98 results about "Data access layer" patented technology

The invention relates to an enterprise data operation multi-source data virtualization access and index automatic management and control method and system, belongs to the technical field of computers, and aims to solve the problems of index definition fragmentation, frequent logic conflicts, dependency static management and verification rule rigid coupling in the prior art. Comprising the following steps: constructing a unified virtualized data access layer to integrate heterogeneous data sources; the indexes are disassembled into semantic atoms capable of being managed in a versioning mode and registered to an atom knowledge base; dynamically constructing an index dependency relation directed acyclic graph based on semantic atom combination; dynamically binding the data quality rules with semantic atoms; and analyzing an index request through a virtualized query engine, reversely traversing atlas aggregation dependency and rules, generating and executing local query, and automatically checking result data quality at the same time. According to the method, unified index definition, dependence on automatic conduction, quality embedded verification and multi-source transparent access are realized, and the data consistency, the treatment efficiency and the system flexibility are remarkably improved.

The invention relates to the technical field of network security, and discloses a data desensitization and access control method based on data consanguinity and sensitivity identification, which comprises the following steps of: constructing a data consanguinity graph for describing derivation, circulation and dependency relationships among fields; identifying a sensitivity level of each field based on a field consanguinity context provided by the graph; in response to a data access request of a user, dynamically generating an access control strategy for the target field in combination with a service scene, a user role and the sensitivity level of the target field, the strategy specifying access permission, access denial or access after desensitization; and executing the strategy through a data interceptor deployed in a data access key layer, releasing and shielding the data or outputting the data after real-time desensitization by calling a specified algorithm. According to the invention, accurate identification and dynamic and consistent fine-grained access control of the sensitivity of the network data are realized, and the security protection capability of the network data is improved.

The invention relates to the technical field of power system data processing, and discloses a meteorological data collection method based on a power grid prediction demand. The problems that existing meteorological data sources are high in isomerism, the preprocessing process is repeated, the labor amount is large, unified standards are lacked, and the self-repairing capacity is insufficient are solved. The method comprises the following steps: constructing a multi-source meteorological data access layer and carrying out unified space-time reference conversion; analyzing a power grid prediction task demand, and dynamically matching and splicing the preprocessing sub-architecture units; executing the customized preprocessing assembly line to generate a numerical mapping graph; performing logic consistency repair on missing or abnormal data; and outputting the numerical mapping graph after integrity restoration to a power grid prediction model interface. According to the technical scheme, unification and adaptation of multi-source heterogeneous meteorological data at the acquisition end according to needs can be achieved, data processing flexibility and expandability are improved, data integrity and physical consistency are guaranteed, and power grid prediction precision and response speed are improved.

The invention discloses an enterprise data asset right confirmation traceability method based on a data-real fusion technology, and particularly relates to the technical field of enterprise data asset management. The core structure of the method comprises a data access layer, a data processing layer, an identification management module, a right confirmation registration module and a traceability tracking module. The data access layer receives multi-modal original data; the data processing layer performs standardized preprocessing and generates data fingerprints; the identifier management module generates a globally unique digital identifier based on a composite coding rule; the right confirmation registration module binds the ownership information with the identifier and performs block chain evidence storage through a multi-chain architecture; and the traceability tracking module analyzes the data full-life-cycle operation log based on the graphical database. Uniform identification, credible right confirmation and deep traceability of the multi-source heterogeneous data assets are realized, and the core problems of unclear ownership and difficulty in traceability of the data assets are solved.

The invention aims to provide the intelligent switching operation ticket forming system and method based on the large model, which are high in efficiency, high in accuracy and low in cost. The system comprises a data access layer (1), a knowledge support layer (2), an intelligent agent execution layer (3), an application layer (4) and a self-learning optimization layer (5). The method comprises the following steps: S1, a data access layer obtains a scheduling instruction and equipment real-time data and transmits the scheduling instruction and the equipment real-time data to an intelligent agent execution layer; s2, an instruction analysis agent (31) analyzes the scheduling instruction to generate structured feature parameters; s3, the statement generation agent (32) generates an operation ticket first draft in combination with the feature parameters, the topological data and the finished ticket knowledge base; s4, performing logic, normative and multi-ticket comparison verification on the first draft by the verification agent (33), and outputting a verification result; and S5, the application layer displays the operation order passing the verification, and feeds back the data to the self-learning optimization layer to update the system. The method is applied to the technical field of power system operation and maintenance intelligentization.

