391 results about "Data call" patented technology

The invention relates to a system for realizing financial agent credible authentication based on distributed digital identity, which comprises a base layer, an identity layer, an authority layer and a business layer, and is characterized in that the base layer integrates distributed digital identity authentication service, subscription service and distributed storage service, and constructs a credible collaboration framework covering the whole life cycle; the identity layer is configured with a DID generation module, a DID verification module and a DID query module; the authority layer deploys a VC signing and issuing module, a VC verification module and a digital envelope module; the business layer comprises a client and a server between security institutions, and carries out cross-institution data calling through mutual trust verification and MCP message interaction. According to the system for realizing the credible authentication of the financial agent based on the distributed digital identity, through the fusion innovation of the distributed digital identity, the verifiable certificate and the block chain technology, the decentralization of identity authentication, the dynamic authority management and the full link of auditing and tracing are realized in a security industry agent cooperation scene.

The invention relates to a method and a system for storing and backing up electric power data of a data-in-data station based on use popularity, and belongs to the technical field of data-in-data stations, and the method comprises the following steps: classifying electric power business data into hot data, temperature data and cold data based on preset access frequency, time window and data volume index; according to a classification result and a business importance degree, storing hot data in an SSD cloud disk or a memory database, storing temperature data in a distributed column database, and compressing cold data and then archiving the cold data to an object storage or a tape library; dynamically configuring differentiated backup strategies for different types of data; automatic scheduling of storage and backup is realized through a cloud platform component, and hot switching of master and slave databases, OSS archived data recovery by a DataWorks tool and a remote multi-copy recovery mechanism are supported; and migrating data in advance in combination with a historical access prediction popularity trend, and triggering cold data compression and archiving when storage resources exceed 80%. The method is suitable for power industry scenes, the storage cost is optimized, and the data calling efficiency is improved.

The invention discloses a security management method and system for data asset transaction, and provides a new normal form of distributed evidence storage and automatic management for data assets through deep fusion of a block chain technology and an intelligent contract. Specifically, embedded coding on a semantic level is carried out on an asset use behavior log recorded in an intelligent contract and a preset data use strategy, and a fine-grained semantic verification mechanism is utilized to realize consistency automatic comparison of an actual behavior and the strategy. And once the deviation from the preset strategy or the existence of abnormal access is detected, the alarm prompt can be triggered in real time. Through the mode, the response capability of the system to violation operation or potential risk events is improved, each time of data calling can be ensured to be in a controllable and traceable state, unauthorized access and malicious operation are effectively prevented, and a safer, transparent and reliable operation environment is created for the whole data element market.

The invention provides a digital employee robot performance intelligent evaluation method and system, and relates to the technical field of data processing, and the method comprises the steps: carrying out the feature extraction of user interaction contents in all scenes; performing fluctuation detection, identifying a time period of abnormal fluctuation, and extracting user request content and robot response content in the time period; restoring the current session path based on a preset business process template, performing path consistency comparison in combination with a response rule of the robot under the path, and generating an abnormal node set if the path is interrupted or the response is offset; extracting a user request format, a robot response behavior and an external data calling state corresponding to each abnormal node, performing abnormal source analysis, calculating user input abnormity, and identifying an attribution probability of abnormity and data interface abnormity; according to the invention, autonomy and accuracy of robot performance intelligent evaluation are improved.

The invention provides a water conservancy information security protection method and system. The method comprises the following steps: S1, edge equipment physical security reinforcement; S2, dynamic encrypted data acquisition; S3, adaptive fragmentation redundancy transmission; a protection module is deployed in a water conservancy sensor and an RTU, equipment vibration, uncovering and environmental parameters are monitored, abnormal physical attacks or environmental overrun are detected, a secret key is automatically erased, a data protection mode is started, data leakage when equipment is physically damaged is prevented, data security of edge equipment is guaranteed, and the safety of the equipment is improved. And in cross-system data interaction, an MPC or federated learning technology is adopted, original data is locally reserved, and a block chain audit log is generated to record a calling behavior, so that data sharing is realized, data is ensured not to be locally out, data privacy is guaranteed, and a data calling tracing basis is provided.

