689 results about "Data resources" patented technology

The invention provides a multi-source heterogeneous data integration and governance-oriented data weaving method, which comprises the following steps of: performing data acquisition from an accessed multi-source heterogeneous data source to generate an original multi-source heterogeneous data stream; performing standardization processing on the original multi-source heterogeneous data stream to generate a standardized multi-source heterogeneous data set; performing active content scanning processing on the standardized multi-source heterogeneous data set to determine business metadata, and performing consanguinity tracking processing on the business metadata to generate enhanced business metadata; calling a domain ontology framework to carry out standardized constraint on the enhanced service metadata to obtain standardized service metadata without cross-data source semantic ambiguity, and carrying out implicit association mining processing on the standardized service metadata based on a graph neural network to generate a semantic knowledge graph containing core entities and relationships; and performing logic abstraction processing on the distributed data resources according to the semantic knowledge graph to generate a unified data access interface.

The invention belongs to the technical field of data storage, and discloses a multi-source marine environment data storage method and system based on HDF5. According to the method, a hierarchical storage framework is constructed, a domain-type-source three-level directory architecture is constructed, a space-time dimension dynamic extension mechanism is executed, and space-time composite coding is performed; designing an HDF5 nested packet storage architecture, wherein grid topological structure definition, dynamic resolution self-adaptive storage, multi-source data processing and metadata management are carried out; constructing distributed data association and indexes, including data standardization preprocessing and cross-source data association; the storage performance is optimized and expanded, wherein density sensitive blocking and layered compression are carried out. According to the method, redundant storage of a high-latitude region is greatly reduced, and dynamic adaptation of a local encryption grid is supported. According to the invention, open circulation and collaborative utilization of interdisciplinary data resources are facilitated.

This disclosure describes utilizing a causal query system to determine causal outcomes for domain-specific causal queries using a framework that includes causal graphs for targeted domains, a large generative model (LGM), and other models or systems. In various implementations, the causal query system provides a framework that includes generating domain-specific causal graphs, encoding or mapping the causal graphs with local data values, and using the encoded causal graphs to determine causal outcomes to causal queries. In some implementations, the causal query system uses the LGM and data resources (e.g., external sources) to populate missing values of an embedded causal graph before using the causal graph to determine causal outcomes.

A data management system may include data connectors configured to establish connections with access control systems and receive heterogeneous metadata related to the data access history. The system may include a transformer that stores graph objects in memory. The graph objects may include application account nodes representing application accounts associated with the domain and resource nodes representing data resources associated with the domain. The system may further store event objects. The system may render for display a data access graph that illustrates a data permission traversal path from a source node to a particular data resource. The data permission traversal path may include a graphical representation representing the particular application account having permission to access the particular data resource. At least a portion of the graphical representation may be rendered according to the data access activity level of the particular application account accessing the particular data resource.

The invention discloses an AI-based meter reading data management and resource scheduling optimization method and system, and relates to the technical field of intelligent management of meter reading data. The method comprises the steps that meter reading data of a meter is obtained, and the meter is provided with a corresponding two-dimensional code metal identification piece; meter reading data are managed according to geographic areas and user types, a multi-level data feature system is formed, and the user types comprise resident types and industrial types; carrying out trend modeling on the multi-level data characteristic system by adopting an AI model so as to determine an energy consumption trend in a future period; dynamically adjusting a meter reading task according to an energy consumption trend and a network load condition so as to dynamically schedule human resources, data resources, network resources and hardware resources; wherein the power grid topology position code is used for binding an association relationship between the meter reading task and the power grid physical conduction path. According to the invention, full-link optimization from meter reading data acquisition to resource scheduling is realized.

A data management system establishes connections with access control systems which are delegated by a domain to control data access and maintain data access history associated with the domain. The system receives a group access permission of a set of data resources to a group of named entities and heterogeneous sets of metadata related to the data access history and generates graph objects. The graph objects include named entity nodes and resource nodes. The named entity node represents a named entity associated with an organization, and the resource node represents a data resource. The system traverses access paths that connect the named entity node and the resource node determines a utilization level of a set of access paths. Based on the utilization level, the system revokes the set of access paths, thereby revoking an access permission of the set of named entity in the group to the specific data resource.

