390 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 discloses a data warehouse intelligent construction method and device based on a large model. The invention provides a data warehouse intelligent construction method and device based on a large model, and belongs to the technical field of big data processing. The method comprises the following steps: a user registers to-be-collected business system data source information through a data source registration entry, and submits the information as a data processing task; receiving a data processing task through a task executor, calling a large model to carry out feature analysis on a data table, and identifying a table type, a service attribute and an acquisition parameter; executing data acquisition according to an analysis result, including identifying a temporary table, determining an acquisition period, selecting an increment field and the like; performing intelligent exploration on the collected data, and identifying field features and data quality; performing data conversion based on the probing result, wherein the data conversion comprises automatically binding a business rule, associating a data standard and generating a conversion rule; and finally, executing data fusion, intelligently matching the target table and the field mapping relation through a large model, generating a fusion rule, and executing fusion.

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 provides a personalized health monitoring method based on multi-instrument data fusion, and aims to solve the problems of non-uniform data standards and poor interoperability of existing multiple health monitoring devices. According to the method, a data standardization protocol is automatically selected and optimized according to data characteristics (such as sampling frequency, data precision and the like) of different devices (such as oximeters, sleep monitors and the like) through a machine learning algorithm, and seamless fusion of data between the devices is ensured. Different from a traditional static data processing mode, the scheme not only improves the collaboration efficiency among the devices, but also effectively solves the problems of inconsistent data formats and information loss. For different types of data generated by multiple devices, a data fusion strategy is automatically identified and optimized by adopting an intelligent fusion algorithm based on deep learning, and information conflict or delay caused by mismatching of data features is avoided.

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.

According to the quality detection method based on the big data governance platform, quality detection is divided into quality detection based on data standards and quality detection based on quality rules, and standardization and flexibility are considered at the same time; the data quality detection task and the data quality detection task are uniformly associated to related metadata to form an executable quality detection task, in quality detection, whether the data meet data standard requirements or not can be detected, various data problems can be detected according to service requirements, all requirements of data quality detection can be covered in an omnibearing mode, and the data quality detection efficiency is improved. A quality detection method with strong universality and good applicability is really established; different weights can be given to six types of quality detection including integrity, consistency, effectiveness, accuracy, uniqueness and timeliness according to the opinions of field experts, so that the data quality score is displayed more reasonably and accurately.

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 discloses an anomaly detection method and device for main network equipment and electronic equipment. The method comprises the following steps: acquiring historical operation data of main network equipment, and determining standard operation data of the main network equipment; inputting the historical operation data into the target model to obtain predicted operation data of the target date; calculating a historical deviation value based on the historical operation data and the standard operation data, calculating a predicted deviation value based on the predicted operation data and the standard operation data, and calculating a comprehensive deviation value through the historical deviation value, the predicted deviation value, the historical operation data, the standard operation data and the predicted operation data; and when the comprehensive deviation value is greater than or equal to a deviation value threshold value, determining the operation state of the main network equipment as an abnormal operation state, and when the comprehensive deviation value is smaller than the deviation value threshold value, determining the operation state of the main network equipment as a normal operation state. Through the method and the device, the problem of low accuracy of the anomaly detection result of the main network equipment in related technologies is solved.

The invention relates to the crossing field of engineering geological survey and informatization technologies, in particular to a drilling whole-process digital management method and system based on a BIM + GIS technology. According to the method, a three-dimensional visual environment is constructed based on a BIM model, GIS data and geological basic data, drill holes are arranged in combination with national engineering investigation standards, the obtained actual drill hole data are collected and accepted based on a mobile terminal program, drill hole arrangement information and the actual drill hole data are input into a drill hole data structure standard library, and the drill hole arrangement information and the actual drill hole data are recorded into the drill hole data structure standard library. A histogram is generated by using a drilling data standard library, and finally, drilling and drilling data are displayed based on a three-dimensional visual environment, so that the problems of low drilling layout efficiency, unreasonable drilling scheme, low data acquisition efficiency, high error rate and low drilling data structuring degree in the prior art can be solved; and on the other hand, a digital collaboration platform is constructed, lagging and distortion of information transmission are reduced, and information sharing is promoted.

The invention belongs to the field of computer vision game anti-cheating, and discloses an FPS anti-cheating method based on deep learning and vision, and the method comprises the following steps: 1, game data preprocessing: zooming an input image to the input size of a network, and carrying out the normalization operation; 2, performing feature extraction on the input image: introducing a focus module into a backbone network part to cut the image, and splitting the high-resolution image into a plurality of low-resolution images or feature maps; 3, constructing a Neck module, wherein the Neck module is responsible for further optimizing and fusing the features on the basis of the features extracted by the backbone network; step 4, constructing a Head module; and 5, constructing a classifier module: analyzing the difference of the duration ratio, the frequency ratio and the open mirror killing ratio of effective aiming of the normal player and the plug-in player, and quantifying a data standard to judge whether the player is the plug-in player or not. According to the method, the plug-in players can be effectively detected.

