320 results about "Data criteria" patented technology

The invention relates to a multi-data standard definition conflict resolution method based on a large model and a knowledge graph, and belongs to the field of public data governance and data standardization. The method comprises the following steps: extracting and preprocessing a multi-data standard definition; defining semantic representation and large model analysis: performing semantic analysis on the definition of each data item by using a large model, and generating a semantic embedding vector and a key feature; knowledge graph construction and entity alignment: constructing a knowledge graph containing all data items, and connecting data item nodes with similar semantics in different standards by adopting an entity alignment algorithm to form a candidate alignment relationship; conflict detection and type identification: aiming at the aligned data item definition, comparing attributes and values, identifying definition conflict points, and classifying and marking conflict types; and carrying out conflict resolution and unified definition generation by using a globally optimized conflict resolution algorithm. According to the method, the problems of data islands and semantic conflicts caused by inconsistent data standard definitions in the prior art are solved.

The invention relates to the technical field of information and data processing, in particular to an enterprise digitalization-oriented data management and application method, which comprises the following steps of: acquiring multi-source heterogeneous data and recording metadata; establishing a cross-department management system to standardize the treatment process; building an asset catalog based on the business section and the data field classification; formulating unified data description of a multi-level data standard system; designing a quality control rule to filter low-quality data; constructing a business index system and embedding the business index system into a business system; identifying a cross-system and cross-type association mode through a metadata association technology and a rule engine; and dynamically adjusting the treatment process by adopting a multi-objective optimization algorithm in combination with service feedback and treatment parameters. According to the method, the defects of existing data governance in comprehensiveness, depth and business adaptability are overcome, standardized governance and potential value mining of multi-source data are achieved, and effective data support is provided for intelligent decision making of enterprises.

According to the intelligent training method, the prediction method, the equipment and the medium for the pharmacokinetic properties of the polypeptide drugs, based on the prediction model obtained through training, the pharmacokinetic properties of at least two polypeptide drugs can be predicted, and compared with a traditional experiment method, the intelligent training method has the advantages of being efficient, accurate and comprehensive in effect and high in practicability. And the comprehensive systematic prediction platform can promote the unification of model data standards developed by different research teams, and effectively ensures the actual value of the polypeptide drug in early screening and optimization.

The invention, which relates to the technical field of mineral product screening, discloses an intelligent construction management platform for city updating, comprising the following steps: establishing a unified data standard and a data interface protocol to ensure that data of different systems, departments and enterprises in the platform can be seamlessly jointed; according to the invention, through unifying the data standard and the interface protocol, data sharing of different systems is realized, and project management efficiency and decision accuracy are improved. The real-time data acquisition and intelligent analysis technology enhances the safety monitoring and intelligent early warning functions, and ensures that potential safety hazards in the construction process are recognized and processed in time. Meanwhile, the flexibility and the emergency response capability of the project are improved by a dynamic adjustment and intelligent early warning mechanism, resources and construction plans can be automatically adjusted in the progress of the project, emergency problems can be dealt with, progress delay and resource waste are reduced, and smooth progress of the project is guaranteed.

The invention provides a standard adaptive execution method and equipment based on data standard management, and belongs to the technical field of data management. The method comprises the following steps: in response to a standardization request for a service system from a user, generating a corresponding mapping relation library based on a preset root library and a source system field; wherein the mapping relation library at least comprises a mapping relation, established on the basis of a preset semantic matching model, between the source system field and the standard field. And converting each source data value of the business system according to the mapping relation library, and executing real-time verification based on a preset multi-level value domain enumeration constraint before the source data values are written into the target library, so as to intercept conversion abnormal data according to a verification result and generate an abnormal snapshot. And when it is determined that the data standard attribute change event exists or the abnormal snapshots meeting the preset conditions exist, determining a corresponding update strategy type based on the change content of the data standard version change or the root cause classification result of each abnormal snapshot, so as to perform standardized execution according to a corresponding update strategy.

The invention provides an abnormal value screening method based on particulate matter component reconstruction, and relates to the technical field of environment monitoring. The method comprises the following steps: obtaining standard ion component data, standard carbon component data and standard inorganic element component data; obtaining a plurality of reconstruction component data; target PM2.5 data are determined; determining a doubt reconstruction component data judgment result of the plurality of reconstruction component data at each moment; determining a univariate time sequence abnormal point judgment result of each kind of reconstruction component data at each moment; determining a multivariable time sequence abnormal point judgment result of the multiple reconstruction component data at each moment; and determining whether the reconstruction component data at each moment is abnormal data. According to the method, the component reconstruction characteristics under different pollution levels can be evaluated, and the understanding of the model on the relationship among the particulate matter components is enhanced, so that the stability and accuracy of identifying whether the reconstructed component data is abnormal data are improved, the calculation efficiency is optimized, and environment monitoring auditing personnel are assisted to make decisions.

