1629 results about "Middleware" patented technology

The invention discloses an unmanned aerial vehicle cluster intelligent cooperative control method, and the method comprises the steps: optimizing a network topology through heterogeneous unmanned aerial vehicle cluster dynamic networking and a dynamic clustering algorithm, and guaranteeing the reliability of a communication link; a layered hybrid decision architecture is designed to improve the task allocation rationality and the dynamic adaptability of the unmanned aerial vehicle cluster; a distributed control strategy network is trained by using a multi-agent near-end strategy optimization MA-PPO algorithm, and unmanned aerial vehicle cluster behavior collaboration is ensured in combination with space-time consistency constraint; an asynchronous incremental consensus protocol AICP is provided, the data transmission amount is reduced, and topology reconstruction is accelerated; real-time three-dimensional environment reconstruction and dynamic threat prediction are realized based on a neural radiation field NeRF technology; a lightweight anti-interference communication middleware is developed, and the instruction transmission stability is enhanced by adopting a space-time coding diversity technology. The method solves the problems of high delay of centralized control of the unmanned aerial vehicle cluster, poor convergence of a distributed algorithm and the like, and is suitable for high-dynamic task scenes such as urban street battle and complex terrain search.

The invention provides a cache information processing method and device of a port platform and a medium, and belongs to the technical field of port distributed information processing. An update request is received, and authentication and flow limiting processing are performed on the request; obtaining a cache key prefix and a data structure type, routing a cache key to a fragment node based on a consumption write-back event, executing a write-in operation in a distributed cache service, and setting survival time and multi-copy synchronization; delivering the message body to the message middleware and obtaining delivery confirmation; the messages are pulled from the queue according to the configured concurrency, deduplication verification is carried out on idempotent identifiers of the messages, and data persistence operation is executed after the verification message version is higher than the current version of the database; index collection points are implanted into all modules of the whole link, and the request delay, the cache hit rate and the message accumulation depth index are visually displayed. The reasonable distribution and optimization of system resources are realized; the consistency and integrity of the data are guaranteed, and the reliability of message transmission is improved at the same time.

The invention discloses an intelligent multi-dimensional automatic inspection operation and maintenance management method, device and equipment, relates to the technical field of network inspection, and aims to solve the problems that the inspection efficiency of network equipment is low and fault early warning is lagged. The method comprises the following steps: scanning equipment in a target machine room to establish an equipment registration file, wherein the registration file comprises an equipment type identifier and an associated inspection strategy template; collecting multi-dimensional data of each registered device according to the inspection strategy template, wherein the multi-dimensional data comprises a hardware operation state, a business middleware state and an environment monitoring parameter; determining abnormal data from the multi-dimensional data according to a preset dynamic threshold value, and generating and issuing graded alarm information according to the influence degree of the abnormal data; and creating a work order according to the abnormal data and automatically distributing the work order so as to process the abnormal data.

The invention discloses a distributed energy collaborative scheduling optimization method based on edge computing. According to the method, a plurality of edge computing nodes are deployed in a distributed energy system, a multi-protocol compatible OPC UA communication channel is constructed through protocol conversion middleware to collect data, and after the edge computing nodes clean and normalize the data, a preliminary scheduling scheme is generated through an improved genetic algorithm; the improved genetic algorithm is optimized through cooperation of a deep reinforcement learning model and an adaptive attenuation mechanism. And uploading the preliminary scheduling scheme to a cloud end, and obtaining a global optimal scheduling strategy through a multi-target particle swarm optimization algorithm. And the cloud carries out credible evidence storage on the global optimal scheduling strategy abstract value through an alliance chain smart contract, and establishes a PoA consensus mechanism. And when the communication is interrupted, the edge computing node starts the local emergency scheduling module, and incremental data synchronization is performed after the communication is recovered. The distributed energy scheduling optimization problem is effectively solved, the energy utilization efficiency is improved, and the system stability and reliability are enhanced.

The invention relates to the field of low-altitude airspace monitoring, and relates to a low-altitude monitoring system based on multi-source heterogeneous perception fusion and rule engine driving, which comprises a perception access layer used for completing data standardization and protocol adaptation and realizing data stream release through message middleware; the processing calculation layer is used for generating a structured alarm event; the application support layer is used for three-dimensional visual interactive display of target situation data and alarm events, unified access of multiple types of sensors such as radar, photoelectricity, radio frequency, ADS-B and meteorological sensors is realized through a plug-in protocol adapter, and target state estimation and track smoothing are realized by combining space-time registration and extended Kalman filtering. The limitation that an existing system can only process a single data source or simple superposition is overcome, and the target recognition precision and the track continuity are remarkably improved.

