467 results about "Data products" patented technology

The invention provides a surface soil humidity multi-source data fusion and downscaling method and system. The surface soil humidity multi-source data fusion and downscaling method comprises the following steps: performing quality evaluation and standardization processing on multi-source soil humidity data; carrying out anomaly detection and restoration by adopting a hierarchical spatial-temporal feature extractor; carrying out regional partitioning based on an adaptive boundary generation algorithm and a soft boundary transition model; data fusion and error control are realized through a regional cascade fusion network and an error chain tracking algorithm; and carrying out downscaling processing by utilizing a terrain adaptive downscaling framework and a multi-scale residual learning model to obtain a soil humidity data product with the resolution of 1km. The soil humidity data of complex terrains and high vegetation coverage areas can be effectively processed, the data fusion precision and downscaling effect are remarkably improved, and the technical problems of a traditional method in the aspects of data quality evaluation, anomaly detection, partition boundary processing, error control and the like are solved.

The invention relates to the technical field of waterlogging and waterlogging disasters, in particular to a remote sensing monitoring system and method for oilseed rape waterlogging and waterlogging disasters, which couple a new generation of earth observation satellite observation means, apply historical disaster data and observation data, identify key sensitive parameters of crop waterlogging and waterlogging disasters, screen oilseed rape waterlogging and waterlogging disaster monitoring and evaluation indexes and determine index parameters. Constructing a waterlogging disaster monitoring and evaluating model; respective advantages of ground observation data and satellite remote sensing data are fully utilized, advantages of microwave satellite remote sensing data and optical and thermal infrared satellite remote sensing data are utilized, and soil moisture content and precipitation data products with higher time and space resolution are formed through fusion; the problems that in the prior art, a traditional waterlogging disaster monitoring and evaluating means is difficult to match with new changes of current complex underlying surface conditions, and new requirements for monitoring and evaluating accuracy and timeliness at the present stage are difficult to meet are solved.

The invention relates to a multi-source remote sensing data quantitative inversion regional crop water consumption demand data fusion method. The method comprises the steps of data acquisition, data assimilation, data fusion and formation of a multi-source heterogeneous database. A distributed multi-source heterogeneous database is built by using advanced technologies such as comprehensive grid computing and cloud computing, a high-performance storage retrieval multi-source heterogeneous database and a data product oriented to a complex irrigation data system are built, agricultural information is collected in real time, a database is formed, and a database management system is established. And finally, efficient data management and sharing are realized. Related agricultural irrigation processes are systematically monitored, including monitoring of water consumption of crops, monitoring and forecasting of agricultural irrigation and the like. An agricultural production management system and an agricultural expert system are developed and are mainly used for diagnosing water shortage, fertilizer shortage and pest and disease damage of crops. The data acquisition forms are diversified, the parameter optimization quantity is large, the acquisition of large-range farmland parameters is realized, and a complete system is formed with remote sensing irrigation monitoring.

The invention relates to the technical field of credible data space, and provides a credible data space platform fusing multiple credible environments and a data use method, and the platform comprises a data credible circulation environment, a plurality of data credible supply environments and a plurality of data credible use environments. The data credible supply environment and the data credible use environment realize supply-demand link through the data credible circulation environment; the data credible circulation environment comprises a data product credible transaction environment and a data information credible delivery environment; a data operation platform is deployed in the data product trusted transaction environment and is used for shelving, browsing and ordering data products; according to the data information credible delivery environment, a block chain data internet is adopted, an encrypted digital asset account is opened on a block chain for each credible object, issued data information assets are stored, data right confirmation is realized through a multi-party encryption technology, and dynamic authorization of the data information assets is realized through a digital envelope technology. The method is not limited by a specific privacy computing technology architecture and is flexible to construct.

A method for monitoring and / or controlling a production of at least one chemical product, the method comprising: providing chemical product data related to a production and / or a processing of the chemical product, providing a plurality of chemical product data templates indicative of a structure associated with at least a part of the chemical product data, selecting at least one chemical product data template by determining at least one chemical product data template corresponds to at least a part of the chemical product data, generating contextualized chemical product data by merging at least a part of the chemical product data and the at least one selected chemical product data template, providing the contextualized chemical product data to a data-driven model for generating environmental property data related to an environmental property associated with processing and / or producing the chemical product, wherein the data-driven model is configured to provide the environmental property data in response to being provided by the contextualized chemical product data, providing the environmental property data for monitoring and / or controlling processing and / or a production of the at least one chemical product.

