142 results about "Data architecture" patented technology

A system and method for machine learning-based data field validation is proposed that utilizes a specific trained machine learning model data architecture that is adapted to be more resilient against training set class imbalance, using a Siamese triplet LSTM network architecture that uses three LSTMs that are trained together and operate in concert. An example non-limiting practical use includes using the Siamese triplet LSTM network architecture to validate whether free-text data fields include a single jurisdiction in an address or multiple jurisdictions in the address.

The embodiment of the invention provides a novel data architecture knowledge intelligent retrieval method and system for electric power system construction, and belongs to the technical field of data processing. The retrieval method comprises the following steps: collecting various data types of enterprise digital architecture related assets; carrying out tagging processing on the collected data; performing data fusion and knowledge extraction on the data by applying an RAG model and a graph database so as to construct a knowledge graph; semantic modeling is carried out based on a deep learning model, and accurate retrieval based on semantic understanding is constructed; building generative retrieval by combining RAG and GPT so as to meet the requirement of enterprise architecture knowledge retrieval; a precise retrieval technology and a generative retrieval technology are modularized. According to the retrieval method, intelligent retrieval service and monitoring analysis and strategy recommendation based on a scene rule engine can be realized through data acquisition, fusion, knowledge extraction and knowledge graph construction of enterprise digital architecture related assets, so that the problems in the prior art are solved.

The invention discloses an intelligent file service system generation method based on a low-code development mode. The method comprises the following steps: constructing a file service core data model, defining file metadata fields, a storage structure and an association relationship, and forming a standardized data architecture. According to the method, the core data model, the visual page component library and the drag-and-drop workflow template are constructed, linkage binding of data-component-process is achieved in combination with a low-code engine, and the efficiency bottleneck of a traditional development mode is broken through; through a three-way real-time synchronization mechanism, real-time hot repair and dynamic branch judgment, page layout and flow rule adjustment can take effect immediately through visual configuration, and the problem of dynamic demand response lag is solved; through the intelligent resource scheduling logic compiled through environment adaptation, a differentiation scheme is generated for different deployment environments, the configuration difference influence under a private cloud and server mixed deployment scene is remarkably reduced, the deployment failure rate is greatly reduced, and the system online stability is improved.

Embodiments of the present invention relate to the fields of large model techniques and big data. Disclosed are a data scheduling method, a system, and an electronic device. The method comprises: in a performance feature set of a performance prediction model, determining a target performance feature matched with a scheduling strategy of a model to be trained, wherein the performance prediction model is matched with the model type of the model to be trained, the model type is used for representing a data architecture of the model to be trained, and the scheduling strategy is used for at least representing a rule required to be satisfied during training of the model to be trained; and identifying from among different training strategies a target training strategy corresponding to the target performance feature, and identifying from among different training resources a target training resource corresponding to the target performance feature; and configuring the identified target training strategy to the model to be trained, and allocating the identified target training resource to the model to be trained.

The invention relates to the technical field of geological analysis, and discloses a method for fusing a three-dimensional geological model and a WebGIS (Web Geographic Information System), aiming at solving the problems of poor data intercommunity, limited spatial analysis capability, difficulty in real-time updating and low model loading efficiency of the existing method, and the scheme mainly comprises the following steps: extracting geological model data, and carrying out standardized format processing; lightweight processing is carried out, and geological attributes and model nodes are bound one by one; the format is converted into a binary format embedded with a metadata label, and data integrity verification and automatic error correction are carried out in the conversion process; constructing a non-uniform adaptive octree spatial index, a multi-level attribute data architecture and a real-time updating mechanism of attribute data; after the geological model and the terrain are precisely registered and fused, a dynamic loading mechanism, a high-performance rendering mechanism and a geological model real-time updating mechanism are constructed, and a three-dimensional geological analysis tool is integrated. According to the method, efficient loading, real-time rendering, dynamic updating and spatial analysis of the three-dimensional geologic model in the WebGIS are realized.