The invention provides an agricultural problem prediction and decision support system based on a large model, and the system comprises a data collection and preprocessing module which is used for collecting data resources of a plurality of channels, and carrying out the data cleaning, data conversion and data storage through a distributed calculation framework; the intelligent agent large model module comprises a large model for agricultural problem prediction, and the large model is trained by adopting historical data; the policy response module is used for extracting information in the policy file, converting the information into structured data and providing a calling interface; and the decision support module is used for generating specific farming activity suggestions based on the structured data in the policy response module and the prediction result of the agent large model module. The system provided by the invention can dynamically provide suggestions in response to farming activities according to crop growth conditions.

The invention relates to the technical field of data resource management, in particular to an online evaluation method for data resource value, which comprises the following steps of: constructing a multi-dimensional evaluation index set, and acquiring metadata and market dynamic information of to-be-evaluated data in real time through a distributed interface; carrying out weight distribution on the index set based on a dynamic weighting algorithm, generating a weight coefficient set and constructing a value calculation model; performing standardized preprocessing on the collected original data, inputting the data into the model, and calculating an initial estimated value; and dynamically correcting the initial value estimation value based on the timeliness attenuation factor and the data scarcity factor, and generating a final value estimation value and an estimation report. Through multi-dimensional index construction, a dynamic weighting algorithm, standardized preprocessing and two-factor correction, automatic evaluation of the data value is realized, the problems of single dimension, static weight and neglect of timeliness scarcity of a traditional method are solved, the real-time performance and scientificity are improved, and a quantitative decision basis is provided for data capitalization.

The invention discloses a data governance method and device based on an MCP protocol and a medium, and the method comprises the steps: obtaining a language instruction of a user through a data center regulation and control MCP client, determining a data governance demand according to the language instruction, and determining an obtaining request according to the data governance demand; and sending the acquisition request to the MCP server to acquire the data resource through the MCP server, and performing data processing according to the data resource. The data governance process is started through the natural language instruction, user operation is facilitated, and the use threshold is lowered. And the data governance demand and the acquisition request are accurately determined through the analysis instruction, so that the governance pertinence is improved. And resources are obtained and processed by means of the MCP server, so that efficient data management is realized. According to the process, user requirements and data acquisition and processing links are integrated, so that data management is more convenient, accurate and efficient.

A system establishes connections with a data resource system and connections with a security monitoring system. The system receives metadata related to data access history of the data resources from the data resource system and risk related signals associated with data access activities from the security monitoring system. The system generates an access graph comprising graph objects that are connected by access paths signaling access levels of the data resources controlled by the data resource system. The system aggregates the metadata from the data resource system, the risk related signals from the security monitoring system, and data associated with the access graph to generate normalized risk signals and identifies a cybersecurity risk-related instance associated with an access paths in the access graph. The system generates an alert which allows a user to adjust access privilege of a data resource associated with the cybersecurity risk-related instance.

The invention relates to the technical field of intelligent customer acquisition, in particular to a cross-border supply chain financial service AI intelligent customer acquisition system based on big data analysis. Functional components such as a big data access engine, an artificial intelligence analysis model, a customer portrait modeling engine, a preference setting interface, a public opinion and risk identification module, an intelligent screening engine and a docking output module are integrated; multi-source data such as customs data, trade data, enterprise industry and commerce data, judicial public data, international manufacture and cutting lists and internet public information from all places around the world are widely fused. The system performs modeling calculation on industry categories, regional distribution, export history, transaction records, public opinion trends and compliance risks of import and export enterprises, establishes customizable customer optimization rules, accurately outputs a target customer list which can be covered by credit insurance and financing service in combination with a machine learning algorithm, and attaches contact information. Various import and export related data resources can be accessed, automatic screening and output of credit insurance and account receivable financing adaptive exporters are realized through preference setting and AI analysis, the customer obtaining efficiency is remarkably improved, the marketing and risk control cost is reduced, and the economic benefit is improved. The problems that traditional cross-border supply chain financial service customer obtaining depends on manual recommendation, offline visit and a static customer library, the efficiency is low, and small and medium-sized export enterprises are difficult to cover are solved.