The invention relates to the technical field of data governance, and provides a data platform metadata annotation completion method, system and equipment, and the method comprises the steps: collecting metadata basic annotations in a multi-source heterogeneous database through a standard application program interface; collecting a logic model definition document and a data standard specification document, and constructing a local knowledge base through vectorization processing; when a user triggers annotation completion, calling a local knowledge base through a large language model, and generating metadata intelligent annotations; and returning the collected basic annotation of the metadata and the generated intelligent annotation of the metadata to the user as annotation completion results. According to the data platform metadata annotation completion method, system and equipment, metadata collection normalization, multi-source knowledge fusion, knowledge base construction and intelligent annotation completion can be achieved, cost reduction and efficiency improvement are achieved, the metadata annotation quality is remarkably improved, and the use threshold is lowered.

The invention relates to the technical field of video recognition and analysis, and discloses a video recognition and analysis method based on physical characteristics. Video frame pixels are mapped to a two-dimensional coordinate system with the upper left corner as an original point, and mirror image expansion and median filtering are carried out on a gray level image; constructing a binary image based on a gray threshold value, and analyzing and extracting a target region by using a four-neighborhood connected domain; using neighborhood search and polar angle sorting to close the tracking contour, and generating equidistant re-sampling points based on Euclidean distance and an interpolation method; the curvature of the re-sampling points is estimated through a three-point difference algorithm, and zero denominator is avoided through numerical protection; performing discrete Fourier transform on the curvature sequence to extract a frequency spectrum, and normalizing an amplitude to form a standardized feature vector; and finally, inter-frame similarity is calculated based on the feature vector, and the most similar frame is automatically retrieved. By processing unified data standards in stages, edge noise is suppressed, sampling uniformity is ensured, and feature stability and cross-frame comparability are improved.

The invention discloses an industrial data standard detection method based on a large model technology, and the method comprises the steps: 1, carrying out the definition of data standards, including a data content standard, a data format standard, a metadata standard, a data quality standard, a data exchange standard, a data security and privacy standard, and an industry and field specific standard; 2, performing large model knowledge enhancement, including general data standard integration, static standard rule scheme injection, dynamic semantic analysis detection scheme injection, data blood relationship detection scheme injection and composite detection mechanism fusion injection; and step 3, performing data standard detection, including data standard formatting and data standard automatic detection. According to the method disclosed by the invention, remarkable effect improvement is realized in the aspects of coverage rate detection, real-time performance, compliance interpretation capability, domain knowledge deep embedding, system management intelligence and the like, and a new generation of basic technical facilities is provided for industrial internet data management.

The invention relates to the technical field of logistics monitoring, in particular to a cold-chain logistics monitoring method and system. The method comprises the following steps: calculating a data integrity index value at each moment in a historical time period, namely an accumulated value of a product of an effective data proportion and an importance weight of each sensor; obtaining threshold exceeding degree index values of all moments, and preprocessing data and corresponding set numerical value intervals based on the sensor; obtaining a multi-source consistency index value at each moment according to a redundant sensor data standard deviation, a semantic tag and a data variable quantity at adjacent moments; carrying out weighted summation on the three indexes to obtain a confidence coefficient weight at each moment; constructing an enhanced input vector according to the confidence coefficient weight, the semantic tag and the data of each sensor; based on the enhanced input vector at each moment in the historical time period, the data and the semantic tag preprocessed by each sensor in the future preset time step length are predicted, the cold-chain logistics can be accurately monitored, and the monitoring reliability is improved.

The invention discloses a simulation data management method based on a servitization integrated architecture, and relates to the technical field of combat simulation and deduction, and the method comprises the steps: building a servitization integrated data management architecture according to a data collection layer, a data storage layer, a data management layer, a data management layer and a data service layer; based on a service integrated data management architecture, data standardization is carried out, a data model is designed, data fusion preprocessing, data integration and data analysis are carried out on collected multi-source heterogeneous data according to a data standard and the data model, data fusion and warehousing management are completed, and meanwhile balance and unification of data security and sharing are guaranteed. According to the invention, a one-stop and all-around data management solution can be provided for simulation application.

The invention provides a method for automatically generating a quality check rule based on a data standard, and relates to the technical field of data governance, and the method comprises the steps: defining the data standard, matching a database field with the data standard, and determining a check range to generate a mapping relation; based on a predefined checking rule template, the data standard and the mapping relation, generating a quality checking rule; and triggering and executing the quality checking rule according to a preset period or event.