The invention provides a dynamic data traceability method and system oriented to network security, and relates to the technical field of network security and data governance crossing, and the method comprises the steps: carrying out the real-time visual monitoring of a user interaction interface of a data transaction platform, and capturing the visual behavior information related to data calling; extracting feature parameters based on the visual behavior information to obtain a visual feature data set, and performing structured conversion on the visual feature data set to obtain a structured call log record containing visual behavior associated information; based on the structured call log record, extracting a time sequence, a frequency and a spatial distribution feature of a call behavior as basic indexes; a plurality of feature sampling states are dynamically selected in a monitoring time window, and a dynamic feature evaluation set is constructed based on the feature sampling states. According to the invention, the accuracy and controllability of network security protection in a data transaction scene can be improved.

The invention discloses a joint optimization clustering distributed photovoltaic power prediction method and system, and relates to the related field of distributed energy management, and the method comprises the steps: carrying out the local calling of data, carrying out the time sequence alignment, and constructing a multi-dimensional feature association number table; extracting geographic position information and historical output data to perform similarity analysis, performing spectral clustering, and outputting a photovoltaic cluster; collecting meteorological time series data according to the power prediction scale, inputting the meteorological time series data into the cluster power prediction model, and performing cluster power prediction; grid-connected space-time joint optimization is carried out according to the cluster-level power prediction value, and an energy storage charging and discharging scheduling strategy is output; after single-station fitting conversion is carried out and a distributed power prediction value is output, output deviation identification is carried out, and a fault node is positioned; and dynamically updating the energy storage charging and discharging scheduling strategy. The technical problems that existing power prediction is not high in precision, cross-cluster power optimization scheduling is difficult to achieve, and the power grid operation stability is poor are solved, and the technical effect of improving prediction accuracy and the power grid operation stability is achieved.

The invention discloses a display equipment intelligent voice interaction method based on a large language model, and the method comprises the steps: constructing a set of display equipment intelligent voice interaction system suitable for a complex scene based on a large language model technical framework through integrating a multi-stage audio processing module, an intelligent voice recognition module, a semantic understanding and intention recognition module and a multi-mode interaction control module; the voice enhancement technology is adopted, high-precision voice instruction capture and noise reduction processing can be achieved in a noisy environment, and geographic space parameters and operation logic implied in user intentions are accurately analyzed in combination with a deep semantic analysis engine; through a multi-mode fusion control mechanism, real-time linkage interaction between a voice instruction and display equipment is supported, natural and smooth voice control experience is provided especially for scenes such as three-dimensional space positioning and topographic data calling in a holographic geographical environment, and the system has strong error recovery capability and good expansibility and is suitable for being popularized and applied. The method is especially suitable for a voice control interaction scene in a holographic environment.

The present invention relates to the technical field of power systems. Disclosed is a relay protection external operation information intelligent management system, comprising: an input module, a data snapshot module, a data acquisition module, a data conversion module, a data storage module, a fault analysis module, a report generation module, a signaling alarm module, a data analysis module 0, and a real-time data calling module. The relay protection external operation information intelligent management system provided by the present invention provides multiple reliable data interaction modes, including wired transmission, wireless transmission and calling of other systems, for relay protection external operation information, and collects and analyzes the relay protection external operation information before a fault so as to provide powerful support for fault analysis of dispatchers and secondary personnel, thereby avoiding erroneous analysis and determination on the fault. The present invention achieves better effects in the aspects of applicability, network occupation and system cooperation.

The invention discloses a cross-system data processing method and device, equipment and a medium, and relates to the field of computer data processing. The method comprises the following steps: receiving a data calling request, wherein the data calling request comprises data extraction information and a requester system identifier; determining a requester data format based on the requester system identifier; obtaining source data from a provider system according to the data extraction information, wherein the source data is in a provider data format; converting the source data from a provider data format to a requester data format, and generating target data adapted to a requester system; and transmitting the target data to the requester system according to the requester system identifier. Through the method, the technical problems of inaccurate data processing and low efficiency among the systems caused by inconsistent data formats of multiple service systems in a power grid scene in the prior art are solved, and the technical effect of improving the accuracy and efficiency of data processing among the service systems of a power grid is achieved.