A transaction system receives a transaction request for a database service. The transaction system retrieves, by a first microservice, a set of data from a data access layer of the database service in response to receiving the transaction request. The transaction system performs a set of computations based on the set of data retrieved from the data access layer. The transaction system stores the set of computations in one or more cache nodes of a data access service and accesses, by a second microservice, the set of computations, performed in response to retrieving the set of data by the first microservice, from the one or more cache nodes.

The invention belongs to the field of artificial intelligence, particularly relates to an integrated artificial intelligence analysis and modeling platform supporting large-scale data processing, and aims to solve the problems of low resource scheduling efficiency, model training reasoning splitting, data algorithm coupling, limited cross-modal modeling and the like under high-dimensional heterogeneous mass data. The platform comprises a distributed data access layer, a unified metadata governance engine, a heterogeneous computing resource scheduling center, a model life cycle management module, a multi-modal fusion modeling framework and a dynamic service orchestration interface, and realizes automatic data access governance, dynamic resource scheduling, model full-cycle management and control and cross-modal intelligent fusion. And the resource utilization rate, the modeling accuracy and the service deployment efficiency are remarkably improved.

The invention discloses a multi-strategy fusion file data desensitization management and control system, and relates to the technical field of information security and data processing, a system architecture adopts a hierarchical design and comprises a presentation layer, a business logic layer and a data access layer, the interface design of the presentation layer is simple, and a user can easily operate the presentation layer; the business logic layer is responsible for processing various rules and ensuring that data can be correctly processed; the data access layer is responsible for interacting with a database to realize secure storage and quick reading of data, and the architecture design ensures the expandability and maintainability of the data desensitization file security management system; system functions are realized in two ways: a common user can perform desensitization operation on sensitive data and download a file; an administrator can modify configuration and manage the desensitization rule besides the functions of a common user; the system can effectively protect sensitive data and reduce the risk of data leakage, and has high practical value.

The invention discloses a model-based micro-service multi-source heterogeneous unified query system and method, and the system comprises a unified data access layer abstract interface which provides a standardized API for a developer to call; according to the model abstraction layer driven by metadata, a three-level metadata structure comprising a BizModel, a BizDataTable and a BizField is adopted for decoupling service logic and physical storage, and multi-source heterogeneous data association crossing MySQL / MongoDB / Elasticsearch / NoSQL is supported through RelativeSource metadata; the declarative query interface is combined with the dynamic SQL generator, provides a chain type API to construct a cross-service query condition, and automatically generates a query statement meeting a target database standard according to a preset data model; and the routing decision module distributes a query request to local execution and remote calling, and supports a plug-in expansion data source dialect generator.

The invention discloses a data warehouse intelligent construction and management method and system, and belongs to the technical field of data warehouse construction and management, and the data warehouse intelligent construction and management method comprises the steps: obtaining an enterprise data source, and extracting the feature parameters of the data source; constructing a data warehouse logic model; self-adaptive ETL configuration parameters are defined; constructing a three-layer physical architecture comprising a data access layer, a data storage layer and a data service layer; intelligent cache strategy configuration is executed based on a deep learning algorithm, a three-level cache architecture is established, and a pre-cache rule and a failure strategy are defined; and running management optimization is implemented through a multi-objective optimization function. According to the method, the construction automation level is remarkably improved, the cache hit rate is increased, the average query response time is shortened, the data consistency and the system performance are effectively balanced, the elastic adaptive capacity of the system is enhanced, the operation and maintenance complexity and cost are reduced, and meanwhile efficient sharing of cache resources is achieved on the premise that data security isolation is guaranteed.

The application provides an extension method and device of a WEB service public component, electronic equipment and a storage medium. The public component includes a controller layer for parameter exchange with the outside world, a service layer for service under the call of the controller layer, and a data access layer for operating a database under the call of the service layer. The controller layer is not inheritable. The business logic of the public component is concentrated in the service layer. The method includes: creating an extension project dependent on the public component by depending on the service layer or the data access layer; deploying an extension service into the extension project by depending on the service layer; and configuring the extension project based on a startup class of the public component, so as to trigger the public component to provide the extension service based on the startup class of the public component. The application embodiment realizes zero-invasion strong extension of the WEB service public component.