The invention relates to a medical performance determination system. The system comprises a data storage module, a performance determination module, an auxiliary module and a display module, wherein the data storage module is used for storing medical data and standard data of each diagnosis group; the performance determination module is used for classifying the medical data according to diagnosis and treatment doctors to obtain diagnosis and treatment data of the doctors; performing performance determination on each doctor according to the diagnosis and treatment data of each doctor and the standard data of each diagnosis group; the auxiliary module is used for determining an auxiliary doctor and corresponding benchmark data according to the performance determination result, and providing the corresponding benchmark data for the auxiliary doctor; and the display module is used for displaying the medical data, the standard data, the performance determination data and the benchmark data. According to the system, the doctor performance can be automatically determined, and the problems that manual determination is prone to errors, is prone to being influenced by external factors and is low in performance determination accuracy are solved.

The invention relates to the technical field of data management and information, and particularly discloses a coal market data management method and system. According to the method, a coal industry global data standard model is constructed, a multi-source data interface layer is deployed to collect heterogeneous data, an intelligent analysis module is utilized to identify field semantics and extract key information, then data is mapped into a standard format through a standard conversion engine, unit unified conversion and code conversion are executed, and finally standardized data assets are formed. According to the system, highly automatic and precise processing of coal market data is realized, the data integration efficiency and quality are improved, and the dependence on manpower is reduced.

The invention relates to the technical field of power grid data fusion analysis, and discloses a power grid multi-dimensional spatial data fusion analysis method and system, and the method comprises the steps: collecting power grid multi-dimensional spatio-temporal data, and forming a spatio-temporal data standard set; constructing a dynamic weight fusion mechanism according to the spatio-temporal data standard set, obtaining a data quality factor, an aging factor, an importance factor and a correlation factor, and obtaining a fusion weight factor set; constructing a three-dimensional space-time coordinate frame, and mapping each dimension of data in the space-time data standard set to the three-dimensional space-time coordinate frame; fusing the data of each dimension in the three-dimensional space-time coordinate framework based on the fusion weight factor set to obtain a comprehensive association degree value of each space-time coordinate point as a data fusion analysis result; the data fusion analysis result is used for formulating a power grid operation strategy and judging power grid operation abnormity. The method has the outstanding advantages of being high in adaptive capacity, capable of accurately quantifying the comprehensive correlation degree of each coordinate point, capable of being applied to power grids of different scales and different operation scenes and the like.

The invention relates to the technical field of cross-standard data exchange, in particular to a cross-standard data exchange method and system based on a BRIDG model. The method comprises the following steps: carrying out data acquisition on a source system to obtain source system data to be converted; performing semantic label mapping on the to-be-converted source system data to obtain a preliminary semantic mapping result; semantic label fusion based on a relation graph is carried out on the preliminary semantic mapping result, and a rich semantic graph is obtained; obtaining a standard document of the target data standard; performing target standard structured analysis on the standard document of the target data standard to obtain a target standard structure model; performing target standard semantic map construction on the target standard structure model to obtain a target standard semantic map; performing cross-graph concept anchoring on the target standard semantic graph and the rich semantic graph to obtain a preliminary concept anchoring set; according to the invention, more flexible, efficient and intelligent cross-standard data exchange is realized by dynamically constructing the bridging body.

The disclosed techniques for generating a migration plan include identifying one or more entities that are eligible for data migration to a destination database from a source database. The techniques include generating, using planning procedures that include a workload balancing procedure, a data migration plan for the eligible entities and executing the migration plan. The workload procedure includes mapping, based on data metric values of the eligible entities, different ones of the eligible entities to instances in the destination database, where the mapping is performed based on utilization metric values of the instances, and where the instances are of a storage service that collectively implements the destination database. The workload balancing procedure includes altering the mappings of entities to instances in the destination database, where the remapping is based on a standard deviation of data for entities mapped to instances in the destination database not meeting a threshold standard deviation.

The invention discloses an intelligent management system and method for a food detection sample, and relates to the technical field of food management, and the method achieves the real-time collection and dynamic perception of multi-source smell diffusion data such as smell diffusion data through setting a plurality of data collection points in a target area of a food detection storage environment. And after the sample management center platform receives the data transmitted by each data acquisition point, high-precision alignment and dimensionless integration of the data are realized through preprocessing. The processing flow effectively eliminates the influence of sensing error, time drift and unit dimension difference, and ensures the comparability and consistency of smell data between samples. Therefore, compared with a traditional monitoring mode only depending on a single-point gas sensor, the storage smell dynamic monitoring system has the advantages that the'smell basic data set 'of the sample can be constructed in a software algorithm mode, and the storage smell dynamic monitoring system with low hardware dependence, uniform data standard and higher calculation precision is realized.