The invention discloses an equipment data acquisition and query optimization method based on a large model enabling ERP-MES system, and relates to the technical field of integrated enterprise resource planning and monitoring management systems, and the method comprises the following steps: carrying out the dynamic adaptive data acquisition and preprocessing of equipment: employing an edge node to deploy a lightweight noise detection model, identifying an electromagnetic interference mode in sensor data collected by the equipment in real time, and dynamically compensating and correcting by combining environment temperature and humidity data; according to the method, an edge node lightweight noise detection model is combined with environmental data compensation and correction, and a BERT large model is utilized to analyze a protocol document design middleware, so that accurate acquisition and efficient processing functions of dynamic self-adaptive data of equipment are realized; preprocessed data are mapped and fused through a multi-modal large model to construct a unified data warehouse, and a mapping strategy is optimized through reinforcement learning, so that the equipment data quality is improved, and the data fusion and utilization efficiency is enhanced while heterogeneous data fusion is achieved.

The invention provides a cross-protocol identification data intelligent analysis middleware method and system. The method comprises the following steps: taking multiple industrial communication protocol identifiers in advance to form a metadata set, and constructing a protocol feature element model library containing a non-standard protocol feature template; a programmable logic device is introduced, physical layer signal waveform characteristics are matched, and corresponding communication protocol stacks are dynamically switched at a hardware level according to a matching result; receiving a communication data stream through an electric domain processing unit of the programmable logic device, and generating a protocol analysis logic sequence in combination with a state transition rule of the meta-model library and a mode matching rule of the protocol stack; performing combined operation on the structured feature template and the analysis logic sequence to generate an executable cross-protocol data analysis rule; and when unknown protocol characteristics are detected, triggering dynamic reconstruction of the template, so that the analysis rule is adapted to a newly added protocol. According to the technical scheme provided by the invention, the protocol compatibility development cost in an industrial multi-protocol scene is remarkably reduced.

The invention discloses an intelligent operation and maintenance distributed cloud native application computing method, and relates to the technical field of cloud computing, and the method comprises the steps: collecting heterogeneous data of an application layer, a middleware layer, a container layer and a service governance layer, constructing a dynamic multilayer dependency graph, and explicitly modeling a cross-layer dependency relationship and implicit dependency caused by resource competition; based on the spatio-temporal features of the spatio-temporal diagram neural network learning map, predicting a cascade fault risk and outputting a high-risk sub-graph; candidate operation and maintenance operations are generated through reinforcement learning, indirect negative influences of the operations on non-target components are evaluated in combination with a causal inference model, and risk filtering operations are verified through a multi-dimensional safety threshold value; and after the safety operation is executed, continuously optimizing the model and the atlas through a feedback closed loop. According to the method, deep insight, accurate risk prediction and self-adaptive decision making of side effect minimization can be carried out on a complex dependency relationship, and the system stability and the operation and maintenance efficiency are remarkably improved.

The invention discloses a method for realizing SQL (Structured Query Language) grammar conversion of different databases based on middleware and the middleware, belongs to the technical field of databases, and aims to solve the technical problem of how to realize SQL grammar conversion of different databases through the middleware. The following operations are executed through the middleware to realize the grammar conversion of the SQL between the source database and the target data constructing an abstract syntax tree AST by taking various SQL elements as nodes; operating nodes in the AST on the basis of requirements of a target database; based on the data type in the target database, performing data type mapping by applying a data type conversion rule, and generating an SQL statement adapted to the target database; performing security check on the generated SQL statement; caching the query result and the generated SQL statement based on a caching mechanism; and recording the conversion process and query processing of the SQL statement.

The invention discloses a food production traceability management system based on a block chain, which belongs to the field of food management systems, and is characterized in that a unique identifier ID of an inheritor is generated based on an SHA-256 Hash algorithm, a Merkle tree root Hash value of food production data is dynamically associated, a non-tampering digital identity file is constructed, a data island of traditional decentralized management is broken through, and the traceability of food production is improved. According to the technical scheme, full-chain credible association between the non-abandoned technology and the production process is ensured, validity of an electronic signature is automatically verified by means of an intelligent contract, data tampering or identity failure risks are recognized in real time by comparing a public key decryption result with a signature hash value, JSON format alarms are pushed by means of Apache Kafka message middleware, cross-department collaborative response is achieved, and the security and reliability of the electronic signature are improved. The risk prevention and control efficiency is remarkably improved, encryption signature is performed in combination with an ECDSA key pair of a hardware security module, strong binding of an inheritor identifier, a production batch and equipment is ensured, identity fraudulent use or qualification counterfeiting is prevented, and traceability of the whole life cycle of non-abandoned skill inheritance is achieved.