A system for converting a source data feed schema into a canonical data product including a memory for storing computer-executable instructions and a processor for executing the instructions stored on the memory. Execution of the instructions programs the processor to perform operations that include receiving a source data feed having a source schema, identifying a plurality of data fields of the source schema, assigning a data category from a plurality of predefined data categories to each data field of the plurality of data fields, modifying the source schema based on predefined parameters, wherein the source schema is modified to match a target schema, comparing the modified source schema to the target schema, and in response to a determination that the modified source schema matches the target schema, converting the source data feed to a canonical data product having the target schema based on the assigned data categories.

The invention relates to an intelligent data transaction matching method. The method comprises the following steps: constructing a user portrait through personal information and historical behavior record information of a data transaction buyer, and generating a user tag set for describing user features; performing multi-dimensional analysis on each data product on the platform to generate a product label set for describing product features; adopting a natural language processing technology and a machine learning algorithm to calculate the matching degree between the user label and the product label; according to the label matching degree, generating a product recommendation list according to a preset weight algorithm; and dynamically adjusting the recommendation strategy according to user feedback. According to the method, more accurate personalized recommendation is realized by comprehensively analyzing the user tags and the product tags, the accuracy and the user satisfaction of a recommendation system can be remarkably improved, the probability of successful business matching is improved by accurately matching user interests and product characteristics, and compared with a traditional recommendation algorithm, the method has the advantage that the recommendation efficiency is improved. The method has obvious advantages in the aspects of product characteristic identification, recommendation strategy adjustment and the like.

The invention discloses an intelligent logistics supply chain management system, and the system comprises a block chain information sharing platform which is responsible for building an information sharing platform based on a block chain, inviting all participants on the supply chain to join, and storing and transmitting the data of each link of the supply chain through the distributed account book technology of the block chain; the product information tracing system is responsible for distributing a unique block chain ID for each fresh food and recording the circulation process of the fresh food in a supply chain; and the collaborative management platform is responsible for integrating and uniformly managing data of purchasing, warehousing, transportation and sales, predicting future sales trend and inventory demand change by using a random forest according to historical sales data and market trend information, and optimizing an inventory level, a reorder strategy, a sales strategy and a promotion activity plan in combination with a genetic algorithm, so as to achieve the purpose of sales promotion. The inventory cost is minimized, the sales demand is met, and the block chain information sharing platform and the collaborative management platform carry out data synchronization.

The invention discloses an artificial intelligence auxiliary authentication method and system for data element right confirmation, and relates to the technical field of data element management and credible circulation. Comprising the following steps: data acquisition: acquiring a data product, an ownership statement and contract terms, and calculating an initial digital fingerprint of the data product; and ownership identification: extracting core value elements and features of the data product based on a multi-modal intelligent analysis model, quantifying value contribution weights formed by all links to the data product, and automatically generating a data element circulation graph. According to the method, the multi-modal intelligent analysis model is constructed, and the data product is deeply scanned and analyzed automatically, so that the dependence on predefined rules is reduced, and the intellectualization and automation of ownership identification are realized; by constructing an intelligent compliance verification model, data operation behaviors are monitored and compared in real time, substantive compliance control over the whole data use process is achieved, and a credible use closed loop is established.

The invention discloses a method for aggregating ocean buoy data, which comprises the following steps of: establishing a space-time correlation model according to the spatial distribution density of buoy clusters and the dynamic characteristics of an ocean environment, and adaptively dividing buoy groups with a data compression cooperative relationship; performing a data-related compression operation within the buoy group; constructing a transmission priority dynamic sorting engine, and calculating a dynamic weight coefficient; performing hierarchical packaging processing on the differential coding data, distributing enhanced forward error correction coding resources for high-priority data, and reserving redundant transmission time slots; the method comprises the following steps: receiving a hierarchical data packet through a low-orbit satellite and executing on-satellite preprocessing, reconstructing an original data stream by using a distributed decoder, and meanwhile, fusing multi-dimensional space-time related data to generate an aggregated data product; and finally, the aggregated data product is transmitted to a ground data center through a satellite downlink. According to the invention, uplink data volume is reduced, disaster monitoring timeliness is improved, ground station processing load is reduced, and system environment adaptability is enhanced.