The application relates to a composite robot multi-modal data encryption transmission method and system and a terminal, and relates to data transmission, which comprises the following steps: collecting information of a composite robot; classifying and encrypting the collected information through a preset encryption algorithm to obtain encrypted information; acquiring data calling information of the composite robot; determining whether the data calling information is consistent with preset reference calling information; if the data calling information is not consistent with the reference calling information, continuously acquiring the data calling information; if the data calling information is consistent with the reference calling information, encrypting the data calling information through the preset encryption algorithm to obtain encrypted calling information; and decrypting the encrypted information according to the encrypted calling information to obtain target collected information and outputting the target collected information to a preset calling platform. The application has the effect of improving the security of composite robot data transmission.

A technical problem to be solved by the present invention is to provide a method for processing real-time accumulated data so as to rapidly search for a packet corresponding to a search condition from a large amount of data called a full packet. The method comprises: a network packet information reception step of acquiring at least one piece of information from flow information including 5-tuple information and package information including meta information, content information, threat detection information, asset information, URL information, and IP information; a step of generating a mapping table in which identification information of the package information and identification information of the flow information are indexed; and a step of generating data specialized for the flow information and storing, in a database, the data including the mapping table.

The invention discloses a subway tunnel full-section intelligent inspection robot system. The system comprises a mobile platform; a disease detection module; the data processing unit adopts an embedded industrial mainboard, is internally provided with a filtering algorithm and a ResNet50 deep learning model, processes the image and the point cloud in real time, automatically identifies the type, the position and the size of the disease and generates a three-level report; a main channel of the communication module is a double 5G industrial module, supports real-time uploading of a disease result, automatically switches a local cache when 5G is interrupted and supplementarily transmits the disease result afterwards, and is provided with a Bluetooth unit for on-site short-distance data calling; the power supply module adopts two groups of 12V / 100Ah lithium iron phosphate batteries which are connected in parallel, the endurance is greater than or equal to 4 hours, a brake energy recovery device is integrated, the battery is charged back during downhill or deceleration, the endurance is prolonged by about 15%, and one-hour fast charging is supported; and an auxiliary function module. According to the method, the consistency and reliability of detection data are remarkably improved, and a stable basis is provided for subsequent high-precision disease recognition.

The invention relates to the technical field of data sharing, and discloses an endogenous security government affair data sharing method based on a digital object architecture. Government affair data, metadata, computing resources and an access mechanism are packaged into a standardized data container, a multi-level government affair data space is constructed, and a collaborative architecture of cloud centralized management and control and edge node autonomous operation is achieved. Based on a digital object architecture, a unique identification code is allocated to each data resource, and accurate positioning and efficient access of data are realized through an identification analysis system. A dynamic heterogeneous redundant architecture and a mimicry judgment mechanism are adopted, potential attack risks are restrained from the bottom layer, and data sharing safety is guaranteed. And in combination with a block chain technology, the traceability and non-tampering property of the service directory and the data calling information are ensured. According to the method, the principle of'availability but not availability 'of data is considered, the efficiency, safety and supervision transparency of cross-department and cross-regional government affair data sharing are improved, and the method has important application value.

The invention provides a rainstorm flood disaster chain monitoring field knowledge graph construction method, and relates to the technical field of knowledge graph construction, and the method comprises the steps: carrying out the preprocessing of original multi-source disaster data, and obtaining various types of quality-controlled data; calling a disaster field fine-tuning large model and an ontology inference engine based on the preliminary corpus and the multi-class quality-controlled data to generate a core ontology and a sub-document set, screening the sub-document set to construct a document association graph, and calling a mapping model to match a structured data field and a core ontology attribute; performing triple extraction according to the sub-document set and the constructed three-level cue word template; ontology instance attributes are vectorized and clustered, a three-layer collaborative system and an atlas core structure are generated through domain conflict repair and pruning density adjustment, a data calling disaster domain fine-tuning large model is obtained based on a processing process to complement an instance implicit relationship of the atlas core structure, and a target knowledge atlas is constructed. According to the invention, construction of the knowledge graph in the disaster field is realized.