The invention discloses a multi-dimensional evaluation method for credential environment migration, and particularly relates to the field of evaluation. According to the method, an evaluation index system covering infrastructure, an application system, data resources and security compliance is constructed, and comprehensive scanning is realized through instruction set detection, binary analysis and equal security compliance inspection; dynamically calculating the weight by adopting an AHP-entropy weight hybrid model, and triggering weight rebalance based on the volatility; through combination of static scanning and a dynamic probe, the compatibility, performance and safety differences are quantitatively analyzed; and finally, generating a visual risk assessment report, integrating data of each stage to calculate a compatibility score, a performance loss rate and a security level, providing instruction level difference comparison, a performance flame graph and a vulnerability attack path interaction view, and outputting a migration suggestion comprising a priority reconstruction list, an NEON instruction optimization scheme and a staged reinforcement plan.

The invention discloses a multi-source data resource key information mining method and system, and the method comprises the steps: obtaining multi-source data of various forms and types, and carrying out the preprocessing; performing division according to data types; word frequency statistics and word correlation analysis are carried out on the character data, and numerical value meanings of the digital data are extracted through context semantic correlation; constructing a cross-modal key information data set based on the key information data set of each data type; designing a multi-branch long-short-term memory neural network model, inputting a cross-modal key information data set into the model for training, and generating key information mining models for different fields by dynamically adjusting network parameters; and selecting to carry out key information real-time extraction and updating on the optimal model, generating a knowledge graph, and carrying out visual operation. The method has the advantages that through multi-source data fusion and processing, the long-short term memory neural network model is combined, the knowledge graph is generated, and domain-specific key information mining and visualization operation are efficiently carried out.

The invention relates to an enterprise multi-dimensional business index analysis data resource optimization method, a medium and equipment, and the method comprises the steps: collecting a multi-dimensional business index analysis request of an enterprise business system, carrying out the mode recognition and feature extraction of the multi-dimensional business index analysis request, and generating business entity features; and inputting the business entity features into the resource allocation model, outputting a priority score and a resource demand prediction result, calculating an optimal resource allocation scheme through an optimization decision model based on the priority score and the resource demand prediction result, and performing automatic resource scheduling according to the optimal resource allocation scheme to generate a business decision instruction. And finally outputting a business decision instruction and a data resource management report. The resource reuse potential among different requests is automatically identified and quantified by adopting a set similarity algorithm, so that the enterprise data resource utilization efficiency is remarkably improved, the redundancy calculation consumption is reduced, and the resource allocation is more reasonable and efficient; manual intervention is reduced, and enterprise data resource management efficiency and response speed are improved.

In a cross-security-region resource access method in a cloud computing system, a virtual block device, which is simulated by a virtio protocol-based BLK front-end driver in the cloud computing system and taken as an RPC calling client, receives an IO access request for data resources maintained by a resource service program triggered by a business application installed on each virtual node through a simulated RPC channel on the virtual block device; in response to the IO access request, encapsulates the IO access request into an RPC request for performing an RPC calling for target data resources, sends the RPC request to a RPC calling server program simulated by a virtio protocol-based BLK service through the RPC channel, so that the RPC calling server program submits the RPC request to a resource access agent program, which submits the RPC request to the resource service program to complete cross-security region resource access.