The invention discloses a dynamic form generation and cross-database adaptation method based on metadata driving, and belongs to the technical field of data architectures. The method comprises the steps that an original metadata attribute graph is established; on the basis of the original metadata attribute graph and user roles and equipment parameters for calling the forms, generating an optimal equipment form interaction data graph corresponding to each user permission; verifying an interaction path between the forms and a cross-database demand of a target database type to carry out cross-database mapping adaptation analysis, and generating an optimal form data adaptation database of the corresponding equipment of each user permission; and performing rule compiling based on multi-source heterogeneous data input by a user in real time and execution logic in the original metadata attribute graph, marking an incremental propagation path in the optimal form interaction data graph of the corresponding equipment of each user permission, and updating the optimal form data adaptation database of the corresponding equipment of each user permission. The method has the advantages that the data interaction efficiency is improved, and the interaction round-trip times and redundant data transmission are reduced.

The invention provides an intelligent ship software architecture design method, which comprises the following steps of S1, carrying out intelligent ship software service architecture design, and adopting hierarchical design which comprises a data sensing layer, a service processing layer, a ship-shore communication layer and a shore end display layer; s2, carrying out intelligent ship software system architecture design, and adopting a cloud-side-end collaborative fusion mode; s3, intelligent ship software technical architecture design is carried out, and a cloud-shore-ship technical architecture mode is adopted; and S4, carrying out intelligent ship software data architecture design, and deploying a database in a cloud-shore-ship mode. According to the technical scheme, the problems that an intelligent ship software architecture cannot effectively achieve software and hardware decoupling, layering and modularization cannot be achieved, ship-crossing multiplexing cannot be achieved, and expandability is poor are solved, the purposes of software and hardware decoupling, ship-crossing multiplexing, software-defined ships and the like are achieved, rapid iteration of intelligent ship software research and development is effectively supported, and the development efficiency is improved. And the research and development period of the intelligent ship is shortened.

The invention provides an MES-based solar cell production and manufacturing execution method and system, and the method comprises the steps: collecting equipment states and technological parameters in real time, combining a bar code system to achieve the single-chip-level metadata association, constructing a standardized data architecture, building a multi-dimensional index, converting the expert experience into reasonable rules, and carrying out the calculation of the reasonable rules. The method comprises the following steps: simulating the influence of parameter combination on product performance, triggering an edge computing node to call a knowledge graph to perform parameter optimization and production simulation based on a dynamic threshold early warning mechanism, identifying process improvement opportunities through a batch tracing report and clustering analysis, forming knowledge base iteration update, predicting inventory risks in combination with a production plan and equipment load, and performing production management. According to the method, intelligent purchasing is automatically triggered, raw material distribution is optimized, technological parameter self-optimization, abnormity self-healing, quality traceability and supply chain collaboration are achieved through data driving, the production efficiency, the product consistency and the resource utilization rate are improved, and a whole-process digital solution is provided for photovoltaic manufacturing.

The invention relates to the technical field of data processing, and discloses a data governance method and system for a distributed data architecture, and the method comprises the steps: carrying out the spatial-temporal feature coding of multi-modal data generated by equipment, and obtaining equipment data carrying a spatial-temporal feature code; constructing a multi-level association bitmap based on the equipment data carrying the spatial-temporal feature codes; based on the constructed multi-level association bitmap, cooperative computing of edge physical nodes and central governance nodes of the distributed data architecture is achieved; according to the method, the multi-level association bitmap is constructed through spatial-temporal feature coding, the problem of association analysis distortion caused by edge node storage fragmentation is solved, and efficient collaboration of edge physical node data fragmentation storage and central governance node global association calculation is achieved.

The invention relates to the technical field of computers, and discloses a data processing method and device, computer equipment, a storage medium and a program product. The method comprises the following steps: acquiring an event system table; wherein the event system table comprises a data architecture version table, and the data architecture version table comprises to-be-processed events; executing the to-be-processed event by utilizing the central node, determining changed metadata information, and writing the changed metadata information into a data architecture version table; and controlling other nodes to obtain the changed metadata information from the data architecture version table, and updating the original metadata information of other nodes according to the changed metadata information.