Various aspects of the present disclosure relate to a network system, user equipment (UE), method, and processor for wireless communication that supports rich data call establishment. The network system receives a message from an originating UE, and a first network entity obtains, from a second network entity, headers, payload, with token claims of a personal assertion token (PASSporT) extension for rich call data, and a private key certificate associated with a user identifier contained in the message. The first network entity creates a signature and at least one header of the PASSporT extension for rich call data, adds the signature in a first Session Initiation Protocol (SIP) header to the message, and transmits the message with the header to a third network entity for verification. When verified, the message with a second IP header is forwarded to a terminating UE to establish an IMS session with the originating UE.

The invention discloses a dynamic charge and discharge power adjustment method based on demand response, and relates to the technical field of charge and discharge power control, and the method comprises the steps: carrying out the historical data calling of a target power pool, and obtaining the historical discharge data; constructing and obtaining a discharge demand analysis model; performing data acquisition on the power supply area under preset environment acquisition conditions to obtain stable environment data; performing power supply mode identification to obtain a real-time power supply mode; synchronizing the stable environment data and the real-time power supply mode to the discharge demand analysis model to obtain a real-time discharge demand; and real-time discharge capacity is obtained through calculation, and charging power adjustment is carried out. The technical problems of low energy utilization efficiency of the power pool, poor power grid load optimization effect, high operation cost and insufficient reliability and stability of the power grid in the prior art are solved, and the purposes of improving the energy utilization efficiency of the power pool, optimizing the power grid load, reducing the operation cost and improving the reliability and stability of the power grid are achieved. And the reliability and the stability of the power grid are enhanced.

The invention discloses an intelligent data calling method based on an MCP protocol, and the method comprises the steps: carrying out the intention recognition and key entity extraction in response to a natural language request of a user, and obtaining a plurality of user intentions and at least one key entity; judging based on the confidence coefficient of the key entity, and screening the user intentions according to the confidence coefficient of the user intentions to obtain an execution sequence containing a plurality of subtasks; and determining at least one target data source tool from a plurality of data source tools packaged based on the MCP protocol according to the description of the subtasks one by one so as to perform data query based on the key entity, obtain a query result and generate a final response. According to the method, the system decision reliability can be improved, the tool calling intelligence is enhanced, the process automation is realized, and the two major problems of low task planning quality and inaccurate tool calling are solved.

The invention provides a database calling method based on a large ocean forecast disaster reduction model, and belongs to the technical field of ocean forecast. A double-layer time granularity index structure is constructed, data is divided into a high-frequency calling unit and a low-frequency calling unit according to calling frequency, and a GPU video memory acceleration matrix and a CPU memory storage matrix are constructed respectively; a heterogeneous parallel scheduling algorithm is designed to realize data migration based on multi-dimensional index optimization, time granularity division is dynamically adjusted by applying a spatio-temporal index self-optimization mechanism, a data calling mode is predicted through a multi-head attention-driven marine spatio-temporal feature predictor, and the accuracy and efficiency requirements are dynamically balanced in combination with a gating weighting function. And finally, the data calling efficiency of the ocean forecast disaster reduction large model is remarkably improved, so that the system can efficiently meet the data requirements of high-precision, large-range and multi-aging forecast scenes.

The invention relates to the technical field of power grid defect recognition, in particular to an Agent-based automatic power grid defect recognition system. The system comprises the following steps: acquiring real-time acquisition data, analyzing the real-time acquisition data to obtain a data analysis result, and performing tagging processing on the real-time acquisition data according to the data analysis result to obtain tag data; based on a D-S evidence theory, according to a preset historical defect graph, performing classification processing on the label data; and performing defect identification on the classified label data by utilizing a defect identification Agent, generating a defect report according to an identification result, and feeding back the defect report to an equipment maintenance system. And the classified label data directly triggers a defect identification algorithm of the corresponding Agent, so that a communication link of traditional cross-system data calling is shortened, and the defect upgrading risk caused by processing delay can be reduced. A structured report is automatically generated, a traceable decision basis is provided for an equipment maintenance system, and artificial transcription errors are reduced.

