7576 results about "Data management" patented technology

The invention provides a reimbursement data management system and method based on AI artificial intelligence, and the system comprises a multi-modal data collection and fusion module which is used for providing an access reimbursement application entrance; the auditing and compliance judgment module is used for invoice authenticity identification, reason rationality identification, reimbursement item classification and automatic auditing; the approval process optimization module is used for learning and optimizing a reimbursement approval process and automatically simplifying or increasing approval levels according to reimbursement application features; the analysis and prediction module is used for performing multi-dimensional analysis on the reimbursement data based on a big data processing framework and a data mining algorithm and generating a visual report and result; and the data storage and block chain module is used for constructing a distributed and non-tampering data storage account book by adopting a block chain technology, and executing a reimbursement process automation rule by utilizing a block chain intelligent contract. The efficiency, quality and safety of reimbursement data management are comprehensively improved, and enterprise financial management is promoted to develop towards the intelligent and refined direction.

The invention discloses a government affair data sharing system based on a data security law risk control mode, and relates to the technical field of data management. According to the method, full-process closed-loop management from data classification and grading, differential desensitization, law and regulation compliance review, access authority precise control to behavior trajectory real-time analysis and risk trend prediction is realized, and the risk trend prediction is realized by introducing key technologies such as a context sensitive desensitization algorithm, legal knowledge graph reasoning, behavior portraits, semantic trajectory similarity scoring and risk rise rate monitoring. The method effectively improves the recognition and response capability of the hidden data re-recognition risk, and achieves the safe, controllable, compliant and ordered intelligent risk control management of government affair data in the sharing process.

The invention relates to the technical field of data management, in particular to an industrial control system remote monitoring data synchronization method, which comprises the following steps of: 1, generating a dynamic synchronization time window based on an equipment state sudden change frequency and a network fluctuation degree; 2, dividing transmission priorities according to the influence degree of data on equipment security control; 3, quality characteristics of available transmission paths are evaluated, data of different priorities are transmitted in a fragmented mode according to a differentiation strategy, and data streams are recombined at a receiving end based on time sequence identification; 4, after network disconnection is recovered, synchronous consistency guarantee is achieved through data segment cascade hash verification and control instruction logic conflict detection; and 5, optimizing a time window generation algorithm and a path evaluation rule according to the historical synchronization effect data. Through accurate control, priority division, network adaptability enhancement and consistency guarantee of data transmission, an efficient and safe industrial control system remote monitoring data synchronization scheme with adaptive capability is provided.

The present invention relates to a method for constructing a digital twin system for an additive manufacturing process with lifecycle data management. The digital twin system for an additive manufacturing process constructed by the method includes a data acquisition and supervisory control system, a data management and storage system, a manufacturing executing system, a configuration model, a simulation system, and a multi-physics simulation system. The present invention can fully and accurately characterize the molding quality of parts, thereby saving a lot of time required for offline data processing, and achieving real-time acquisition and updating of data.

The invention discloses a teaching data management method and system based on artificial intelligence, and the method comprises the steps: obtaining a standardized time series data stream according to a heterogeneous data stream generated by a multi-source teaching platform in real time; based on the standardized time sequence data stream, performing classified encryption on the teaching data through a dynamic hierarchical storage strategy based on attribute-based encryption to obtain a security hierarchical storage topological structure; according to a user query request and a teaching scene label, extracting a target data set from the security hierarchical storage topological structure to obtain an enhanced multi-modal teaching data set; based on the enhanced multi-modal teaching data set, generating an interpretable teaching mode graph through a dynamic sub-graph evolution algorithm; and according to the teaching mode map and the real-time teaching feedback data, generating a personalized teaching recommendation strategy through a course-learner dual-channel adaptive recommendation model. According to the embodiment of the invention, the utilization efficiency of teaching resources can be improved, and personalized and intelligent teaching recommendation and decision can be realized.

