temporal correlation of geographical object, belong to data analysis technical field.The method includes: obtaining multi-source multi-temporal remote sensing image and auxiliary data and pre-processing, generate consistent time series data stack;In three-dimensional space-time domain, image is divided into voxel and is adjacent tracking, identify geographical process object with evolution behavior and record its attribute;Determine the spatio-temporal topological relationship between geographical process object, generate unified spatio-temporal relationship table by composite reasoning;With geographical process object as node, spatio-temporal relationship as edge constructs geographical process object spatio-temporal graph model, extracts and standardizes the attribute characteristics of node and edge;Importance index of each node is calculated by using graph convolution network and topological dynamic mechanism joint modeling.The application realizes closed-loop analysis from data processing, relationship modeling, importance evaluation to decision support, improves the interpretability and decision effectiveness of remote sensing time series change detection.

The present application belongs to the technical field of supply chain management, and particularly relates to a control and sale commodity directional sharing system and method based on permission approval, wherein the method comprises the following steps: S1: in response to a list creation request of a business, obtaining business identity information, target customer information and candidate commodity information; S2: calling a pre-set permission verification engine, and performing pre-position permission verification on the combination of the business, the target customer and the candidate commodity based on a multi-dimensional permission data model; S3: if the verification is passed, the business is allowed to build a sharing list for the target customer from the commodities within the permission range, and a list snapshot ID bound to the list is generated; S4: the built sharing list is submitted to a pre-set approval process; S5: a time-limited sharing link or a two-dimensional code is generated based on the list snapshot ID; and S6: in response to an access request of the target customer through the sharing link or the two-dimensional code.

This application discloses a blockchain-based elevator dispatching data management system, comprising: several elevator terminals, a dispatching server, and several blockchain servers; wherein, the dispatching server includes: a data processing module, which includes: a neural network unit; the input data of the dispatching neural network model of the neural network unit includes dispatching instructions received by the elevator terminals and elevator monitoring data, and the output data of the dispatching neural network model of the neural network unit is elevator dispatching data; a model uploading unit uploads the dispatching neural network model and its input and output data at the same time to the blockchain constructed by the blockchain servers. The advantage of this application is that it provides a blockchain-based elevator dispatching data management system that can effectively manage dispatching and ensure the reliability and traceability of data storage.

This utility model discloses an experimental device for measuring the starting pressure gradient of pulverized coal, relating to the technical field of pulverized coal measuring devices. It includes a storage tank, a feed pipe, an air inlet pipe, a connecting box, a support frame, and an air compressor. The output end of the air compressor is fixedly connected to the connecting box via an air delivery pipe. The connecting box is equipped with a locking mechanism for locking and maintaining the detected data. Through this locking mechanism, this utility model can automatically detect and lock the steadily rising pressure value in the storage tank and the inner cavity of the air inlet pipe during the pressurization of pulverized coal, effectively preventing the detected pressure value from automatically resetting during depressurization. This facilitates maintaining and recording the pressure value under the corresponding state, thereby ensuring the stability and traceability of the pressure data. By conveniently unlocking, the starting pressure gradient of pulverized coal can be remeasured based on the new pressure value, further improving the accuracy and reliability of the measurement.

The application relates to the technical field of natural language processing and intelligent question answering, in particular to an educational administration question answering system based on semantic analysis, which comprises the following modules: a multi-modal input module that receives natural language question text, fuses real-time academic portrait data and system time into an implicit state vector; a semantic analysis module that extracts core intention features and target entity features; a logic verification module that searches for a target rule node in an educational administration logic knowledge graph based on the intention features, and compares and calculates the implicit state vector in time and state constraint conditions; a dynamic response and guidance module that generates graded response content according to a logic feasibility determination result, or generates an alternative suggestion path based on a graph association structure; the application realizes the leap from static information retrieval to dynamic decision assistance, effectively intercepts invalid operations and reduces the cost of manual interpretation.

The invention provides a medicine abnormal toxicity inspection electronic experiment record management system. The system comprises an inspection method management module, an animal management module, an animal data management module and an inspection result management module. Wherein the inspection method management module can carry out design, auditing and version control on a drug abnormal toxicity inspection experiment recording template; the animal management module is used for recording full life cycle data of experimental animals; the animal data management module is used for recording drug abnormal toxicity inspection experiment data; and the inspection result management module is used for generating, auditing and publishing electronic experiment records of drug abnormal toxicity inspection. According to the embodiment of the invention, the system achieves the automatic and full-life-cycle management of the drug abnormal toxicity inspection experiment data, guarantees the primitiveness, authenticity, safety and traceability of the laboratory data, effectively improves the inspection work efficiency, and achieves the comprehensive, scientific, unified, ordered and efficient computerized system management of the inspection data.