The invention belongs to the technical field of hydrology and water resources, and discloses a cold and dry mountainous area drainage basin runoff simulation method based on an MIKE SHE / MIKE 11 coupling model in combination with GIS / RS data. According to the multi-source data fusion technology, a cold and dry mountainous area distributed input data set is constructed through TRMM satellite rainfall data, an MODIS LAI product and an ASTER DEM, and the rainfall space representation precision is improved by 40%. According to the model coupling mechanism, an MIKE SHE / MIKE 11 collaborative simulation framework is provided, earth surface-groundwater flow data interaction is achieved through river channel linkage, and the complex river network flood routing simulation error is reduced to 10% or below. According to the parameter partition calibration method, a drainage basin is divided into five hydrogeological regions, sensitive parameters such as a Manning coefficient and a hydraulic conduction coefficient are optimized in combination with a genetic algorithm, and the basic flow simulation precision is improved by 25%.

A computer-implemented method and apparatus for managing physical and digital products' customization using container format are disclosed. In some embodiments, the method comprises receiving a container file with serialized objects, deserializing these objects to form a hierarchical object structure, and interacting with a database to obtain real-time configuration data. Custom attributes of the products are defined by binding attribute / value pairs to the hierarchical structure. A visualization of the customized product is generated based on these pairs, and manufacturing instructions are determined considering the attribute / value pairs and manufacturing constraints. The apparatus comprises a memory and a processor to execute instructions for deserializing the container file, retrieving configuration data, organizing objects into a hierarchical tree, negotiating product customizations, and outputting manufacturing data. This system enables efficient and accurate production of customized products by managing data, rendering graphics, and incorporating manufacturing constraints.

The invention discloses a traffic data security encryption and circulation system and method based on a block chain, belongs to the technical field of traffic control, and aims to solve the problems of security, privacy and trust in traffic data sharing. The system comprises an edge computing node which is deployed near a data source and is used for performing encryption or privacy enhancement processing on original traffic data; a block chain network with a smart contract is deployed, node identities are managed, verification information is recorded, an access strategy is stored, and data circulation is controlled; and the data processing unit is used for aggregating the processed data to generate a circulatory data product. The method comprises the steps of edge security processing, block chain management verification, product generation by the data processing unit and management and control circulation of the block chain according to a strategy. Through edge security processing and a block chain trust mechanism, data security privacy is guaranteed, safe, transparent and credible circulation and utilization of traffic data are realized, and reliable data support is provided for intelligent upgrading and digital transformation of the traffic industry.

The invention provides a field-level rice yield remote sensing estimation method based on high-resolution total primary productivity and a dynamic harvest index, and the method comprises the following steps: firstly, obtaining a rice growth season time sequence Sentinel-2 image based on a remote sensing cloud platform, calculating a leaf area index, and obtaining meteorological data EAR5 products and CO2 data; then, a self-service sampling method and a multi-model process sensitivity analysis method are used for analyzing the influence rule of the rice growth season environment factors on the GPP, an improved double-leaf light energy utilization rate model is constructed, and high-resolution rice GPP high-precision estimation is achieved. And finally, forming an HIDYM method in combination with the dynamic harvest index to realize the yield estimation of the field-level rice in Jiangsu province for many years. The method can be used for quickly and accurately estimating the yield of the large-range field-level rice.

The invention relates to the technical field of electromagnetic situation visualization, and particularly discloses an electromagnetic space diagram design and implementation system and method, and the system comprises a space-based satellite electromagnetic spectrum surveying and mapping module, a surveying and mapping data processing module, and a data product generation module. The space-based satellite electromagnetic spectrum surveying and mapping module is used for acquiring global electromagnetic spectrum information and surveying and mapping the global electromagnetic spectrum information to obtain surveying and mapping data; the surveying and mapping data processing module is used for storing surveying and mapping data in a database in a grid division manner; preprocessing the surveying and mapping data to obtain standard electromagnetic spectrum data; screening required electromagnetic spectrum data from the standard electromagnetic spectrum data according to application requirements; and the data product generation module is used for generating an electromagnetic space diagram based on the required electromagnetic spectrum data, and visualizing and applying the electromagnetic space diagram. According to the system, multi-level, multi-dimensional and multi-scale expression of electromagnetic spectrum surveying and mapping data is realized, and organization and application of global electromagnetic spectrums are realized.