The present invention provides a flight attitude control method based on inertial navigation technology, which relates to the field of aircraft control technology and includes an attitude control system. The attitude control system includes a quantum inertial navigation fusion module, a distributed multi-source collaborative inertial navigation module, a real-time error compensation module based on deep learning, an energy collection and self-powered inertial system module, a distributed attitude data management module based on blockchain, a multimodal fusion and virtual twin collaborative control module, and a terahertz communication and inertial navigation fusion anti-interference module. The present invention uses a quantum annealing algorithm combined with a compressed sensing algorithm to optimize quantum sensor data, and then combines the D-S evidence theory and the particle swarm optimization algorithm in the distributed multi-source collaborative inertial navigation module to fuse multi-source data, which can deeply mine the deep connection and complementary information between different sensor data, break the simple data level superposition limitation, and greatly improve the accuracy of the attitude information after fusion.

The invention relates to the technical field of information management, and comprises a distribution automation operation and maintenance work log intelligent recording platform based on a CS architecture, and the platform comprises a log field analysis module, a task chain construction module, a task logic verification module, and a log storage tracing module. According to the method, missing and abnormal fields are effectively marked and corrected through meticulous analysis and comparison of uploaded log records, the accuracy and integrity of data are improved, task scheduling is optimized and the operation and maintenance management efficiency is improved through association of device numbers and task types and adjustment of execution time in sorting and grouping of task sequences, and the task scheduling efficiency is improved. Task chains are recombined to solve conflicts and adjust priorities, smooth execution of operation and maintenance tasks is guaranteed, delay is reduced, logic verification enhances task reliability through rule verification and error marking, unassociated tasks are deduced, analyzed and corrected, the exception processing capacity is enhanced, the data tracing and storage efficiency is improved, and the tracing capacity of data management is enhanced.

Systems, computer program products, and methods are described herein for building material data management. With reference to an example method, the method receives a first dataset formed of first data entries associated with a building material data source and generates a building material data entity based on the building material data source. The method includes outputting a representation of the building material data entity. The first dataset may be formed of data records (e.g., construction documents, user inputs, sensor data, or machines data), and the representation may be a visual representation may include notifications, visual presentations of the building material entity, etc.

The invention provides a data management method, device and equipment and a readable storage medium, and the method comprises the steps: obtaining key value cache data generated by a first type of computing power unit in a pre-filling stage, transmitting the key value cache data to a memory pool, and caching the key value cache data in the memory pool; and in response to a data acquisition demand of the second type of computing power unit in a decoding stage, transmitting the specified key value cache data cached in the memory pool to the second type of computing power unit according to the data acquisition demand. According to the technical scheme of the invention, the memory pool is arranged and the aggregated transmission channel is utilized, so that the transmission efficiency of the key value cache data between the computing power devices is effectively improved, the data transmission delay is reduced, and the network transmission protocol overhead is reduced, thereby improving the data interaction efficiency of the computing power devices in a pre-filling stage and a decoding stage, and improving the user experience. The utilization of computing power resources is optimized, and the throughput and performance of large model reasoning are improved.

The present application relates to the field of environmental monitoring and governance, and discloses a supervision system and method for agricultural non-point source pollution scenarios. The system includes a perception module, a data management module, an intelligent analysis module, and an application service module. The perception module collects pollutant concentration, hydrological characteristics, and abnormal behavior data through water quality sensors, high-position video monitoring equipment, and drones; the data management module dynamically integrates, stores, and standardizes the data collected by the perception module; the intelligent analysis module predicts the diffusion path of pollutants in the water body based on the pollution diffusion model, and inverts the spatial location and intensity of the pollution source by combining the video monitoring abnormal behavior records with the diffusion model; the application service module displays the analysis results, triggers warnings, and supports remote governance operations through an intelligent early warning system, a GIS visualization platform, and mobile devices. The present invention can accurately monitor agricultural non-point source pollution, improve the efficiency of pollution source positioning and supervision, and provide technical support for the governance of agricultural non-point source pollution.

The invention belongs to the technical field of medical data processing, and discloses a medical data multi-source fusion verification and correction method and system, and the method comprises the steps: obtaining multi-source data; constructing a dynamic baseline model of the emergency department, the ICU and the common ward, responding to and verifying the abnormal condition of the patient data, and performing early warning; establishing a term library, carrying out multi-source fusion on the patient data obtained from multiple sources, and carrying out data correction; and generating a multi-source data quality evaluation table of different departments based on the whole-process data, and feeding back and updating the term library and fusing the correction weight based on the quality evaluation table. Through a real-time monitoring and intelligent early warning mechanism, quality problems in the data can be found and corrected in time, human errors are reduced, and the data management cost is greatly reduced. Through multi-source data fusion and consistency verification, the system can ensure seamless connection of data from different data sources, and cross-system and cross-platform data consistency and cooperative work are realized, so that the accuracy of medical decision and the reliability of data are improved.