The invention discloses a leasing user credit risk assessment method and system based on a block chain, and relates to the technical field of block chain management. The leasing user credit risk assessment method based on the block chain comprises the following steps: carrying out block chain calling delay assessment; evaluating data write-in delay; and performing off-chain transmission delay evaluation. According to the method, the stability delay evaluation is performed based on the link transmission data volume, meanwhile, according to the stability delay evaluation result, whether to perform block parameter optimization or not is judged, data write-in delay evaluation is performed based on write-in delay data, whether to perform block chain data call optimization or not is judged, and under-chain transmission delay evaluation is performed based on transmission delay data; and meanwhile, whether data byte number optimization is carried out or not is judged, so that the effect of improving the reliability of the lease user credit rating data transmission risk assessment is achieved, and the problem of low reliability of the lease user credit rating data transmission risk assessment caused by corresponding transmission delay in the data chaining process of the block chain in the prior art is solved.

The invention relates to the technical field of V2G networks, and relates to a multi-strategy encrypted transaction data processing method, system and device, and a storage medium. The multi-strategy encrypted transaction data processing method comprises the following steps: acquiring transaction data and a data calling request; the transaction data and the data calling request are input into an encryption strategy selection smart contract, the encryption strategy selection smart contract determines calling information of the transaction data according to the data calling request, an encryption algorithm meeting a screening condition is screened out from a preset encryption algorithm library according to the calling information to serve as a target encryption strategy, and the target encryption strategy is output; and sending the target encryption strategy to the edge computing node, and encrypting the transaction data by the edge computing node according to the target encryption strategy to obtain encrypted transaction data. According to the invention, the transmission efficiency can be improved and the transmission cost can be reduced on the premise of ensuring the transaction data security.

The invention provides a data sharing method and system. The intelligent level and compliance of data management can be improved. The data sharing method comprises the steps of performing classification based on structured data and unstructured data of to-be-shared data to obtain a data label and a data type; based on the data label and the data type, establishing a data asset directory of the to-be-shared data; obtaining a data calling application and a department sending the data calling application; based on the data asset directory, the data calling application, the information of the department and a preset rule, determining a data calling permission of the department; when the data calling permission of the department shows that the department allows calling, performing desensitization processing on the data based on the preset rule to obtain desensitized data; and sending the desensitized data to the department sending the data calling application.

The embodiment of the invention relates to a security verification method and device for an intelligent agent, equipment and a storage medium. The method comprises the steps of generating a first structured representation for describing a dependency relationship in a task running process based on running time sequence data corresponding to at least one task running process of an intelligent agent; the first structured representation comprises a plurality of operation nodes corresponding to the following items: a plurality of processing functions and data called in the task operation process; determining corresponding security description information of a plurality of operation nodes in the first structured representation at least based on a tool security configuration related to an available tool of the agent and a data security configuration related to an accessible data object of the agent; and based on the corresponding security description information of the plurality of operation nodes, executing security verification on the task operation process of the intelligent agent. Therefore, accurate modeling and effective verification of the operation process of the intelligent agent can be realized, so that the coverage rate and accuracy of risk identification are improved.

The invention discloses a power equipment fault incremental learning method and system oriented to a small sample condition, and belongs to the technical field of power equipment fault processing. According to the comprehensive incremental learning platform, a comprehensive data calling space is arranged in the comprehensive incremental learning platform; according to the invention, through linkage of the comprehensive incremental learning platform and the fault incremental dynamic processing module, joint optimization from data acquisition to weight adjustment is realized; the weight risk analysis module is matched with the decision regulation and control module to ensure that an operation program constructed by historical operation data is not excessively forgotten by learning a new fault optimization decision during small sample fault learning; a fault link of traditional scattered data acquisition-isolated model reasoning is reconstructed into a closed-loop system of feature classification-weight optimization-operation data solidification, so that the diagnosis accuracy under a multi-fault concurrent scene is greatly improved, and the problems of data link fault and poor model stability are effectively solved.