The invention provides an intelligent laboratory full-process collaborative management system and method based on multi-dimensional data fusion, and the method comprises the steps: obtaining an original data stream from laboratory instrument equipment, carrying out the format recognition and conversion of heterogeneous instrument data through a standard protocol adapter, and generating a first data set in a unified format; aiming at the first data set, executing automatic analysis by adopting data middleware, and integrating into a structured second data set based on a metadata rule of field mapping and unit conversion; according to the second data set, a multi-source data fusion model is constructed, data are classified according to instrument types through batch processing and aggregated according to timestamps, and a fused third data set is generated; aiming at the initial process configuration, adjusting a node sequence and a parameter threshold value by using a visual design tool, and generating an optimized process configuration adaptive to the diversified scene; according to the optimized process configuration, process scheduling is executed through a dynamic process engine, execution time and resource occupation are monitored in real time, and a process execution log is generated.

The invention relates to the technical field of industrial internet data processing, in particular to a cross-platform multi-source data integration analysis method and system based on the industrial internet, and the system comprises a data collection layer, a data preprocessing layer, a data integration layer, a data storage layer, an intelligent analysis framework, an application layer and a data security layer. Through the data adapter and middleware technology, efficient collection and integration of multi-source heterogeneous data are achieved, multiple data sources and communication protocols are supported, the compatibility and expansibility of the system are improved, and the system can rapidly adapt to different industrial scenes and data source changes; according to the method, advanced big data and artificial intelligence technologies are applied, a specific analysis model for industrial production is combined, deep analysis can be performed on the data, potential values in the data are mined, an accurate analysis result is provided for equipment fault prediction and production process optimization, and the intelligent level of industrial production is improved.

The invention discloses a logistics carbon emission data monitoring system based on a block chain and edge calculation, and relates to the technical field of logistics systems. According to the logistics carbon emission data monitoring system based on the block chain and edge calculation, on the aspect of data integration and estimation, multi-source heterogeneous data is fused to construct a dynamic compensation model, a lag compensation algorithm is developed, emission factors are adjusted, more accurate real-time carbon emission estimation is achieved, and full-chain data standardization and association are achieved through middleware; in the aspect of privacy protection, the blockchain and zero-knowledge proof technology are combined, enterprise data authenticity verification is ensured, original information is not leaked, a carbon emission result is subjected to chaining evidence storage, original data is encrypted and stored, and cross-enterprise federal learning ensures that data cannot be out of a domain; the logistics carbon emission data monitoring accuracy, privacy protection and auditing supervision intelligent level are improved.

The invention discloses a method and tool for manufacturing a cold shield of a nuclear fusion device, and relates to the technical field of metal plate machining. The manufacturing method of the cold shield of the nuclear fusion device comprises the following steps: providing a sub-panel, a flange and a pipe fitting; the multiple sub-panels are welded, and a first middleware is obtained; welding the edge of the first middleware and the turnup to obtain a second middleware; after the pipe fitting is welded to the surface of the second middleware, a third middleware is obtained; and the third middleware is shaped. According to the method, the third middleware is shaped, that is, the third middleware is shaped after all welding procedures are completed, so that the third middleware has relatively small profile tolerance, the profile tolerance of the cold shield meets the design requirement, the assembly difficulty of the cold shield is reduced, and the risk of failure of the cold shield is reduced.

The invention discloses an intelligent fusion and standardization processing system and method for multi-source heterogeneous operation and maintenance data, and belongs to the technical field of operation and maintenance data. The system comprises a data acquisition module, a data preprocessing module, a data fusion module and an information extraction module; the data acquisition module is used for collecting original multi-source heterogeneous operation and maintenance data from different data sources, and the data sources comprise facilities, operating systems, basic components, middleware, databases and / or information systems; the data preprocessing module is used for cleaning, denoising and standardizing the acquired data; the data fusion module is used for selecting a low-level data fusion model, a middle-level data fusion model or a high-level data fusion model according to the fusion scene and fusing the preprocessed data; and the information extraction module is used for carrying out feature extraction on the fused data. According to the method, deep fusion and standardized processing of the multi-source heterogeneous operation and maintenance data are realized, and a unified and high-quality data basis is provided for data analysis and decision making.