A system, a method, and a device for authentication of a product includes one or more databases configured to store data of one or more products, and a user device communicatively coupled to the databases via a network. The user device includes at least one memory configured to store computer executable instructions, and at least one processor configured to execute the computer-executable instructions to receive, from an authenticator, product search data of the product, and to search the product in the databases based on the product search data. The product is listed by a user for authentication, and the product is authenticated by scanning an authentication tag attached to the product. The authentication tag is pre-programmed and becomes inactive when detached from the product. There is also a dual-purpose device for authenticating a commercial product and associating a brand with the authentication of the product.

The invention provides an electric power data product quality evaluation system. The system comprises a data acquisition module; the rule generation module is used for extracting data features from the power data and inputting the data features into a rule generation model obtained through training to output a candidate rule set, and rules in a candidate rule base are reordered based on service weights to obtain a recommendation rule set; the dynamic threshold value optimization module is used for dynamically updating an abnormal threshold value based on the data distribution condition of the power data in the historical time period and the business demand adjustment coefficient; the quality evaluation module is used for performing quality evaluation on the power data based on rules in the recommendation rule set and corresponding abnormal thresholds to obtain a quality evaluation result; and the feedback optimization module is used for feeding back and adjusting the rule generation module and the dynamic threshold optimization module based on the quality evaluation result, and realizing intelligent recommendation and dynamic threshold optimization of the power data quality evaluation rule and self-adaptive updating of the rule base.

The embodiment of the invention provides a method and a system for processing ocean multi-parameter wide-width imaging data of a Beidou interference altimeter, and relates to the technical field of GNSS-R. The method comprises the following steps: constructing a set of complete and strict data processing chain; through precise calculation of a GNSS-R direct signal and reflection signal delay inequality interference geometric model and correction of actual measurement delay inequality errors, systematic errors in the process of converting original signals into geophysical parameters are remarkably reduced, and the precision and reliability of parameters obtained through final inversion are improved. And on the basis of a self-adaptive data collection strategy of parameter space-time transformation characteristics and a spatial interpolation reconstruction process, discrete strip data is intelligently'woven 'into a continuously-covered wide-swath imaging type data product, so that the data format better meets the analysis requirements in the fields of oceanography, climatics and the like, and the intuition and usability of the product are improved.

The invention relates to a part generation method based on atomization disassembly and encapsulation data. The part generation method comprises the following steps: step 1, analyzing a demand scene; step 2, carrying out atomization disassembly; step 3, performing standardization verification; step 4, packaging the function logic layer; step 5, packaging the element part layer; 6, packaging an interface layer; according to the method, the problems of function solidification and difficult splitting of a traditional data product are solved, and efficient circulation and value release of data elements are promoted; and reusability and circulation efficiency of data parts are improved through the element part layer.

The invention provides a step optimization method, medium and system for a complex industrial process, and belongs to the technical field of big data modeling, and the method comprises the steps: building a multi-dimensional data collection system, installing a sensor and a monitoring device at a key node of a target industrial process, collecting process parameter data, equipment state data and product quality data in a parallel multi-thread mode to form an original data set, and collecting process flow connection relation data; performing time domain decomposition operation on the original data set, decomposing each data into a long-term stable numerical component and a short-term fluctuation numerical component, and respectively obtaining a process parameter stable component, a process parameter fluctuation component, an equipment state stable component and an equipment state fluctuation component; according to the technical scheme of the invention, the problem that the product cannot stably operate in the optimal state can be solved.