The invention discloses a target detection algorithm-oriented data architecture optimization method in the field of visual detection, and the method comprises a video data management module, a data automatic labeling module, a special data sample reservation module and an image data de-duplication module. Business data of different sources are subjected to renaming management in a unified mode, videos are intercepted by adopting different video interception frequencies and stored as picture data, naming of the picture data is based on the names of the source videos, and related frame numbers are added to serve as supplements. According to the method, the redundancy of the service data set is reduced by utilizing an image similarity calculation method, the dispersion degree of the service data set is improved, the time cost of subsequent manual annotation and the resource cost used by transfer learning are reduced, and meanwhile, the detection performance of an AI visual detection technology in an on-site scene is ensured.

The invention is suitable for the technical field of engineering investigation, and provides an engineering investigation digital drilling machine based on the Internet of Things sensing technology and a big data service system.The digital drilling machine comprises a drill tower, a hydraulic standard penetration piece, a slurry pump, an integrated operation table, a double-clamping structure, a power head, monitoring equipment and other assemblies; linkage and data interaction of all the assemblies are achieved through a controller special for engineering machinery. The big data service system covers three aspects of a data architecture, a core algorithm and a security mechanism, the data architecture comprises an edge computing layer and a cloud analysis layer, the core algorithm comprises a drilling efficiency prediction model and equipment health degree evaluation, and the security mechanism comprises data encryption and access control. The big data service system provides intelligent decision support and service for engineering investigation, and the engineering investigation efficiency and quality are effectively improved.

A local machine learning based recording and audio transcribing system is proposed that operates in real-time in parallel and time-synchronized with a operating theatre recorder system, modifying encoding of the operating theatre recorder system outputs for generation of the pre-processed recording files to be transmitted to a remote cloud-based processing backend using operating a centralized machine learning model data architecture across a network. By modifying the recording or the generation of the pre-processed recording files, the system can be tuned for providing increased signal resolution at more relevant portions of time or frame portions to improve the accuracy and predictive capability of a backend machine learning model that is configured for operation using the pre-processed recording files while adapting for practical network bandwidth and computing resource limitations in cloud-based implementations.

The invention discloses a data scheduling method and system and electronic equipment, and relates to the field of large model technology and big data. The method comprises the steps that target performance characteristics matched with a scheduling strategy of a to-be-trained model are determined in a performance characteristic set of a performance prediction model, the performance prediction model is matched with a model type of the to-be-trained model, and the model type is used for representing a data architecture of the to-be-trained model; the calling strategy is used for at least representing rules which need to be met in the training process of the to-be-trained model; identifying a target training strategy corresponding to the target performance feature in different training strategies, and identifying a target training resource corresponding to the target performance feature in different training resources; and configuring the identified target training strategy to a to-be-trained model, and allocating the identified target training resource to the to-be-trained model. The technical problem of low data scheduling efficiency is solved.

Described herein is technology for providing the secure transfer of assets between blockchain networks. A secure-execution server can be configured to execute a bridge program in a secure execution environment to interact with a first pool of warden servers to facilitate secure transfer of assets between a first blockchain network and a second blockchain network. The bridge program may include instructions that, when executed by the secure execution environment, cause the secure-execution server to perform operations that may include performing lock operations that lock first assets from a contractless blockchain network and mint second assets representing the first assets in a contracting blockchain network, where the contracting blockchain network supports smart-contracts that are unsupported on the contractless blockchain network; and performing unlock operations that unlock the first assets by transferring the first assets in the first blockchain network in response to the second assets being returned or destroyed.

The invention discloses a database migration and grammar transformation method, device and equipment, and the method comprises the steps: firstly responding to the login operation of a target user on a data architecture management platform, verifying whether the target user has the authority of database migration, and if yes, obtaining original database attribute information through the data architecture management platform; and according to the attribute information of the original database, establishing corresponding attribute information in the target database. The method comprises the following steps: firstly, acquiring an SQL execution statement, then synchronizing data in an original database to a target database through a data warehouse tool of a distributed system, then acquiring an interface and the corresponding SQL execution statement through a log pipeline recording platform, and performing grammar optimization on the SQL execution statement by utilizing a pre-trained large model to obtain an optimization result. Therefore, the efficiency and accuracy of database migration and grammar transformation can be effectively improved.