The invention relates to the technical field of mine production operation management, in particular to a mine production operation intelligent decision-making system based on multi-source heterogeneous data fusion. A data preprocessing module; a data fusion modeling module; an intelligent decision module; and a decision execution feedback module. In the scheme, an edge computing terminal is deployed through a data acquisition unit, a multimode communication technology is integrated, data of an underground sensor, electromechanical equipment and the like are accessed in real time, and the data transmission reliability is ensured through a communication quality evaluation formula; the business system interconnection unit maps heterogeneous fields of systems such as ERP, WMS and the like into global unified business keys by means of semantic middleware, and semantic ambiguity is eliminated. The data preprocessing module integrates the dispersed data into a standardized data set through intelligent cleaning, format conversion and three-dimensional association, and provides data support for decision making.

The invention relates to the technical field of distributed response, in particular to a distributed message dynamic response method based on websocket. The method comprises the following steps: constructing a distributed message service cluster to configure a websocket communication module, message middleware and a client for each service node, and providing a unified service access point to the outside through an Nginx load balancer, so as to automatically register and subscribe a global control theme to the message middleware and form a hierarchical theme subscription structure; when the client initiates a connection request, the connection is distributed and a secure channel is established; the client sends a service request message, packages the service request message into a standardized message format, and associates session information of the client at the same time; and receiving the session message, performing intelligent filtering, generating a response result, and pushing the response result to the client in real time. According to the invention, efficient processing and real-time response of messages in a distributed environment can be realized.

The invention discloses a multi-role collaborative management architecture based on RBAC + HIS synchronization, and the architecture comprises a role authority management module which builds a static role authority baseline based on an RBAC model, and associates the real-time organization architecture data of an HIS system through a dynamic rule engine, and generates a multi-level role authority tree; the data synchronization middleware adopts an API gateway to realize one-way data push between the HIS system and the psychological assessment platform, comprises a field-level encryption unit and an incremental data verification unit, and supports isolated transmission of patient medical records, medical advices and assessment tasks according to inpatient areas; the multi-terminal cooperation engine realizes authority mapping of the doctor workstation, the mobile nursing terminal and the patient self-service terminal through distributed session management, a conflict detection mechanism is built in, and a secondary authentication process is triggered when cross-inpatient-area operation is detected. According to the invention, dynamic authority management is realized, data secure transmission and multi-terminal cooperation are guaranteed, auditing tracing is enhanced, and business continuity when the system is abnormal is ensured.

The invention provides a training and examination robot system based on a multi-modal large model, equipment and a computer program product, and aims to accelerate training transformation and upgrading and improve coping ability as basic appeals, and based on regular training work of teams, training and examination robot, sensor acquisition equipment and big data platform three-terminal equipment. A multi-modal data acquisition layer for realizing real-time attitude detection and motion capture by using an edge calculation algorithm, a data processing and analysis layer for finishing real-time image processing through localized edge calculation in a network-free or power-free environment, and system control functions for finishing intelligent decision making, evaluation, error correction and the like are provided; an intelligent decision-making and control layer of a training subject rewriting decision-making mechanism is established, cross-modal collaborative learning middleware is utilized to realize modal representation consistency while training subject transposition evaluation is realized, training and assessment operations of the same subject of multiple persons or different subjects of multiple persons are supported, and the training and assessment efficiency is remarkably improved.

The invention provides a data driving and multi-element cloud edge cooperative computing method for intelligent workshop construction, which comprises the functions of multi-protocol heterogeneous equipment sensing, edge node adaptive load balancing, lightweight real-time edge computing processing, cloud centralized management control, industrial intelligent application service deployment scheduling, cloud edge task unloading and the like. The system comprises a data acquisition and transmission middleware, an edge stream processing engine and a cloud service center. The method has the characteristics of real-time performance, low delay, flexibility, expandability, loose coupling, low resource occupancy, high availability and privacy security.