The invention relates to the technical field of data processing, in particular to a ceramic supply chain quality traceability data management system based on a block chain, which comprises a data acquisition and processing module, a dynamic identifier generation module, an identifier embedding control module, a cross-chain data synchronization module, a multi-modal verification module and a redundancy recovery module. The data acquisition and processing module integrates firing temperature, forming pressure parameters and microscopic image data through Internet of Things equipment and edge computing nodes to generate a structured data set, the system integrated resource scheduling module optimizes node computing resource allocation, and anti-quantum encryption and IPFS distributed storage guarantee data security. And the terminal equipment integration module simplifies the multi-modal data acquisition process, and finally collaborative optimization of the ceramic quality tracing reliability, the operation efficiency and the artistic integrity is realized.

The invention relates to the technical field of cell culture data processing, in particular to a cell culture information data management method and system. The method comprises the following steps: performing culture environment multi-parameter high-frequency real-time monitoring on a cell culture environment box to obtain multi-dimensional cell culture environment time sequence parameters; performing culture environment key disturbance parameter screening on the multi-dimensional cell culture environment time sequence parameters to generate environment key disturbance parameters; acquiring historical cell culture batch data; based on historical cell culture batch data, carrying out multi-parameter coordinated regulation and control on the environment key disturbance parameters to obtain a cell culture environment regulation and control strategy; regulating and controlling the cell culture process according to the cell culture environment regulation and control strategy, and performing cell culture knowledge graph construction on historical cell culture batch data to obtain a cell culture management knowledge graph. According to the invention, intelligent management of cell culture data is realized through construction of the cell culture knowledge graph.

The invention relates to the technical field of data analysis, provides an equipment state data management method and system applied to an automatic radix astragali seu hedysari refined production line, and is used for realizing equipment health precise prediction and active maintenance through whole-process data monitoring management. The method comprises the steps that a production line equipment state data set is acquired, a production line equipment state feature set is extracted from the production line equipment state data set, and the production line equipment state feature set comprises multi-dimensional time sequence features reflecting the equipment operation trend and topological features of the incidence relation between the equipment; training an astragalus membranaceus essence production line state prediction model based on the production line equipment state feature set, wherein the astragalus membranaceus essence production line state prediction model is used for predicting the equipment abnormal probability and the performance degradation trend in a selected time period according to the current equipment state feature; and generating an equipment management strategy set according to an output result of the radix astragali seu hedysari refined production line state prediction model, wherein the equipment management strategy set comprises production parameter adjustment instructions and maintenance node planning schemes for different equipment maintenance priorities.

The invention discloses a mobile collaboration platform data management method, and relates to the technical field of data processing, and the management method comprises the following specific steps: S100, data sensitive grading: calculating sensitivity scores of various types of data in a mobile collaboration platform by using a formula. According to the method, the sensitivity scores of various data are calculated through a formula, and the data are divided according to the sensitivity levels, so that different levels of protection measures are taken for the data with different sensitivity degrees, and meanwhile, through a built-in sensor and a built-in behavior monitoring module, the sensitivity of the data is improved. The operation behavior information, the equipment information and the business process information of the user are collected in real time, the current business scene is intelligently judged, a basis is provided for subsequent privacy protection strategy making, the data processing efficiency is improved, the data security is greatly enhanced, and data leakage and abuse are effectively prevented.

The invention provides a prospecting prediction system based on multi-scale big data fusion, and the system comprises a geological big data management module and a big data mining analysis module which are respectively used for carrying out the management and mining analysis of geological, geophysical, geochemical, remote sensing and mineral data; the multi-element extraction module is used for carrying out geological element extraction on the mining analysis result output by the big data mining analysis module; the multi-scale grid calculation module is used for carrying out subdivision and assignment on the geological elements through a multi-scale multi-element grid technology; the intelligent prospecting prediction module is used for compiling a result map; the intelligent prospecting evaluation module is used for compiling an optimal decision diagram; the auxiliary decision-making module generates a prospecting result report; and the prospecting dispatching command module is used for synchronously updating the data in the prospecting dispatching command module. By integrating the prospecting prediction basic data set, the knowledge base, the model base and the algorithm base, flexible scheduling and convenient use of various data, knowledge, models and algorithm tools are achieved.