The invention discloses an equipment health management system and method based on a multi-channel parameter diagram. A parameter acquisition unit acquires health parameters of equipment; the parameter diagram construction unit is used for converting the collected equipment health parameters into equipment parameter diagram data and constructing an equipment parameter diagram; the health condition evaluation unit obtains an equipment health level according to the equipment parameter diagram; the fault level evaluation unit establishes a unified fault level, and obtains an equipment fault level according to the equipment health level; and the maintenance management unit performs attribution analysis according to the equipment fault level to obtain an equipment maintenance scheme. According to the method, firstly, through a unified data architecture and a cross-industry fault system, rapid access of multiple types of equipment is supported, and evaluation management is carried out; and secondly, maintenance suggestions are generated driven by a large language model, automatic closed loop from fault detection to a maintenance scheme is realized, and scientific basis and intelligent suggestions are provided for equipment maintenance.

The invention provides a one-stop integrated management system for intelligent educational administration data, and the system comprises a data architecture which outputs a data source which can be automatically optimized after constructing and optimizing an educational administration data model; the algorithm architecture is internally provided with an algorithm model and an algorithm engine, and the algorithm model generates an evolution sandbox which can be processed by the algorithm engine by utilizing a quantization evaluation technology after the algorithm model passes through the distillation data source; relates to the technical field of educational administration. According to the method, advanced technologies such as quantization evaluation, digital twinborn cognitive synchronization and federal multi-agent game are creatively introduced into the field of education management, education decision ecology with self-evolution ability is constructed, breakthrough innovation is formed in three levels of data management, algorithm architecture and system fusion, and the method has the advantages of being high in practicability and easy to popularize. The problems of decision black box, resource mismatching, algorithm rigidity and the like of a traditional system are solved, the educational resource configuration efficiency is effectively improved, and the educational administration system has the high-quality characteristic of sustainable evolution.

The invention provides a full-life-cycle digital asset management system. According to the technical scheme, the full-life-cycle digital asset management system is characterized by comprising a meta-model management module, a data source management module, a metadata management module, a data architecture design module, a data management module, a data product management module and a data asset management module; wherein the data management module comprises a data standard management module and a data quality management module; wherein the meta-model management module is connected with the metadata management module; the data source management module is interactively connected with the metadata management module, and the data source management module is also interactively connected with an external data source; the data management module is in interactive connection with the metadata management module, the data architecture design module, the data product management module and the data asset management module. According to the application, a layered modular architecture is adopted, and an automatic process from data modeling to capitalized operation is realized through a full-life-cycle management mechanism driven by a meta-model.

The invention discloses a data development management processing method and device and electronic equipment. The data development management processing method comprises the following steps: taking a dimension correlation model structure definition as a center of communication construction management; a project space is used as a basic unit of management, data architecture is flattened and labeled, and data component content is abstracted into resources and managed in a unified mode; access limitation setting is performed on resources in a project space, preprocessing and post-calculation are performed on data, and multiple forms of data services which are safe, compliant, credible and controllable are provided. According to the technical scheme, a low-threshold, low-cost and easy-to-expand capability is provided for data development management processing, meanwhile, an effective method for simply sharing data is provided, and the data construction efficiency, the data circulation efficiency and the data use efficiency are improved.

The invention relates to the technical field of vision measurement, and discloses a three-dimensional vision measurement system based on multi-view structured light, and the system comprises a data collection module which obtains image data, system data and point cloud data through a sensor and a system; the synchronous link module is used for generating a synchronous pulse interval based on the system data; calculating a cross correlation coefficient to judge interference and finish construction of a synchronous link; the three-dimensional measurement module is used for adjusting and calibrating by utilizing a composite structure, adjusting brightness through double modulation, constructing a target section data representation model for iterative optimization, analyzing to obtain an absolute phase value, constructing an energy function, obtaining a matching point pair based on image data and calculating a depth error; the data architecture module is used for dividing point cloud data, carrying out gridding discretization on an integral region, carrying out parallel calculation on energy values, summarizing the energy values, and dynamically adjusting the order of multi-pole expansion; and the enhanced anti-interference module is used for carrying out anti-interference processing on the image data, adjusting measurement parameters and adjusting the projection light intensity based on the predicted light intensity.