The invention discloses a passenger data flow efficient integration method and system based on an aviation information data standard. The method comprises the steps that a to-be-integrated passenger order data flow and a to-be-integrated passenger check-in data flow are acquired, and the data format, the data structure and the data source of the passenger order data flow are different from those of the passenger check-in data flow; performing targeted format conversion on the passenger order data stream and the passenger check-in data stream to obtain a target passenger order data stream and a target passenger check-in data stream corresponding to the passenger order data stream and the passenger check-in data stream respectively; target fields are extracted from the target passenger order data flow and the target passenger check-in data flow; and based on the target field, integrating the target passenger order data stream and the target passenger check-in data stream to obtain a data integration result, and mapping the data integration result into a target data structure which conforms to the aviation information data standard. According to the invention, the technical problem of low accuracy of passenger data flow integration is solved.

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.

A communication method and system of a DPTP protocol, a product and a medium relate to the field of data transmission, and the method comprises the following steps: under the condition that a dot matrix pen establishes a connection with an upper end application, the dot matrix pen receives a protocol level and a data standard number sent by the upper end application to the dot matrix pen; the dot matrix pen returns a confirmation message to the upper end application, wherein the confirmation message comprises an equipment authentication strategy number; if the authentication strategy number indicates that authentication is needed, the dot matrix pen carries out authentication operation on an authentication instruction sent by the upper end application; under the condition that the authentication operation result is that authentication succeeds or the authentication strategy number indicates that authentication is not needed, the dot matrix pen packages the collected writing track data into message data in a data format according to the data format corresponding to the data standard number; and the dot matrix pen sends the message data to the upper end application. By implementing the method, the stability of data transmission between the dot matrix pen and the upper application can be improved.

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 present application discloses a data fusion method and system based on ERA5 reanalysis data and satellite observation data, and relates to the technical field of meteorological data fusion. The method comprises: firstly converting the altitude coordinates of the reanalysis data set from air pressure values ​​to corresponding altitude values, so as to facilitate subsequent matching and fusion; then dividing the reanalysis data set after the altitude coordinate conversion into a grid model according to a preset resolution, and calculating and fusion the parameters of the reanalysis data and the observation data according to the space-time grid as a unit; for each space-time grid, firstly calculating the mean value and standard deviation of the reanalysis data of the space-time grid, and then using the satellite observation data obtained by matching, calculating the mean value and standard deviation of the observation data, and finally determining the fusion data grid model; the present application adopts satellite observation data, and through the design of a reasonable data fusion algorithm, better corrects the ERA5 reanalysis data set, which is more in line with the actual atmospheric change characteristics.

The invention relates to the technical field of data real-time stream processing, in particular to a method and system for achieving FlinkSql statement configuration through a user-defined ETL process, and the method comprises the following steps: operation of a job development page, graphical configuration of the ETL process, column configuration and FlinkSql basic configuration items, functions, where conditions, join and output configuration, and generation, preview and storage of FlinkSql statements. The method and system for realizing FlinkSql statement configuration through the user-defined ETL process have the beneficial effects that the use threshold is reduced through visual operation through the user-defined ETL process nodes; different tables of a plurality of data sources can be associated by using join nodes, so that the data availability is expanded; the data can be cleaned by using the function configuration node, the data standard is standardized, and dirty data is removed.

The invention discloses a data integration method based on a data center. The method is based on data integration construction requirements of a multi-source heterogeneous data system, and comprises the following steps: firstly, establishing a data standard, constructing a data model, and establishing a unified specification for multi-source heterogeneous data in the system; building a data warehouse based on the data model, and storing data in the integration process; meanwhile, a data center is constructed, and data services such as data extraction, conversion, loading and display are provided by relying on an ETL technology and a data object encapsulation access method; and finally, distributing and synchronizing the integrated data by using a message middleware technology. Data integration of the multi-source heterogeneous data system can be achieved, and the method has the advantages of being high in stability, low in coupling, high in availability and the like.

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 a rehabilitation department nursing health big data sharing platform, which comprises data acquisition, storage, analysis, user authority management and other modules. The data acquisition module is connected with multiple terminals such as a hospital information system, automatically acquires various data of patients, sorts and classifies the data, and comprises a cleaning unit to ensure data quality; a distributed architecture is adopted for data storage, and structured and unstructured data storage and backup redundancy are considered; the data analysis module comprises a plurality of sub-modules, can be used for mode mining, analytical statistics and illness state prediction, and is further provided with a personalized analysis unit. In addition, a data sharing interface module, a real-time monitoring and early warning module, a rehabilitation nursing knowledge pushing module, a platform interaction module and the like are arranged, cross-mechanism cooperation is supported, and user communication interaction is guaranteed. The platform integrates multi-source heterogeneous data, has the advantages of establishing data standards, achieving comprehensive deep analysis, improving data availability, promoting subject development, guaranteeing data safety and the like, and can improve rehabilitation nursing services and benefit patients and the society.

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.