The invention discloses a project progress, quality and safety collaborative management and control system and method based on BIM and Internet of Things, and belongs to the technical field of constructional engineering informatization management. In order to improve engineering management efficiency and reliability, the system comprises a data acquisition layer, a data processing layer, an application layer and a security module. The data acquisition layer is connected with the data processing layer, the data processing layer is connected with the application layer, and the security module is respectively connected with the data acquisition layer, the data processing layer and the application layer; the data acquisition layer comprises IoT equipment, an external data interface, data middleware and a BIM model, the IoT equipment acquires data through the external data interface, the IoT equipment is connected with the BIM model through the data middleware, and the data processing layer comprises a multi-source data fusion engine and an intelligent algorithm module; the application layer comprises a model management module, a model display module, an early warning management module, a data management module, a three-dimensional visual monitoring platform, an intelligent decision center and a mobile terminal module. The project management efficiency is improved.

The invention relates to a railway material purchasing asynchronous task processing method, device and system, and the method comprises the steps: constructing a six-layer message channel architecture of a purchasing business process, and executing an instruction of deploying a message agent node in an active-active mode for each channel based on the core message middleware of a Kafka cluster; the front-end gateway is instructed to package the purchase event into a binary message body with a transaction ID and a timestamp, and the binary message body is written into a persistent queue after priority labeling is carried out according to a task type label; processing the concurrent tasks by adopting a multi-stage feedback queue scheduling algorithm, and dynamically allocating computing resources based on a thread pool; a maximum retry threshold value is set according to an exponential backoff retry strategy, so that the failed task is automatically transferred into a dead message queue; and dynamically calculating an optimal message routing path based on the supplier portrait and the material classification model, and extracting the order to an exclusive processing queue of the optimal supplier according to Topic dynamic switching of the message queue. According to the invention, the coupling degree is reduced, the system performance is improved, and the fault tolerance is enhanced.

The invention discloses an intelligent monitoring method for a hydrogeological environment, and the method comprises the steps: 1, constructing a space-air-ground integrated sensing network, and dynamically adjusting the monitoring frequency through a self-adaptive sampling strategy; 2, developing cross-platform data middleware, realizing conversion from multi-protocol data to a WaterML 2.0 standard, constructing an anomaly detection model in combination with a deep residual network, and correcting regional parameter deviation; 3, designing a hybrid fusion architecture, processing time sequence data by using an improved Transform at a bottom layer to capture long-term dependence, constructing a graph neural network at a top layer to fuse spatial connectivity, and outputting a prediction result with a confidence interval through an attention mechanism and a Bayesian network; step 4, establishing an edge-cloud hierarchical computing system, deploying lightweight model real-time early warning at an edge end, integrating complex models such as 3D geological modeling at the cloud end to generate a regional report, and adopting federal learning cooperative training and embedding differential privacy protection; and 5, developing a three-dimensional geological visualization platform and an intelligent decision-making system.

The invention discloses a middleware management method and device, relates to the technical field of middleware, and mainly aims to realize unified management and configuration of middleware, reduce the management and maintenance difficulty of the middleware and improve the flexibility and convenience of flow management. According to the main technical scheme, each middleware instance is divided into one or more logic clusters according to operation characteristics of each service, wherein the operation characteristics are used for representing characteristics related to high-reliability operation of the services; general configuration setting is carried out on the one or more logic clusters to obtain global configuration information containing all the logic clusters, and the general configuration setting at least comprises setting of physical mapping and routing strategies of middleware instances docked by all the services in the running process; and respectively issuing the global configuration information to each middleware instance contained in each logic cluster so as to run according to the global configuration information when a service butted with the middleware instance contained in each logic cluster is started. The middleware management method and device are used for middleware management.

The invention provides an industrial control method and system, a medium, equipment and a program product. The method comprises the following steps: generating a control instruction by using a logic control module; the control instruction is transmitted to the equipment driving module; an equipment driving module is used for driving execution equipment to execute corresponding operation of the control instruction; wherein the logic control module and the equipment driving module are physically isolated or isolated by using middleware. In other words, independent operation between the logic control module and the equipment driving module is realized through physical isolation or middleware isolation, so that tasks are ensured to be mutually independent and do not interfere with each other, and the stability and safety of the system are improved. In addition, resource competition between the logic control module and the device driving module can be reduced, delay and conflicts are reduced, and real-time performance is improved. In addition, the logic control module and the equipment driving module can be independently developed, tested and optimized, so that the operation and maintenance cost is reduced.