The application discloses a prediction method, system and storage medium for patient drug reactions. The method comprises: constructing a data architecture of a drug reaction prediction model according to pre-input source domain data, target domain data and drug attribute information; based on the data architecture of the drug reaction prediction model, performing training on the drug reaction prediction model according to a target training function to determine execution parameters of the drug reaction prediction model; and determining drug reaction prediction parameters according to the execution parameters, the source domain data and the target domain data to determine a prediction result of the patient drug reaction. The application places the representation alignment process of the patient sample and the cell line sample in the specific drug context fusion information through drug conditionalization alignment, thereby reducing the cross-domain distribution difference. In addition, the drug priority prediction result is generated in units of patients by using the drug reaction prediction parameters, the risk of model degradation into drug identity memory is reduced, and the generalization prediction ability for drugs is enhanced.

The invention relates to the technical field of data encryption, in particular to a transmission encryption method based on a Beidou communication data architecture, which comprises the following steps of: S1) adjusting related communication data and calibrating the related communication data as a data item to be filled or a data item to be missing based on the related communication data needing to be transmitted in the stage and an adaptive data transmission channel in the related data architecture; s2) performing priority processing on the to-be-missing data items, selecting part of data from the corresponding to-be-missing data items based on changed capacity data of the to-be-missing data items, calibrating the part of data as to-be-filled data, then determining to-be-transmitted missing items, performing related filling on the to-be-filled data items, and preferentially confirming filling capacity data corresponding to the to-be-filled data items; relevant data are selected from the to-be-filled data, and then to-be-transmitted filling items are determined; and S3) performing data transmission based on the determined data transmission channel of the corresponding data item, and determining an encryption key of the corresponding data item based on the transmission delay of each group of different data items in the transmission process.

The invention relates to a business system updating method and device, computer equipment, a computer readable storage medium and a computer program product, relates to the technical field of databases, and can improve the adaptation degree of a data architecture and a business current situation. The method comprises the following steps: acquiring a database table of a business system of an enterprise, determining a logic entity corresponding to the database table, and storing the logic entity into an enterprise architecture management system; determining a conceptual entity corresponding to the business object of the enterprise based on a pre-acquired business architecture of the enterprise; determining a first association relationship between the logic entity and the concept entity; based on the first association relationship and a second association relationship between the logic entities, determining a data architecture of the enterprise, and storing the data architecture into an enterprise architecture management system; and based on the data architecture, updating the database table in the business system to obtain an updated business system.

The invention discloses a power grid equipment fault analysis method and device, computer equipment and a storage medium, and relates to the technical field of power grid equipment fault diagnos.The power grid equipment fault analysis method and device integrate various complex and diverse data sources which are widely distributed in a power grid, construct a highly structured and logically clear data architecture based on a snowflake model, and analyze the fault of the power grid equipment. And data related to fault analysis can be quickly positioned from mass data in a short time. Meanwhile, data storage is carried out in the Hadoop distributed file system, the information dimension of fault analysis is greatly enriched by utilizing the powerful distributed storage, data redundancy and fault-tolerant mechanism of the Hadoop distributed file system, and a stable data basis is provided for power grid equipment fault analysis. And multiple complex factors of power grid equipment faults are comprehensively considered, a comprehensive and high-adaptability model system is constructed, various complex fault types can be accurately identified, fault diagnosis errors caused by single or inaccurate models are effectively avoided, and the fault prediction and diagnosis capability is improved especially under the complex conditions of severe weather and the like.