The invention provides an employment public service platform, and relates to the technical field of human resource management, and the platform comprises a demand data storage unit which builds a database of demand professional course information of each post corresponding to each enterprise, according to the market change data, controlling to carry out adaptive adjustment on the course information of each requirement specialty in the database; the satisfaction data calling unit is used for inputting personal verification information of employees participating in the employees and calling out satisfaction professional course information matched with the employees; and the promotion data analysis unit is used for acquiring required post information corresponding to employees. According to the employment public service platform provided by the invention, post matching can be efficiently completed according to learning information mastered by employees and learned information required by enterprise posts.

The invention discloses a data governance reinforcement method based on a medical security data warehouse, and the method comprises the following steps: S1, obtaining data converged and accessed from different data sources, and carrying out the data extraction work of formulating a rule; s2, after to-be-processed data access is realized from the data acquired in the step S1, data processing is carried out; s3, after processing the data, storing the data to a data warehouse and carrying out classified calculation; s4, transmitting the data calculated in the step S3 into a data service layer, realizing access control, permission control and transmission encryption control of data calling permissions of other systems, and downloading the data in batches, or packaging the data into a standard API (Application Program Interface) as required; and S5, displaying the decision-making layer data, and realizing various customized data report analysis requirements and personalized data application requirements. The method has the advantages of unifying data aggregation ways, improving data quality, unifying data quality verification rules and medical insurance platform data exits and the like.

The invention relates to the technical field of data interaction, and particularly provides a smart medical interaction method and system based on big data. The method comprises the steps that a physiological knowledge data model is created, a user inputs personal attributes through a terminal for registration, and different permissions are given according to the personal attributes; a user inputs related health data through the terminal and collects physiological data of a patient; related health data are analyzed, and weight values are given to the real-time physiological parameters; carrying out calibration according to the weight value; inputting the real-time physiological parameters into an illness state simulation model for simulation; and inputting a simulation result into the illness state simulation physiological knowledge data model, searching a corresponding doctor for answering according to the simulation result, and storing an answering process. The system comprises a health data acquisition module, a health data calling module and a health data interaction module. According to the invention, the quality and efficiency of medical services are improved, and an accurate, convenient and personalized health management scheme is provided for patients.

The invention discloses a high-safety engineering construction collaborative supervision method and system based on a BIM model, relates to the technical field of collaborative management, is used for solving the problems of non-network problem delay and the like caused by redundant data accumulation in dynamic links, and comprises the steps of monitoring the stability of the dynamic links in real time and setting a dynamic monitoring threshold value; judging the stability of the dynamic link according to the dynamic monitoring threshold value, changing a cache strategy to recover the stability of the dynamic link when the stability is low, collecting transmission behavior data and storage behavior data when the stability is high, and calculating the data transmission priority of the transmission data and the cache data according to the transmission behavior data and the storage behavior data; according to the data transmission priority, a transmission rule is set to transmit data in different modes, feedback data is collected according to the data transmission condition, the feedback data is utilized to calculate a data redundancy proportion and a data calling rate, a deletion rule is set, and the redundant data is deleted according to the deletion rule. And the influence of non-network problem delay on engineering progress is reduced.

The invention discloses a call request processing method and system, a storage medium and electronic equipment. The method is applied to a core network control node, and comprises the following steps: in response to a call request initiated by a calling party, obtaining call data of a call initiated by the calling party, the call data at least comprising a calling party number and a called party number; when the number of the called party is located in a preset first number list, adopting a plurality of call request evaluation models to predict the call request of the calling party to obtain a plurality of abnormal request probabilities; performing weighted fusion calculation on the plurality of abnormal request probabilities to obtain a target abnormal request probability; determining whether the call request is abnormal according to the target abnormal request probability and a preset probability threshold; and under the condition that the call request is abnormal, refusing to establish the call connection between the calling party number and the called party number. Therefore, according to the scheme provided by the embodiment of the invention, the processing precision of the call request is improved.