The invention relates to the technical field of archive management, in particular to a material collection contract archive whole-process collection system based on a large model agent. The system comprises a data access layer, an intelligent processing layer, a knowledge service layer, an application layer and a security compliance layer which are in communication connection in sequence. The data access layer is used for collecting multi-source heterogeneous contract data and pushing a collection result to the intelligent processing layer; and the intelligent processing layer realizes intelligent analysis, verification, state tracking and knowledge association of contract data based on a large model agent. The objective of the invention is to provide a material collection contract archive full-process collection system based on a large model agent, and by constructing a technical architecture integrating data collection, intelligent processing, knowledge precipitation and closed-loop management, automatic and intelligent management of a full life cycle from generation to archiving of contract archives is realized.

The invention discloses a decision-making system and method based on a Dores database, and the system comprises a data access layer which is used for accessing multi-source heterogeneous financial data in real time, a Dores storage calculation layer, and achieves the data storage, column-type bucket separation and materialized view pre-calculation based on the Dores database; the visual application layer is used for providing bidirectional interactive financial data visualization and decision support; wherein the data access layer acquires data in real time through a streaming computing engine and transmits the data to the Dores storage computing layer, and the visual application layer performs real-time data interaction with the Dores storage computing layer through a two-way communication protocol. According to the method, the synchronous delay of financial data is shortened from 6 hours to 1 second, second-level real-time integration is realized, the aggregation query response time of billion-level data is reduced to be within 1 second based on a Dores column type storage and materialized view technology, the user interaction response delay is lower than 500 milliseconds through WebSocket two-way communication, and real-time adjustment of parameters and dynamic refreshing of a billboard are supported.

The invention provides a data annotation system and method based on a large language model, a medium and a terminal, and the system comprises a data access layer which is used for collecting to-be-annotated data, and carrying out the preprocessing of the to-be-annotated data, so as to enable the to-be-annotated data to be converted into a unified data format; the intelligent annotation engine layer is used for retrieving context information of a vertical field for the received to-be-annotated data in the unified data format, splicing the retrieved context information and the to-be-annotated data and then inputting the spliced information and the to-be-annotated data into a plurality of pre-trained large language models; the large language model is used for generating a labeling result of the to-be-labeled data; and the quality control layer is used for monitoring the quality of the labeling results generated by the plurality of large language models and carrying out feedback analysis according to the monitored labeling quality problem. According to the method and the device, the automation of the whole process from the acquisition of the to-be-labeled data to the generation of the labeling result can be realized, the vertical domain knowledge is integrated, the labeling result is strictly controlled, and the process is continuously subjected to feedback optimization.

The invention relates to the technical field of environmental information and industrial carbon emission, in particular to a cloud analysis and scheduling method for cement telegraph pole carbon footprint calculation, which comprises the following steps: constructing a cloud unified data access layer, and collecting raw material, energy and production logistics full-link data in real time; on the basis of life cycle evaluation, eight process stages are divided, and a high-precision carbon footprint accounting model is established; performing multi-dimensional sensitivity analysis on the key process parameters through Monte Carlo simulation to generate a carbon emission scene probability map; outputting a low-carbon scheduling instruction according to the optimal scene, and driving an advanced plan scheduling system to execute emission reduction and production scheduling; and a long-short-term memory neural network is introduced to realize model self-learning. According to the invention, real-time monitoring, accounting and active optimization of carbon emission in the whole life cycle of the cement telegraph pole are realized.

The invention relates to the technical field, in particular to an automatic quotation system and method based on a logistics business scene, and aims at solving the problems that traditional quotation data is disordered, and adaptability is insufficient. The system comprises a data access layer, a rule engine layer, a quotation output layer, a data storage unit and an auxiliary support module, various inquiry demands are collected through multiple channels, and a standardized data set is generated through AI feature extraction and verification; the rate is matched according to a'basic rate library priority 'strategy, dynamic adjustment is performed in combination with a floating rule, and the lowest profit is guaranteed through cost profit accounting and calibration; and a client preference presentation format is adapted, and a feedback closed loop is formed through multi-channel pushing and full-process tracking. The method comprises the steps of demand standardization, rate matching, adjustment, profit verification, calibration and output. The method achieves the high-efficiency, standard, precise and adaptive quotation, gives consideration to the profit guarantee and customer experience, and is traceable in the whole process.