The invention discloses a virtual environment modeling method for an OHT system of a semiconductor factory, and belongs to the technical field of semiconductor production, and the method comprises the following steps: data collection and preprocessing: collecting field facility data of a semiconductor factory production line, operation related data of an OHT vehicle, and product information data, and carrying out the preprocessing of the data, so as to obtain basic data; virtual environment modeling: constructing a virtual environment model according to the basic data; simulation and optimization: carrying out simulation operation based on the constructed virtual environment model, and carrying out performance evaluation; then, optimization is carried out according to a simulation result and a performance evaluation condition; and verifying and applying a result. According to the method, accurate modeling and simulation are carried out on the OHT system, the configuration and scheduling strategy of the OHT system is optimized, resource utilization can be optimized, the cost can be reduced, and the stability, reliability and flexibility of the system can be enhanced.

A system for event-driven distributed data network analysis, the system includes: a multitude of domain data nodes, each comprising a stream storage, a multitude of transformation pods, and a product API, with each domain data node ingesting heterogeneous event streams, validating schema compliance, performing enrichments, and making data products available under versioned schema contracts; each domain data node further comprises a hardware-based edge intelligence appliance comprising an enclosure, a compute module with heterogeneous processing units selected from CPUs, GPUs, and TPUs, a secure enclave module for confidential execution of transformation code on encrypted data, a protocol-structured stream storage medium supporting multi-level retention, and industrial I / O interfaces configured for direct interaction with sensors, programmable logic controllers, and cloud-native services; an event mesh backbone processor configured to connect the multitude of domain data nodes via a publish-subscribe architecture, with the backbone guaranteeing exactly one-time delivery, partition-level sorting, and geo-replicated durability; a Contextual Intelligence Engine coupled with the Event Mesh Backbone processor, the engine comprising a semantic graph memory and a Streaming Graph Reasoner configured to map raw events into an ontology, perform graph joins in real time, and recognize composite causal patterns across multiple domain data nodes; a governance and policy control unit integrated into both the data and control layers. This layer enforces zero-trust security, role-based access control, real-time provenance tracking, and regulatory compliance; and An actuation interface coupled with the contextual intelligence engine and the governance layer. The actuation interface is configured to generate control commands for operational technology devices and digital workflows, thus closing the loop from data acquisition to autonomous decision-making.

The invention relates to the technical field of big data management, in particular to a big model metadata authority management method and system based on an RBAC-ABAC fusion model, and the method comprises metadata annotation, data product release, big model and user access, semantic perception, dynamic authority adjustment, row-level authority control and authority life cycle management. The method has the beneficial effects that by fusing the advantages of the RBAC model and the ABAC model, the defects of a single authority management model are overcome, the efficient, dynamic and fine-grained authority management of the large model metadata is realized, the security of the large model metadata is improved, and the authority management requirement of the large model for accessing the dynamic business data is met.

The embodiment of the invention provides a structured data field use control method and device, a medium and a product, and relates to the technical field of data use. The method comprises the steps of obtaining a data product published by a data provider; the data product is formed by accessing structured data into a data space in a data source form by a data provider; binding a target strategy generated based on the structured data to the data product, and determining a bound target data product; the target strategy comprises a post strategy and a calculation strategy executed at a first trusted connector of the data user, and a pre strategy executed at a second trusted connector of the data provider; and performing data contract signing with the data provider according to the target data product. The method is based on a structured data form, and is more accurate than traditional privacy calculation control; the target strategy and the data product are directly bound, and a traditional strategy configuration mode based on a central server is replaced.

The invention provides a data consanguinity establishing method, which comprises the following steps of: reading metadata of a technical index configured for a data product, and acquiring an identifier of the technical index from the metadata of the technical index; reading metadata of a business index configured for the data product, and obtaining an identifier of the business index and an identifier of a technical index associated with the business index from the metadata of the business index; reading configuration information of an application program of the data product, and obtaining an identifier of an application index related to the application program of the data product and an identifier of a technical index associated with the application index from the configuration information; and determining an association relationship among the technical index, the business index and the application index based on the identifier of the technical index, the identifier of the business index, the identifier of the technical index associated with the business index, the identifier of the application index and the identifier of the technical index associated with the application index. The invention further provides a data blood relationship establishing device, electronic equipment, a storage medium and a program product.