The invention discloses an electromechanical engineering construction information operation and maintenance management method and system based on the Internet, and particularly relates to the technical field of data management. Constructing an initial BIM model based on the design drawing, and generating three-dimensional model data containing equipment geometric information and space coordinates; a three-dimensional laser scanning device or a high-precision positioning sensor is used for obtaining the geometrical morphology and actual coordinates of a real object on site; the collected point cloud data is compared with the initial BIM model through a spatial data matching algorithm, deviation is recognized, the BIM model is automatically updated, and model precision dynamic correction is achieved; binding the updated equipment information and an equipment entity with a two-dimensional code, and synchronously binding an actual position coordinate through an indoor positioning label; uploading the corrected model and equipment information to a cloud operation and maintenance platform to realize information centralized management and multi-terminal sharing; the method improves electromechanical engineering operation and maintenance efficiency and information precision, and has good application value.

The invention relates to the technical field of e-commerce data processing, in particular to an e-commerce sales platform background data management method and system. The method comprises the following steps: S1, collecting a commodity dynamic data stream, a user behavior event stream and a promotion strategy stream in real time, and generating a standardized data stream through time sequence alignment; s2, constructing a dynamic coupling data cube; s3, executing a real-time decision: in response to the payment request, selecting an inventory distribution or replacement commodity pushing strategy based on a commodity-user coupling matrix value; in response to the resource overload state, triggering a resource scheduling strategy; and S4, dynamically adjusting calculation parameters of the coupling matrix according to decision execution feedback. By solving the problems of real-time standardization processing of multi-source heterogeneous data and real-time coupling of dynamic inventory and user behaviors, the data processing capacity, inventory distribution efficiency and recommendation accuracy of the platform are remarkably improved.

The invention discloses a booster station monitoring operation and maintenance system, and relates to the technical field of data management. A plurality of heterogeneous intelligent sensors are deployed in a booster station to monitor the operation state of equipment in real time, an electromagnetic field sensor is utilized to sense the electromagnetic interference intensity, and when abnormal high-frequency pulses are detected, a data anomaly detection mode is triggered to detect the abnormal high-frequency pulses; calculating an error compensation value according to the abnormal degree, correcting abnormal data, ensuring the accuracy of the data, performing equipment state evaluation according to the recovered data, and if potential safety hazards are found, sending intelligent early warning to operation and maintenance personnel and providing suggestions for adjusting monitoring strategies or optimizing shielding measures; according to the invention, the anti-interference capability and accuracy of booster station monitoring data are effectively improved, the risk of operation and maintenance misjudgment caused by electromagnetic interference is reduced, the reliability of intelligent monitoring in an ultrahigh-voltage power transmission scene is enhanced, and a powerful guarantee is provided for safe and stable operation of a power system.

The embodiment of the invention provides a project research and development data key information processing method and device. A research and development content recognition system and a self-adaptive research and development knowledge graph are constructed. Unified processing and time sequence alignment of text, voice and image contents are realized through multi-modal information decomposition and fusion. Semantic completion and error correction are carried out based on research and development of a semantic analysis model, a knowledge graph structure is dynamically constructed and optimized, and a structured document with a traceability relation is generated. The system adopts a deep neural network model to extract research and development key information, constructs a multi-level document framework, and realizes intelligent conversion from research and development data to a project application document. According to the method, the defects of the traditional technology in the aspects of multi-modal information processing and knowledge structure optimization are effectively overcome, and the research and development data management and project declaration efficiency is remarkably improved.