The invention provides an industrial data management and development synchronization method and system for a data-in-data station, and the method comprises the steps: S1, constructing a data architecture of the data-in-data station according to different demands of an enterprise; s2, based on the data architecture, establishing a data management and development collaboration mechanism of the data-in-data platform; s3, based on the data architecture and the collaboration mechanism, making a construction method for data management and development of the data-in-the-data platform; and S4, based on the data architecture, the collaboration mechanism and the construction method, formulating a work specification of data management and development of the data-in-the-data platform. The method comprises a collaboration mechanism, a construction method, a work specification and the like of data architecture design, treatment and development of the data in the data platform, and different requirements of enterprises on data unified management, public data asset construction, personalized data application construction and the like can be met by designing a three-layer logic data architecture of the data in the data platform.

The application discloses a kind of production line unit modeling methods for digital twin monitoring, comprising the following steps: S1, establish production line scene data architecture;S2, establish warehouse production line system requirement diagram and monitoring application requirement diagram;S3, establish warehouse production line structure diagram, equipment structure diagram, value definition diagram, establish warehouse production line activity diagram, equipment activity diagram, equipment mathematical model;S4, establish the object node and variable of OPC UA information model;S5, establish equipment three-dimensional model in Solidwork, import three-dimensional simulation software VC in intermediate format STP;S6, define the operation flow of production line, the operation constraint relationship between each equipment;Define the independent and dependent relationship between each motion structure;S7, according to equipment mathematical model, establish corresponding data structure, determine the data source to collect data and update OPC UA information model.The application has good visualization and interactivity, and production line state feedback is timely, can effectively help manager to understand production line state, improve management efficiency.

The invention discloses a radiation source recognition reasoning question-answering system and method based on graph retrieval enhancement generation, and belongs to the technical field of artificial intelligence and signal processing. The system comprises a data processing module, a knowledge graph construction module, a retrieval and reasoning module, a graph retrieval enhancement generation module and an output module. The method comprises the following steps: preprocessing multivariate data through a three-layer data architecture to generate a structured triple; constructing a dynamic knowledge graph; top-to-bottom accurate retrieval and bottom-to-top context optimization are realized by adopting a U-retrieval strategy; generating a traceable recognition analysis and processing suggestion based on the retrieval sub-graph in combination with a large language model; and outputting a final result with reference and term interpretation. According to the method, the problems that knowledge updating is lagged and reasoning cannot be explained in a traditional radiation source identification system are solved, the identification accuracy, the real-time performance and the result interpretability are remarkably improved, and the method is suitable for radiation source intelligent identification and reasoning tasks in a complex electromagnetic environment.

A system and method for cross mapping an evidence data for risk management is provided. The method includes identifying a matching requirement for a first data element of the evidence data by matching the first data element to a requirement in a centralized requirement layer of a multi-layer data architecture; mapping the matching requirement to at least one control in more than one framework of a plurality of frameworks according to the multi-layer data architecture, wherein the centralized requirement layer of the multi-layer data architecture has a plurality of requirements that each represent a criterion and are shared across the plurality of frameworks; and determining, based on the mapping, a control state for the at least one control in more than one framework of the plurality of frameworks in response to the evidence data.

The invention discloses an enterprise-level architecture modeling and layer-by-layer decomposition method based on a unified meta-model, which comprises the following steps: constructing the unified meta-model covering business architecture, data architecture, application architecture, technical architecture and security architecture domains, including defining core element types and cross-domain association relationship types of each architecture domain; according to the unified meta-model, enterprise-level overall architecture modeling is carried out, and an enterprise-level architecture asset library including multi-architecture-domain standard assets and dependency relationships thereof is generated; and step-by-step architecture decomposition design is carried out on a project to be implemented based on the unified meta-model and the enterprise-level architecture asset library, and a project-level architecture blueprint aligned with the overall architecture, a refined project demand specification and a landing technology design scheme are sequentially output. Through a unified meta-model and a layer-by-layer decomposition tracing mechanism, the problem of disjunction of semantic segmentation and strategic execution in cross-domain architecture modeling is solved, and collaboration, alignment and controllability of cross-domain architecture design are achieved.