The invention discloses an automatic deployment system and method based on OpenStack, and relates to the technical field of cloud computing infrastructure automation, and the method comprises the steps: automatically discovering a newly added physical server through a PXE protocol, and obtaining server hardware information through an IPMI interface; according to the Kickstart configuration template, through a TFTP / HTTP service, completing unattended operation installation of the operating system for the registered physical server; reading an installed physical server and a node role definition thereof, and automatically distributing and configuring an OpenStack core component; respectively and automatically configuring Neutron network topology and managing and distributing a Glane mirror image based on a resource application of a response user; performing approval control based on roles and workflows on a resource creation request of a user; according to the method, the high reliability of the deployment process is ensured by utilizing a state tracking and anti-reentry mechanism, and the efficiency is remarkably improved.

This invention discloses a dual-mode (BeiDou and UWB) collaborative positioning method for rail transit, specifically relating to the field of fusion positioning technology. The method includes the following steps: based on the spatial coverage status of the two types of signals along the train path, a cross-modal distortion discrimination array is constructed to identify trajectory abrupt change regions and dynamically adjust the signal fusion weights; abrupt change points are corrected using a constrained backtracking trajectory fitting algorithm, and pseudo-trajectory points are eliminated by combining the spatial topology of the positioning base station; time-series analysis is performed on the changes in signal fusion weights, and if frequent signal jump trends exist, the relevant fusion weights are lowered to the minimum tolerance threshold to improve trajectory continuity and positioning robustness. This invention achieves accurate identification of trajectory abrupt change regions by constructing a cross-modal distortion discrimination array, effectively corrects abnormal trajectory points by combining dynamic adjustment of fusion weights and a constrained backtracking trajectory fitting algorithm, and suppresses signal jump trends through a time-series analysis mechanism, thereby improving the stability of trajectory fusion and positioning accuracy.

The invention discloses a processing method for industrial internet identification analysis data, and the method specifically comprises the following steps: 1, carrying out the data processing near a device or a sensor, reducing the delay and bandwidth consumption, analyzing the data in real time, generating feedback, achieving the real-time decision through edge calculation, reducing the dependence on a cloud end, and improving the response speed; 2, dynamically adjusting a data stream processing strategy according to a real-time analysis result, preferentially processing important data, reducing unnecessary data processing burden, processing the data by adopting an event-driven mode, and triggering corresponding processing logic based on a specific event; the data transmission delay is reduced, the response time is shortened, the real-time processing capability is improved, unnecessary calculation is reduced, and the resource utilization rate is improved; the data security is enhanced by adopting a block chain technology, and the non-tampering and traceability of the data are ensured; the decision quality is improved through self-adaptive data stream processing, and the strategy is dynamically adjusted through real-time data.

The invention discloses a dynamic safety management and control system and method based on an intelligent lock, and relates to the field of intelligent management and control, firstly, a background management platform generates an authorization data packet according to an operation task and issues the authorization data packet to a key management machine, and after an operator passes identity authentication, an intelligent key obtains authorization and interacts with a target lock; and after the verification is passed, the intelligent key drives the lock to open, reads the physical state of the lock after unlocking, sends state information to the key management machine through the real-time communication module, and finally uploads the state information to a background platform for analysis and database updating. According to the scheme, closed-loop management of authority control, operation verification and state feedback is achieved, safety and management efficiency are improved, real-time synchronization and traceability of the lock state are ensured, and remote monitoring and risk early warning are effectively supported.

The invention provides an electric power science and technology project information question and answer method and system based on retrieval enhancement generation, and the question and answer method is applied to the question and answer system comprising a query coding module, a prefix candidate generation module, a termination position screening module and an answer generation module. The method specifically comprises the following steps: constructing an input prompt by splicing a query operation and an electric power science and technology project document, and performing semantic coding in combination with a language generation model; according to a limited word list decoding strategy, generating a plurality of candidate prefix sequences through the electric power science and technology project document; based on a leapfrogging decoding strategy, obtaining a termination position of each candidate prefix in the electric power science and technology project document, and generating a corresponding candidate text segment; and calculating the semantic correlation between the query operation and each candidate text segment, screening answer information in combination with a corresponding semantic correlation threshold, and outputting the answer information. According to the method, non-block retrieval answering is realized through prefix positioning driven by the dynamic limited word list and leapfrogging type termination position judgment, and the question and answer accuracy and question and answer efficiency are guaranteed.

The invention discloses a new energy battery recovery system and method based on the Internet of Things. The system comprises a data acquisition layer, an edge calculation layer and a cloud platform layer. The data acquisition layer acquires key parameters of a battery in a running state, a charging state and a standing state in real time through an integrated embedded sensor, and uploads the key parameters to the edge calculation layer and the cloud platform through the Internet of Things; the edge calculation layer adopts a dynamic self-adaptive strategy, filters noise in combination with a TS-SFEA algorithm, analyzes voltage-temperature collaborative change by a Pearson's correlation coefficient, constructs a battery health state parameter matrix, and inputs a pre-training model to predict residual life and health level; the cloud platform layer integrates production and use historical data, records full life cycle information of the battery through a block chain technology, and generates an echelon utilization score and a recovery value index based on an AI evaluation model; and when the cycle count is greater than or equal to 500 times, the system triggers a health state reestimation mechanism, and dynamically updates an OCV-SOC mapping table and a parameter matrix to ensure the timeliness of an evaluation result.