A distributed generative artificial intelligence (AI) reasoning and action platform that utilizes a cloud-based computing architecture for neuro-symbolic reasoning. The platform comprises systems for distributed computation, curation, marketplace integration, and context management. A distributed computational graph (DCG) orchestrates complex workflows for building and deploying generative AI models, incorporating expert judgment and external data sources. A context computing system aggregates contextual data, while a curation system provides curated responses from trained models. Marketplaces offer data, algorithms, and expert judgment for purchase or integration. The platform enables enterprises to construct user-defined workflows and incorporate trained models into their business processes, leveraging enterprise-specific knowledge. The platform facilitates flexible and scalable integration of machine learning models into software applications, supported by a dynamic and adaptive DCG architecture.

The invention discloses a public institution kitchen energy data management system based on cloud data, particularly relates to the field of energy management, and comprises a multi-source heterogeneous data acquisition module, an edge intelligent preprocessing module, a cloud data lake storage module, a multi-dimensional analysis engine module, an intelligent decision center module and a visual interaction module. According to the method, space-time alignment of multi-source data is realized through protocol adaptive conversion and millisecond time synchronization technologies, a high-consistency analysis basis is constructed, real-time index calculation and adaptive model optimization are implemented by edge calculation and cloud dynamic modeling collaborative architecture, hidden energy loss is accurately identified, and the real-time performance of the system is improved. The intelligent decision center is combined with digital twinborn verification to generate a control strategy, a minute-level closed-loop response mechanism is formed, automatic adjustment and optimization of equipment parameters and intelligent distribution of maintenance work orders are achieved, manual intervention delay is eliminated, timeliness and execution accuracy of an energy strategy are guaranteed, and multi-system collaborative management efficiency is remarkably improved.

The invention discloses a data management method based on a distributed storage system, relates to the technical field of data management, and is used for solving the problem of storage management behavior strategy mismatch. On the basis of dynamic perception of data access behaviors in a distributed storage system, a behavior feature vector fusing an access mutation rate, periodicity and an access span is constructed, behavior pattern recognition and strategy structure generation are completed, optimal deployment and hierarchical storage of copies are achieved through node resource state perception and construction of a cost function, and the strategy structure generation efficiency is improved. And after compression and consistency configuration are executed and the strategy falls to the ground, the compressibility and the offset trend of the behavior path are analyzed, scheduling management information is extracted, and a stable execution or strategy adjustment signal is generated, so that the problem of strategy execution mismatching caused by behavior perception deficiency in the distributed storage system is reduced, and the strategy execution efficiency is improved. The strategy closed-loop control and the resource scheduling optimization under behavior driving are realized, so that the data management efficiency and the strategy adaptation capability of the distributed storage system are improved.

The invention discloses an integrated collaborative management method for construction site risk operation data, and belongs to the technical field of data management. The method comprises the following steps: constructing and calibrating a space-time risk reference database; deducing a potential risk conduction link set, and generating an associated intervention knowledge base; during operation, through multi-sensor cooperative verification, an abnormal signal is confirmed as a risk event; matching the risk event with a conduction link to calculate a risk upgrade level and dynamically adjust an early warning threshold; and when the early warning is triggered, generating and issuing a dynamic collaborative response instruction, and feeding back a processing result to correct the reference database to form a management closed loop. According to the method, the technical means of constructing the space-time risk reference, deducing the conduction link, cooperatively verifying the risk and dynamically regulating and controlling the threshold are adopted, so that the predictability of project risk management and control, the efficiency of resource cooperative scheduling and the scientificity of overall management decision are improved.

Methods and systems for managing a data processing system based on location data are disclosed. A management controller of the data processing system may provide the location data via an out-of-band communication channel to a geolocation management server tasked with mapping a location of the data processing system over time. The data processing system may identify an occurrence of an event based on the location data (e.g., a change in location of the data processing system), prompting the data processing system to perform an action set to update operation of the data processing system (e.g., to conform to location-based policies). Based on its updated operation, the data processing system may provide computer-implemented services that are more likely to be in compliance with local policies.

The invention discloses a geological structure fracture automatic identification and detection system based on deep learning, and relates to the technical field of geological structure fracture automatic identification and detection, and the geological structure fracture automatic identification and detection system comprises a fracture image analysis module, a distortion intelligent evaluation module, a form adaptive correction module, a correction efficiency evaluation module and an identification data management module. The distortion intelligent evaluation module is used for acquiring imaging parameter information of each region in the crack image in real time, judging the form distortion degree of each region in the crack image under a perspective distortion condition, and dividing each region in the crack image into a low distortion region, a medium distortion region and a high distortion region according to a judgment result; and the form self-adaptive correction module is used for constructing a fracture form correction mechanism according to the division result of each region in the fracture image. According to the invention, the problem of fracture shape distortion caused by the change of a shooting view angle is solved, accurate identification and automatic correction of the fracture are realized, and the detection precision and stability are improved.