The invention discloses a dynamic pricing method and system for data trust transaction, and relates to the field of data processing. The dynamic pricing method for the data trust transaction comprises the steps of obtaining related data of a to-be-priced data product, wherein the related data comprises production cost, service cost and a market supply and demand relationship; the related data is input into a preset dynamic pricing model, the price of the data product to be priced is determined, and model parameters in the preset dynamic pricing model can be adjusted according to historical transaction data of the data product and the related data of the data product.

The invention relates to the technical field of data product pricing, and discloses a data pricing method based on multi-dimensional value evaluation, a terminal and a storage medium. The method comprises the steps of performing desensitization processing on data needing to be priced based on a differential privacy mechanism, generating a privacy budget value and a privacy risk value of the data, and obtaining a privacy score according to the privacy budget value and the privacy risk value; generating a quality score of the data according to the evaluation index of the desensitized data on the specified task; calculating a dynamic weight coefficient meeting the optimal privacy budget value by using a dual-objective optimization algorithm, wherein the dynamic weight coefficient is used for balancing a privacy protection objective and a data quality objective; and based on the privacy score, the quality score, the dynamic weight coefficient and the cost information of the data provider, generating a data pricing formula by using a meta-learning model, and outputting a pricing result. According to the invention, fair and reasonable data pricing is realized, the expectation of the data purchaser for the data and the leakage risk of the data provider are balanced, and the healthy development of the data transaction market is promoted.

The invention relates to an urban fine-scale day-by-day atmospheric pollutant concentration estimation method, which comprises the following steps: acquiring urban region multi-source data, and performing multi-scale space-time matching processing; constructing a global estimation model of the atmospheric pollutants and training the global estimation model; obtaining the annual global atmospheric pollutant concentration under the fine scale of the urban area, and converting the annual global atmospheric pollutant concentration into a global atmospheric pollutant concentration weight; calculating a day-by-day local atmospheric pollutant concentration estimation residual error; and estimating to obtain the urban fine-scale day-by-day atmospheric pollutant concentration. The method has the beneficial effects that global features and local changes are comprehensively considered, the spatial resolution of an existing data product in a city is effectively improved, a high-precision hectometer-level day-by-day atmospheric pollutant data product is obtained, a polluted area can be positioned more accurately, and the method has a wide application prospect. Therefore, formulation and implementation of accurate prevention and control measures of urban atmospheric pollution are more scientifically guided, and the method has important application value.

The invention relates to the technical field of industrial automation, in particular to an industrial manufacturing equipment intelligent control system based on the Internet of Things, which comprises a manufacturing data acquisition module used for acquiring equipment parameters of manufacturing equipment and demand parameters of manufactured products, a real-time data acquisition module used for acquiring workshop environment data and equipment operation data in real time, and a processing module used for processing the workshop environment data and the equipment operation data. The product parameter analysis module is used for dividing manufacturing demand levels and constructing a demand standard index according to a division result, the manufacturing environment monitoring module is used for analyzing the environmental abnormality of a workshop, and the equipment monitoring module is used for monitoring the environmental abnormality of the workshop. The monitoring module is used for analyzing the operation state of each piece of manufacturing equipment in a workshop according to the equipment operation data collected in the monitoring period and analyzing the operation state of a production line according to the analysis result, and the equipment control module is used for controlling the manufacturing equipment in the next monitoring period. According to the invention, the equipment control efficiency in the industrial manufacturing process is effectively improved.

The invention discloses a forest biomass and carbon library metering technology based on sample plot survey information, the technical scheme comprises a data acquisition system, a data processing and conversion module and a data website module, the data acquisition system is a basic part, and the data processing and conversion module is a core part. And the data website module provides data products and visual display for the user. Each tree is managed through a two-dimensional code, automatic quality control is performed based on historical survey data, forest vegetation biomass and carbon reserve situations of a quadrat and a sample plot are calculated by associating information of each tree of the quadrat and the sample plot, and a forest vegetation carbon sequestration rate and a carbon sequestration function are obtained by comparing previous survey data. According to the system, the investigation efficiency can be greatly improved, the forest vegetation carbon source function can be evaluated in real time, historical data can be used for automatic quality control of each re-investigation, investigation data can be uploaded in real time, and the working efficiency can be improved by more than 20 times through the application of the system.