The invention discloses a data transmission method and device, electronic equipment, a storage medium and a program product. The method comprises the following steps: determining a to-be-sent data volume quota application; sending the to-be-sent data volume quota application to a receiving end, so that the receiving end determines a data volume quota and issues the data volume quota based on application information carried by the to-be-sent data volume quota application; distributing the data volume quota issued by the receiving end to a data transmission queue corresponding to the to-be-sent data volume quota application, so as to update the data volume quota balance of the data transmission queue corresponding to the to-be-sent data volume quota application, and obtaining the updated data volume quota balance; and through a data transmission queue corresponding to a to-be-sent data volume quota application, transmitting a data stream to a receiving end based on the updated data volume quota balance. According to the invention, the receiving end can dynamically allocate a proper amount of data volume quota according to actual needs, and the data resource waste of the receiving end in the transmission process is reduced.

The invention provides a geographic knowledge complex question-answering method based on a space-time agent architecture. The geographic knowledge complex question-answering method comprises the following contents: natural language analysis: accurately understanding intentions of users and information contained in questions; multi-modal geographic entity recognition: processing non-text data contained in user input; generating a WKT format and injecting a prompt; knowledge graph retrieval enhancement; in the spatial computing tool chain arrangement, an LLM generates a problem solving scheme after combining multi-modal information, WKT geometry and related data resources associated with a knowledge graph, tools or functions needing to be called and an execution sequence of the tools or the functions are listed, and the series of tools adopt a model context protocol; in answer generation and response, the method can effectively solve the problems that in the prior art, when complex geographic questions and answers are processed, question input recognition is incomplete, reasoning steps are not accurate, and the answer basis is not real, and more intelligent and reliable question and answer support is provided for the field of natural resource planning and the like.

The invention relates to the technical field of artificial intelligence, in particular to an intelligent pre-auditing system and method for public data resource registration elements with a large model, and the method comprises a management side rule base construction step and an operation side auditing step. The method has the beneficial effects that automatic extraction, structured conversion and compliance pre-auditing of registration elements are realized by applying a multi-modal data analysis engine and a large model technology, and manual intervention links are reduced by more than 40%. A multi-dimensional rule knowledge base containing national standards, industry specifications and local regulations is constructed, dynamic loading and self-adaptive updating of verification rules are supported, and the adaptability to different types of data resources is improved. And a pre-auditing device based on the micro-service architecture is designed, and technical support is provided for marketization configuration of data elements. Through pre-auditing quality problem big data of process precipitation, the standard conformity of a data production end is reversely optimized, and a'registration-feedback-improvement 'closed-loop treatment mechanism is formed.

The invention discloses a data access control method and device, and relates to the technical field of cloud computing. The method comprises the steps that an access control strategy for a target data resource is acquired, the access control strategy of the target data resource indicates a target data table, and then in response to an operation request for the target data resource triggered by a user, a resource identifier of the target data resource and a user identifier of the user in the operation request are extracted. Querying a target data table based on the operation request to obtain target permission data having a mapping relationship with the user identifier in the target data table, and if the target permission data comprises the resource identifier, passing the authentication; and if the target permission data does not comprise the resource identifier, the authentication is not passed. According to the method, access control with data as granularity is realized, whether the access authority exists or not is determined by inquiring whether the target authority data comprises the resource identifier or not, and the maintainability of an authentication system and the access control efficiency are improved.

The invention relates to the technical field of authority management, and discloses a dynamic authorization and authority management system applied to an agent application system, and the system comprises a user agent module which receives an operation access request of a user for a resource, returns a result according to an authentication and authorization module, and allows or rejects the operation access request; the authentication and authorization module is used for receiving the operation access request, calling the role management module for verification and returning a result to the user agent module; the role management module is used for managing user information, roles and permissions and establishing association and corresponding permissions between the users and the roles or the virtual roles; the dynamic permission adjusting module is used for monitoring operation of the resources and adjusting the permission of the role or the virtual role; the data resource management module is used for operating and accessing data resources; the model management module is used for operating and accessing the model; the intelligent agent management module is used for operating and accessing the intelligent agent; according to the invention, the dynamic authorization of each resource in the intelligent agent application system and the independent management of the authority are realized.