The invention relates to the technical field of data management, in particular to an electrical equipment fault prediction system and method based on data fusion, and the system intelligently adjusts a data collection strategy by accurately capturing electromagnetic signal characteristic parameters of an electrical equipment operation environment and scientifically evaluating an electromagnetic interference index. The accuracy and efficiency of data acquisition are effectively improved, meanwhile, by monitoring the operation state parameters of the electrical equipment, the characteristics of the electrical equipment can be deeply extracted, the data acquisition compliance index is calculated, a powerful basis is provided for data preprocessing, finally, the multi-dimensional operation state parameters of the electrical equipment are highly fused, operation degradation factors can be accurately identified, and the accuracy and efficiency of data acquisition are improved. According to the invention, the method achieves the precise prediction of the fault level of the electrical equipment, gives out an early warning in time, remarkably improves the accuracy and timeliness of fault prediction, effectively reduces the operation and maintenance cost, enhances the stability and safety of a power system, and provides a powerful technical guarantee for the intelligent management and maintenance of the electrical equipment.

The invention relates to the technical field of electric digital data processing, in particular to a traditional Chinese medicine data management system and method for data retrieval. The method comprises the following steps: acquiring morphology data of a traditional Chinese medicinal material sample; performing grade evaluation based on the traditional Chinese medicinal material morphology data to generate traditional Chinese medicinal material grade label data; acquiring a to-be-detected traditional Chinese medicinal material image; preprocessing the to-be-detected traditional Chinese medicinal material image, and performing entity recognition and relation extraction to obtain traditional Chinese medicinal material semantic annotation data; and fusing the traditional Chinese medicinal material grade label data and the traditional Chinese medicinal material semantic annotation data to obtain traditional Chinese medicinal material semantic annotation enhanced data. According to the method, the information of the traditional Chinese medicinal materials is expressed through structured processing and semantic enhancement, the knowledge graph containing dominant and implicit semantic relationships is constructed, and the retrieval depth, flexibility and intelligent application of knowledge of the traditional Chinese medicinal materials are improved.

The invention discloses a time sequence data management method of an edge computing gateway, which relates to the technical field of edge computing and industrial Internet of Things, and comprises the following steps of: respectively recording a communication bandwidth occupancy rate, a buffer area residual rate and a scheduling thread occupancy rate of the edge computing gateway in a preset fixed time period; and constructing a resource use original data matrix covering all time points in the fixed time period. According to the method, by periodically monitoring the resource use state and fusing the high-priority task scheduling performance, the scheduling resource abnormal occupancy index is dynamically generated, and intelligent sensing and scheduling optimization of the edge computing gateway on the resource pressure are achieved. When the abnormal index is increased, the system automatically triggers buffer area redistribution and low-optimal task data compression, data writing and scheduling real-time performance of key tasks are guaranteed preferentially, the problems of task starvation and data loss are effectively avoided, and the stability and the response capability of the system in a high-pressure environment are improved.

The invention relates to the technical field of cloud computing and distributed storage, and discloses a distributed metadata management method and storage system based on cloud computing, and the method comprises the following steps: S1, collecting the access frequency of a plurality of metadata objects in a set time period; s2, performing weighting processing on the access frequency, and constructing access heat distribution under multiple time scales; s3, obtaining the available cache capacity of a plurality of cache nodes, and constructing cache resource weight distribution; s4, assessing the access cost and migration cost between each metadata object and each cache node; and S5, generating a scheduling strategy between the metadata object and the cache node based on a preset optimization target, wherein the optimization target is access cost minimization. According to the method, a heat, resource and cost joint modeling mechanism is constructed, and optimal scheduling and feedback adaptive control are combined, so that accurate decision, dynamic adjustment and migration cost controllability of copy deployment are realized, and the performance and stability of distributed metadata management are effectively improved.