The invention belongs to the technical field of wireless household electrical appliance intelligence, and discloses a wireless household electrical appliance intelligent identification and analysis method and system based on multi-protocol fusion, which can automatically extract new equipment protocol features through centralized middleware scheduling and adaptive learning mechanism of a protocol adaptation engine unit in combination with dynamic model training of an AI identification center unit. Generating a temporary adaptive interface and updating the protocol template; the dynamic protocol library supports OTA updating, a novel protocol and unknown equipment can be adapted without manual configuration, and the defects that the number of traditional system equipment is increased, and protocol type expansion is blocked are overcome; the intelligent optimization module dynamically adjusts the bandwidth priority and the data reporting frequency based on reinforcement learning and behavior prediction, guarantees smooth communication of key equipment in a high-concurrency scene, reduces standby power consumption of idle equipment, solves the problems of high-concurrency delay and high energy consumption of a traditional system, and improves the system reliability. And double improvement of identification reliability and system energy efficiency is realized.

The invention discloses a high-concurrency real-time message pushing system and method based on an SSE protocol, and relates to the technical field of communication. Comprising the steps of 1, establishing a high-concurrency real-time message pushing system, 2, performing access, heartbeat detection, connection state management and load balancing of a client through an access module, performing dynamic strategy allocation based on tenant ID hash through a load balancer of the access module, routing client requests to different SSE servers, and sending the client requests to the SSE servers. 3, caching and routing management of messages are carried out through a message management module, distributed message middleware kafka is used as a cache queue through the message management module, real-time messages sent by a service system are received, and the messages are stored in a classified mode according to top and Tenant; the connection metadata comprises a connection ID, a client subscription topic and a timestamp, and step 5, monitoring the connection number of each node in real time through a monitoring module, triggering connection migration and message reissuing when the node fails, removing the information of the failed node, and notifying a load balancer to route the original connection to other nodes. And meanwhile, the message management module is notified to re-push the message which is not successfully pushed by the fault node to the new node, so that the message is prevented from being lost.

The invention relates to the technical field of intelligent decision making, can be applied to business scenes such as financial science and technology and medical health, and discloses a routing decision making method, device and equipment for data processing and a medium, and the method comprises the steps: constructing a label strategy SQL training set, and carrying out the supervision training of the SQL training set, and obtaining a trained language model; receiving a to-be-processed SQL task, generating a structured feature vector, generating a routing strategy through a reinforcement learning module, and determining a processing engine of the task; after the execution path identifier is analyzed, the task is distributed to a corresponding engine through message middleware; and generating a feedback data set based on the task execution index and the execution path identifier, and updating the strategy parameter based on the data set. According to the method, the label strategy SQL training set is constructed, decision optimization is carried out in combination with the reinforcement learning module, the optimal processing engine of the calculation task can be judged, calculation overhead and resource waste are reduced, and particularly the calculation performance is improved in a large-scale data processing scene.

The invention relates to the technical field of computers, can be applied to the field of science and technology finance / digital medical treatment, and discloses a back-end system creativity transformation method and device, electronic equipment and a storage medium. The method comprises the following steps: deploying a credential back-end system environment by using a credential server and credential middleware, and physically isolating credential traffic and non-credential traffic; carrying out dynamic segmentation scheduling on the traffic of the credential and credential gateway in the credential and credential environment and the traffic of the non-credential and credential gateway in the non-credential and credential environment; deploying a domestic database, and finishing data migration from the original database to the domestic database through an automatic tool chain; segmenting the traffic to a credential and credential gateway in the credential and credential environment for gray verification, and switching a back-end service chain of the credential and credential environment to a domestic database after the verification is passed; and monitoring the operation performance data of the credential environment in real time, and switching the traffic to the non-credential environment and the original database through the global traffic management tool if an exception occurs. According to the method, the risk controllability and smooth transition of creative transformation are realized.

The invention relates to the cross technical field of artificial intelligence and data retrieval, and particularly provides an RAG question and answer optimization method and device.Firstly, original knowledge documents of various formats and natural language query of a user are received on an input layer, then a knowledge base construction module and a knowledge retrieval module are arranged on a processing layer, and a knowledge retrieval module is arranged on the processing layer; the middleware layer is provided with an MCP Server module and a vector database, the MCP Server module is a standard interface agent, and the vector database is a distributed storage engine for efficient approximate nearest neighbor search and mixed retrieval; and finally, deploying an LLM generation module at an output layer for generating a final answer based on the retrieved enhanced context. Compared with the prior art, the method has the advantages that irrelevant or low-signal-to-noise-ratio knowledge contacted by a large language model (LLM) can be effectively reduced, and the accuracy, the reliability and the practicability of knowledge base questions and answers are comprehensively improved.