The invention discloses a low-code platform design system based on modularization and a dynamic extension component, and relates to the technical field of low-code development, and the system comprises a form module which is used for standardly defining a data model and dynamically rendering a user interface, realizing unification of form configuration through a structured metadata specification, and establishing a form module; bidirectional binding of the view and the data model is realized; the process module is used for realizing modeling, execution and state management of a business process, supporting automatic task scheduling and multi-instance management based on standardized process elements, and keeping consistency of a process state through an increment synchronization mechanism; and the data processing module is used for cooperatively managing platform data resources, supporting dynamic expansion and decoupling dependence between the form module and the process module through an event-driven mechanism. According to the method, the strong binding relationship between the decoupling form and the process is established, the reusability of the process module is improved, and the process module is independent of the form and can independently provide API service to the outside, so that the method is adaptive to more business scenes.

The invention discloses a method for constructing a three-dimensional geographic entity and a three-dimensional electronic map, which comprises the following steps of: firstly, classifying acquired basic surveying and mapping data based on a constructed multi-level classification framework, and determining an entity category to which each element in the basic surveying and mapping data belongs; then, according to entity category design mapping data corresponding to the elements, converting the mapping data into a geometric mapping relation and an attribute mapping relation of a two-dimensional geographic entity, and through the geometric mapping relation and the attribute mapping relation, converting the mapping data and the attribute information corresponding to the elements into geographic entity geometry and geographic entity attributes; semantized geographic two-dimensional entities are generated to effectively inherit and structurally reuse stock data, and massive waste and repeated construction of data resources are avoided. And then, selecting a corresponding three-dimensional conversion method according to the type of the two-dimensional geographic entity, and converting the two-dimensional geographic entity into a three-dimensional geographic entity. And finally, constructing a corresponding three-dimensional electronic map according to the three-dimensional geographic entities corresponding to all the elements.

The invention discloses a cross-industry data sharing method and system using a trusted data space, and relates to the technical field of data sharing, and the method comprises the steps: obtaining a cross-industry data dimension relation; obtaining a sharing request, and carrying out dimension migration analysis on the sharing request to obtain a dimension migration path set; according to the dimension migration path set, adaptive reorganization operation is executed on the to-be-shared data, and reorganized shared data is obtained; according to the cross-industry data dimension relationship and the dimension migration path set, performing cross-industry confidence evaluation on the recombined shared data to generate a shared decision result; and performing data sharing on the recombined shared data through a secure channel of the trusted data space. The technical problems that existing cross-industry data sharing is difficult, and data resources are wasted are solved.

The invention provides a real-time data processing method and system based on edge computing, and relates to the technical field of data processing.The data validity period is calculated through a composite decision model of terminal equipment physical sampling frequency constraint and preset service rules, the signal restoration accuracy requirement and the service scene emergency degree are effectively balanced, and the real-time data processing efficiency is improved. Overtime failure of key data or occupation of non-key data resources is avoided; the data transmission integrity in a bandwidth fluctuation environment is improved through a dynamic window cutting mechanism driven by a real-time network state; optimizing edge computing power load distribution in combination with a routing decision mapping strategy and a processing priority resource ratio; the terminal instruction reliability is improved based on hierarchical control of historical data abnormal value purification and geometric distance measurement; a complete technical chain from data acquisition, self-adaptive transmission cutting, aging precise arbitration and routing resource collaboration to closed-loop control feedback is formed, and the transmission efficiency, the resource utilization precision and the control stability of high-concurrency real-time data processing are enhanced.

The invention relates to the technical field of government affair data sharing, in particular to a government affair data security sharing and real-time interaction method and device, and the method comprises the steps: firstly deploying a government affair MCP Server cluster, carrying out the data calling and processing, then encrypting the data, and finally achieving the standardized packaging and convenient calling of government affair data resources. Compared with the prior art, 70% of cross-department API development workload can be reduced through an MCP standardized interface, the data leakage risk is reduced to 0.01% through an authority approval and data encryption mechanism, and the data analysis delay is reduced to the second level from the minute level through streaming communication.