The present disclosure provides a request response method and device, computer equipment and storage medium, the method comprises: in response to receiving the network service request initiated by the target application in the service logic layer of the terminal equipment, based on the request model object indicated by the network service request, determine whether there is a target interface simulation entity corresponding to the network service request; the target interface simulation entity is used to simulate the response result corresponding to the network service request returned by the data access layer of the terminal equipment through the interface; in the case where the target interface simulation entity exists, based on the request model object, the target interface simulation entity is used to determine the simulation response result corresponding to the request model object; based on the simulation response result, the simulation response model object corresponding to the request model object is generated, and the simulation response model object is called back to the service logic layer, so that the target application executes the operation corresponding to the network service request according to the received simulation response model object.

The invention relates to the crossing field of industrial energy management and artificial intelligence, in particular to a tire production factory energy real-time intelligent management method and system based on a large language model. The system is composed of a data access layer, an LLM processing layer, a decision output layer and a data iteration layer. The method comprises the following steps: uniformly collecting and semantizing energy / environment / production data; and the LLM is combined with RAG / LoRA and function calling to convert a natural language into a cross-system executable PLC control sequence, and upper and lower limit / slope / mutual exclusion check, receipt idempotence and the like are carried out. Scheduling, query, ARIMA prediction, correlation and genetic optimization and contour anomaly + FTA diagnosis are integrated, automatic disposal and audit precipitation are achieved, and daily fine tuning and monthly upgrading are supported. According to the scheme, comprehensive energy consumption is reduced, abnormity handling time is shortened, and production line stability and management efficiency are improved.

The invention belongs to the technical field of wireless system application, and particularly relates to a radio frequency-based wireless signal test platform system and a building method thereof, and the system comprises an Android master control terminal, a radio frequency communication module and an environment sensing unit; the android master control terminal carries an industrial-grade android equipment operating system, an integrated presentation layer, a business logic layer and a data access layer; the radio frequency communication module is connected with the Android master control terminal through a serial interface and is used for dynamically configuring frequency bands, spreading factors and bandwidth parameters; an environment database is established by setting an Android master control terminal, a radio frequency communication module and an environment sensing unit, adaptive communication capability testing of various radio frequency modules is realized, wireless signal data can be visually tested anytime and anywhere by using an established testing platform and environment data, and dependence on a traditional darkroom and a frequency spectrograph is avoided; and self-adaptive setting of frequency bands, spreading factors and bandwidths of the module in different environments is realized through an existing environment database.

The embodiment of the invention provides a category and library table dependency relationship determination method and device, equipment, a medium and a product. The method comprises the following steps: for any data access layer bean in a target project, running a first execution code corresponding to the data access layer bean; according to an SQL statement generated during the operation of the first execution code and a method name for calling the SQL statement, determining a first dependency relationship between a method contained in the data access layer bean and library table information; for any control layer bean in the target project, detecting dependency classes of all hierarchies corresponding to the control layer bean through a recursive algorithm, and when the dependency classes are data access layers bean, determining methods included in the data access layers bean; and determining the dependency relationship between the classes and the library table information in the target project according to the dependency classes of all hierarchies corresponding to each control layer bean, the methods contained in the data access layer bean and the first dependency relationship corresponding to each data access layer bean, so that the overall efficiency of analysis can be improved, and the probability of misplacement missing and misplacement can be reduced.