The invention discloses a data modeling method and device, computer equipment and a storage medium, relates to the technical field of artificial intelligence, and is applied to data modeling of a financial big data platform. The original data elements are processed in a standardized mode, and the type labels are automatically marked according to the preset classification rules; in combination with a feature coding technology, converting multi-dimensional data elements into uniform characterization representation; calculating by using a data field standard map and semantic similarity, automatically identifying an abnormal mode, and performing quantitative scoring through a pre-training review model; and finally, performing iterative optimization according to the review index score, and generating a detailed feedback report. According to the method, the modeling efficiency is greatly improved, automation and intelligentization of the field creation, type judgment and standard binding processes are realized, the data standard coverage rate and the modeling quality are effectively improved, the risk of manual review and script deployment errors is reduced, and the modeling efficiency is improved. And the modeling reliability and the operation and maintenance efficiency of the financial big data platform in a complex business scene are enhanced.

The invention relates to a method and equipment for integrating information required by power supply scheme auditing based on management promotion. The method comprises the following steps: acquiring a power supply scheme and an existing auditing process; according to an existing auditing process, roles involved in the process are obtained, and dynamic auditing link optimization is carried out according to role permissions to obtain a basic auditing operation process; according to the power supply scheme and the basic auditing operation process, analyzing an information source required by auditing, obtaining the information required by auditing, and tabulating the information required by auditing; and processing the information required for auditing through a text recognition technology and a natural language processing technology, extracting key information, performing intelligent comparison with an existing data standard, if the key information conforms to the existing data standard, uploading the tabular information required for auditing to an auditing system, and otherwise, giving an alarm. Compared with the prior art, the information required by power supply scheme auditing is integrated, and automation of auditing information acquisition is realized.

The invention provides a metadata-driven personal health record data processing method and system, and aims to solve the problems of efficient integration, exchange and intelligent utilization of multi-source heterogeneous health data. The method comprises the following steps: constructing a personal health record data standard specification shared document, and designing a standardized form; heterogeneous data sources are integrated through an ETL process, and high quality, consistency and integrity of data are guaranteed; and performing data mining and analysis by using the data of the data warehouse, and displaying a result through a chart or a report. The system architecture integrates a system parallel computing framework, an archive data processing module, a security and privacy guarantee module and a system monitoring and operation and maintenance management module, and provides personalized service and decision support for different subjects through efficient storage, distributed processing and intelligent analysis of structured and unstructured health data. The efficiency and flexibility of data processing are remarkably improved, and the complex requirements of health big data processing are met.

The invention discloses a building construction quality optimization method and system based on a large-span transfer beam, and relates to the technical field of building structure intelligent construction quality control, and the method comprises the steps: collecting multi-source engineering data, constructing a unified data standard, and carrying out the multi-working-condition disturbance modeling through combining a simulation platform; importing a finite element system for dynamic structure response analysis and outputting a response risk map; mapping the response variable to a multi-factor coupled bearing capacity function, and outputting a load limit which can be actually and stably borne by the template system; and constructing an on-site real-time monitoring network, performing linkage comparison on monitoring data and a multi-working-condition disturbance modeling result, and driving response verification, maintenance strategy adjustment and demolding node management and control. According to the method, a construction quality optimization mechanism with disturbance modeling, bearing capacity evaluation and real-time monitoring as the core is constructed, and risk prediction, response regulation and control and quality closed-loop control of the whole construction process of the large-span transfer beam are achieved.

The invention discloses an OSM-based urban traffic three-dimensional simulation scene modeling method and system, and the method comprises the steps: obtaining map data of a target simulation region, carrying out the preprocessing of the map data, and obtaining the preprocessing data; road shoulders, curbs and sidewalks are subjected to parameterization batch filling according to the preprocessed data, and a two-dimensional simulation model is correspondingly generated; defining a target data standard, generating a target high-precision map according to the target data standard and the two-dimensional simulation model, and converting the target high-precision map into a three-dimensional road network model through target software; based on three-dimensional visualization software, a three-dimensional simulation model is generated according to the three-dimensional road network model, and three-dimensional visualization simulation is generated based on a digital twinborn tool and a blueprint tool. Aiming at traffic simulation modeling requirements, the OSM map is used as a data source, the data conversion relation between the simulation model and the three-dimensional model is deeply explored, the automatic modeling efficiency of traffic simulation is improved, and the three-dimensional visualization capability of the simulation model is enhanced.