The invention discloses a video image data cleaning method and system for urban rail transit engineering, and the method comprises the steps: calculating a video adjacent frame structure similarity index SSIM, dividing video blocks according to a threshold value, and constructing an index set; the method comprises the following steps: selecting at least one multi-modal large language model, performing feature preprocessing, cue word construction and model input to calculate scores, judging features by adopting a grouped voting mechanism, obtaining a feature matrix and retaining a background image; defining a feature block, constructing a matrix to obtain a sampling set, calculating a sampling interval according to a training sample demand, and sampling or supplementing synthetic data according to the interval to realize redundancy elimination; and counting the use amount of augmented categories, synthesizing data by using a model, matching the data through a discriminator and an auto-encoder, and fusing the matched data and the original data to complete augmentation, thereby achieving automatic cleaning of video image data. The data storage and management cost is reduced, and data resources are more reasonably configured.

The invention provides a port logistics intelligent simulation and decision optimization platform based on a digital twin technology, and the platform comprises a basic layer which provides calculation, storage, network and basic software support; the resource layer integrates data resources, model resources and algorithm resources and is used for managing port multi-source data, business process models and intelligent algorithms; the digital twinborn layer is used for constructing and maintaining a high-fidelity digital twinborn body synchronous with a physical port and realizing virtual-real mapping, dynamic data fusion and model self-evolution; the simulation layer is used for deducing based on the digital twin and comprises a simulation engine and an event driving and data interaction module; and the application layer is used for providing a user interface, analyzing decision and optimizing functions and supporting scheme simulation, evaluation and closed-loop optimization. According to the method, the high-fidelity digital twinborn body of the port can be constructed, real-time mapping, accurate simulation, prospective prediction and intelligent decision making of the whole process of port logistics are achieved, and a technical closed loop of data acquisition, digital twinborn, intelligent decision making and virtual-real linkage is formed.

The invention relates to the technical field of data processing, and discloses an industrial Internet of Things cloud platform data analysis method, which realizes distributed model training of a multi-node joint model and industrial Internet of Things data mining by adopting a distributed federated learning model training architecture so as to break through the problem of data resource islands of a traditional centralized training mode. Aggregating to obtain more effective industrial Internet of Things data; meanwhile, the distributed federated learning architecture can prevent leakage of local industrial Internet of Things data of each node, local use of the industrial Internet of Things data and local training of the model, thereby effectively ensuring the security of the industrial Internet of Things data.

The invention discloses a credible authentication method and device, equipment and a storage medium, and relates to the field of credible authentication, and the method comprises the steps: sending to-be-authenticated information to a basic support platform, so that the basic support platform verifies the to-be-authenticated information, and returning a target digital certificate to a target connector according to a verification result; determining a first credible authentication result based on the target digital certificate, and signing the target metric value to obtain a target metric value signature; verifying the target metric value and the target metric value signature to obtain a second credible authentication result, and triggering a target connector starting operation based on the second credible authentication result, so that the platform service encrypts the identity information and the data resources to obtain encrypted identity information and data resources; and obtaining a third credible authentication result according to the encrypted identity information and the data resource, and determining a target credible authentication result based on the first credible authentication result, the second credible authentication result and the third credible authentication result to complete credible authentication. And the credibility enhancement of the connector environment is realized.

A train operation intelligent dispatching system and method are provided, where the system includes: a data acquisition and control module, configured to collect multi-source data affecting train operation; a data processing module, configured to perform data aggregation on the multi-source data, and process the multi-source data to form multi-source data in a unified data format; a multi-disciplinary data resource pool, configured to perform real-time storage and updating of the multi-source data in the unified data format, and store historical multi-source data; an intelligent fault analysis module, having intelligent fault analysis models therein, configured to perform fault analysis based on the multi-source data to obtain fault analysis results of corresponding disciplinary systems, and output fault advance warnings of corresponding disciplinary systems according to the fault analysis results; and a process preplan module, configured to provide preplan handling processes corresponding one-to-one with external multi-disciplinary systems.