This invention discloses an industrial agent reasoning framework and method based on physical first-principle constraints, belonging to the field of industrial intelligence technology. The framework includes a data access layer, a task parsing layer, a candidate solution generation layer, a physical constraint verification layer, a conflict rollback and replanning layer, an execution decision layer, and a knowledge accumulation layer. The physical constraint verification layer uses at least one physical first-principle model as a pre-constraint hard constraint gating before the candidate decision sequence enters the execution decision layer. It performs parameter mapping, boundary condition solving, consistency calculation, residual determination, and executability determination on the physical computation variables obtained from the structured reasoning task mapping, and outputs structured conflict information when the verification fails. The conflict rollback and replanning layer performs targeted rollback and replanning based on the violation type, violation node level, and source of missing boundary conditions in the structured conflict information. The execution decision layer only outputs execution-type output results for candidate decision sequences that have obtained the pass flag. The knowledge accumulation layer writes the structured conflict information and the corrected pass results into a rule base, template base, or historical case base to serve as filtering conditions, initial parameter values, tool sorting criteria, or threshold setting criteria during subsequent candidate generation. This invention can improve the physical feasibility, reliability, interpretability, and auditability of industrial agent decision-making results.

The invention relates to the technical field of reimbursement management and control, and discloses an intelligent reimbursement management and control system and method, and the system comprises a data access layer, a core engine layer, a business application layer, and an intelligent output layer. The core engine layer adopts a deep fusion architecture of a reimbursement exclusive rule engine unit and an AIAgent intelligent interaction unit, and realizes data intercommunication through an MCP protocol. According to the invention, an enterprise financial cloud, a business cloud, a tax platform, a budget system and a historical order returning database are connected, a closed-loop management and control system of data acquisition-intelligent verification-order returning processing-rule precipitation is formed, and intelligent management of the whole process (classification, execution, optimization and precipitation) of order returning rules is realized. Compared with the prior art, the method has the advantages that the order returning processing efficiency is improved by 83% or above, the repeated order returning rate is reduced to 12% or below, the hidden violation recognition rate is improved to 92% or above, and the technical problems that rules are rigid, the order returning efficiency is low, risk recognition is lagged, business and financial collaboration is lacked, and self-optimization capacity does not exist are effectively solved.

The invention discloses a visual script generation method and device, equipment and a medium. The method is applied to an upper computer, and comprises a presentation layer responding to visual operation, a business logic layer responding to presentation layer operation to realize business logic processing, a data access layer and a hardware communication layer. In response to a task configuration operation in the graphical programming interface, selecting a target logic block from to-be-added logic blocks matched with the target control equipment for configuration and connection, and establishing a to-be-executed task; in response to a register mapping operation in the register mapping configuration interface, establishing a mapping relationship between a register address of target control equipment in the register mapping configuration interface and a target logic block; and generating a to-be-executed script file of the target control device based on the to-be-executed task and the mapping relationship, so as to transmit the to-be-executed script file to the target control device for execution. Script generation is achieved through graphical programming, equipment control is achieved through scripts, the technical threshold is low, and the development efficiency is high.

The invention discloses a multi-source integrated full-data defense line early warning platform based on front-end sensing data, and relates to the technical field of information, and the platform comprises a data access layer, a data fusion layer, an AI analysis layer and an application layer which are connected in sequence. The data access layer comprises a unified adaptation module and a real-time synchronization module, and the unified adaptation module is provided with a plurality of data adaptation sub-modules corresponding to a public security data source, a government affair data source, an operator data source, an internet data source and a sensing network data source respectively. According to the multi-source integrated full-data defense line early warning platform based on the front-end sensing data, overall optimization of an early warning disposal process is realized, the problems of difficulty in integration of multi-source heterogeneous data and insufficient real-time performance are effectively solved on the aspect of comprehensive improvement of the early warning capability, and the early warning capability is improved through time sequence alignment and intelligent track completion. The accuracy and integrity of the early warning information are improved, and the response time from risk discovery to disposal starting is shortened.

The application discloses a data migration method and device. The method comprises the following steps: in response to a migration request, obtaining target data to be migrated from a source database; storing the target data into a cache, and determining a mapping relationship between the target data and a target data table in the target database according to a predetermined allocation rule; sending a connection request to the target database through a unified data access layer, and transmitting the target data to the target database according to the mapping relationship after the connection with the target database is established. The application solves the technical problem of low data migration efficiency caused by insufficient resources of the unified data access layer.