The invention relates to the technical field of artificial intelligence large model application, in particular to a national data standard file-oriented intelligent data element extraction method and system, which comprises the following steps: reading data standard document content, performing text partitioning on the read document content according to a preset rule, compiling a large model Prompt, and compiling the large model Prompt. Persistently storing the data element and the regular expression extraction result into a database; the method has the beneficial effects that deep semantic analysis is carried out on the national standard file by debugging a large model prompt, and accurate recognition and extraction of data elements in the file are realized by utilizing a means of combining text segmentation and a natural language processing technology. According to the method, the key data information can be quickly and accurately obtained from the national data standard file, the extracted data element and data rule information data structure is standardized, the method can be directly used for subsequent data modeling and data quality inspection, and manpower and time costs are greatly saved.

The application discloses a data model and data standard mapping method, device, equipment and medium, wherein the data model and data standard mapping method comprises: obtaining data standard information of metadata corresponding to each data type through a standard source end; based on a data standard template corresponding to the data type, using the data standard information to define governance attributes of the metadata corresponding to the data type, so as to generate preliminary data standards corresponding to all the metadata; a review end returns public data standards corresponding to the metadata based on the preliminary standards; any data model is obtained, the semantic distance between the data model and the public data standards is calculated, and based on the semantic distance, the mapping relationship between the data model and the public data standards is confirmed. The method can improve the efficiency of extracting general standards for different data models offline in advance in the process of formulating data standards, and intelligently establishes the associated mapping relationship between the data model and the data standards.

The invention discloses an exploration big data model construction method and device, equipment and a medium, and relates to the technical field of data processing, and the method comprises the steps: carrying out the standardization processing of obtained exploration data to determine a data standard, and collecting multi-source heterogeneous exploration data based on the data standard, multi-source heterogeneous survey data is subjected to distributed classified storage according to a multi-level classification system, a survey big data model is constructed according to user project requirements, coordinate enabling is set based on the survey big data model so as to carry out GIS data visual interaction, and a unified survey data model is established through data standardization and survey data standard making. A surveying multi-specialty data unified storage center is constructed, and full-life-cycle data management is achieved.

The invention discloses a budget management system, and the system comprises a budget basic configuration module which is used for defining a budget data standard, and carrying out the configuration of the dimensions and attributes of a budget pool and budget items; the business data acquisition module is used for being connected with a data system of a business department of a preset type and acquiring business budget data of each business department; the budget execution control module is used for monitoring and controlling application, use and change processes of the budget according to the budget management target; the budget flow tracing module is used for managing budget data in the whole budget execution process; according to the method, the problem that budget management and control are not centralized and unified in the prior art is effectively solved, the efficiency of budget management is improved through standardized data and a centralized management mode, the accuracy and reliability of budget data are ensured, powerful data support is provided for various decisions of enterprises, and the advantages of the enterprises in market competition are enhanced.

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 relates to the technical field of complex equipment data management, in particular to a model-driven complex equipment data relation automatic construction method and system. The method comprises the following steps: constructing a business entity meta-model standard framework comprising a base layer and a domain extension layer through a meta-model technology, and establishing a dual-check system; a hierarchical modeling method is adopted to construct a data model system, and model management is performed through a multi-source heterogeneous data reference mechanism and semantic version control; constructing a data association relationship by adopting a multi-modal fusion method and integrating structural analysis and semantic reasoning; and finally, four-dimensional quality evaluation of integrity, consistency, timeliness and accuracy is carried out on the data association relationship. According to the method, the problems of non-uniform data standards, low association efficiency and incomplete change transmission in complex equipment development are solved, and an automatic closed loop from data association construction to quality control is realized.

The invention belongs to the technical field of pumped storage power station intelligent data processing, and discloses a pumped storage power station data processing method and system based on a space-time knowledge graph. The 5G Internet of Things dynamic data, the BIM + GIS static data and the construction log semi-static data are deeply associated with a millisecond-level timestamp based on a national 2000 geodetic coordinate system; in an underground cavern excavation scene, real-time displacement monitoring data can be synchronously matched with BIM component deformation simulation, the problem of monitoring-simulation asynchronization is solved, obvious lag does not exist in progress deviation early warning any more, the management and control delay risk caused by data splitting is effectively avoided, and the dynamic safety of underground cavern group construction is guaranteed; in a data acquisition stage, a data standard is directly embedded into a source through a standard semantic pre-labeling module, and unified semantic tags such as unique component identifiers and process codes are preset for various types of data.