The invention relates to the technical field of robots, automatic driving and industrial internet of things, in particular to a multi-source data fusion visualization system which comprises a unified data access layer, a time-space synchronization engine, a customizable fusion visualization panel and a visualization information interaction module by expanding a Foxglove platform. The unified data access layer accesses and standardizes multi-source heterogeneous data, the time-space synchronization engine realizes data time alignment and space registration, the customizable panel flexibly displays multi-dimensional data, and the interaction module realizes man-machine operation and hardware feedback. The system solves the problems of multi-tool fragmentation, difficulty in data synchronization, visualization fixation and lack of self-research system adaptation in the prior art, adapts to a lightweight self-research system of an ARM embedded platform, and improves the research, development and debugging efficiency of robots and automatic driving equipment.

The invention discloses a cross-platform data fusion method in the field of cross-border trade, and the method specifically comprises the following steps: A1, constructing three types of data storage modes of a modular trusted data middle table, a support relational database, a graph database and a block chain, and relates to the technical field of data processing. According to the cross-platform data fusion method in the cross-border trade field, by constructing a modular data platform and integrating a relational database, a graph database and block chain storage, the problem of unified storage and management of multi-source heterogeneous data in cross-border trade is effectively solved. Based on a micro-service architecture and a unified data access layer, flexible deployment of an algorithm module and efficient access of multiple data sources are realized, and the automation level of data fusion processing and the system flexibility are remarkably improved. Through the introduction of the block chain credible mutual recognition system, the authenticity, traceability and non-tampering performance in the cross-border data sharing process are ensured, a credible foundation is laid for multi-party cooperation, and the credibility of the platform is greatly enhanced.

This invention discloses a vehicle exhaust system technical management system and method. The system adopts a web-based architecture, including a user interface layer, a business logic layer, and a data access layer. The business logic layer integrates three main modules: pre-design research, development phase assurance, and after-sales maintenance. Each module is further subdivided into sub-modules for managing knowledge in specific domains. Through this unified platform, centralized storage, classified management, and related sharing of technical knowledge throughout the entire lifecycle of the exhaust system are achieved. This allows for the systematic accumulation and continuation of technical knowledge, effectively solving the problems of knowledge dispersion, easy loss, and difficulty in sharing and analysis in traditional management, and improving the systematic nature and collaborative efficiency of technical management.

The application discloses an AI-assisted pathological sample diagnosis method and a diagnosis system, relates to the technical field of medical image assistance, and comprises the following steps: acquiring a pathological sample from a digital pathology image library through a data access layer, and acquiring user information corresponding to the pathological sample from a clinical information library; performing multi-scale attention feature extraction and representation learning on the pathological sample through a multi-scale feature extraction network; quantifying the dynamic uncertainty of the pathological sample through a Bayesian neural network; performing multi-modal knowledge fusion; performing diagnosis decision process visualization output through a visualization module; evaluating and verifying the diagnosis system based on the visualization output result; the recognition ability of microstructure in the pathological sample and the confidence evaluation accuracy of the diagnosis result are significantly improved, the explainability and clinical practicability of the system are enhanced, incremental learning and long-term verification are supported, and the robustness, generalization ability and cost-effectiveness of the diagnosis system are effectively improved.

The invention provides an AI video monitoring platform based on an RISC-V framework. The AI video monitoring platform comprises eight levels of frameworks including an equipment perception layer, an edge computing layer, a data access layer, a data processing layer, a data storage layer, an algorithm engine layer, a platform application layer and an industry application layer. The invention belongs to the technical field of monitoring platforms, particularly relates to an AI video monitoring platform of an RISC-V architecture, and aims to at least solve the problems that traditional security depends on manual screen staring and inspection, abnormal event recognition lags behind and the missing report rate is high, and the existing system is high in authorization cost, insufficient in edge scene energy efficiency ratio and poor in adaptability. The risks that the data transmission delay is high, real-time early warning cannot be supported and privacy leakage exists in original video cloud storage due to a front end-cloud framework are avoided; the method avoids the phenomena that different brand devices and platform protocols are not uniform, the compatibility is poor, the deployment and maintenance cost is high, and the expansion capability is weak, and overcomes the defects that a general algorithm is insufficient in precision, lacks an industry exclusive algorithm, and cannot cover the multi-scene safety protection requirement.