211 results about "Data scatter" patented technology

The invention discloses an intelligent environment monitoring and regulation method for a marine ranch, and belongs to the field of environment monitoring, and the method comprises the steps: collecting water body parameters, employing a data fusion algorithm to generate a comprehensive environment state index, and solving the business problems of data dispersion, response lag and inaccurate adjustment in water body environment monitoring and regulation. A time sequence analysis model and an optimization algorithm are combined, potential anomalies are analyzed, a risk change trend is predicted, environment adjustment requirements are dynamically calculated, a precise regulation and control instruction set is generated and transmitted to equipment to be executed, and meanwhile, through deviation comparison between real-time feedback data and a preset threshold value, comprehensive indexes and regulation and control parameters are iteratively updated, so that environment stability is ensured. Through multi-level data processing and a self-adaptive adjustment mechanism, the timeliness and accuracy of water body environment regulation and control are remarkably improved, closed-loop management from monitoring to optimization is achieved, and efficient support is provided for intelligent decision making in a complex environment.

The invention discloses an offshore wind power fault monitoring method based on a knowledge graph and digital twinning, and aims to solve the problems that multi-source data acquisition is dispersed, the transmission delay is high, and real-time convergence and integration are difficult to realize in the operation state monitoring of offshore wind power equipment. According to the invention, the following modules are provided: a multi-source data acquisition layer is used for solving the problems of dispersed data acquisition and transmission lag and ensuring the real-time performance; the knowledge graph construction module is used for solving the problems of extraction, fusion and storage of equipment entity relationships; the digital twin modeling module realizes visual presentation and accurate simulation of the state of physical equipment; the fault monitoring reasoning module solves the problems of anomaly detection and root cause positioning; the intelligent early warning decision module determines an early warning level and efficiently matches a solution; the visual interaction module solves the problems of scattered information display and poor linkage, supports third-party docking, realizes accurate early warning and root cause positioning, improves the decision-making efficiency, adapts to severe environments, supports large-scale wind power plant monitoring, and reduces the operation and maintenance cost.

The invention discloses an AI-based digital project performance evaluation data processing method and system, and relates to the technical field of artificial intelligence and digital project management, and the method comprises a multi-source data collection module which is used for obtaining data; the entity alignment module is used for establishing an association relationship among cross-system data entities; the dynamic index generation module is used for dynamically adjusting the evaluation index weight by utilizing a reinforcement learning framework; the efficiency prediction module is used for modeling a task dependency relationship according to the time sequence diagram convolutional network and outputting a delay risk probability; and the visual interface is used for displaying the data. According to the method, cross-system entity alignment, dynamic index weight adjustment, task delay risk prediction and root cause analysis are realized through AI technologies such as BERT semantic matching and a graph neural network, visual data display and interaction functions are provided by virtue of a visual interface, the problems of data dispersion, index static state, risk lag and the like in traditional project evaluation are solved, and the project evaluation efficiency is improved. And the decision support capability of project management is improved.

The invention provides a method, a device, equipment and a medium for generating an engineering project management digital model, and the method comprises the steps: collecting original data related to engineering project features, carrying out the preprocessing, forming a standardized project data set, constructing a space-time reference frame based on the data set, fusing a multi-dimensional feature tensor of multiple engineering features, and carrying out the construction of a space-time reference frame. The method comprises the steps of generating a project progress node and an integrated feature tensor, fusing the project progress node and the integrated feature tensor to generate a multi-source association graph containing entity relationships and feature semantics, generating a verified engineering project management digital model according to the project progress node, the integrated feature tensor and the association graph, and dynamically updating and optimizing the model in response to change data in project execution. According to the method, the problems of data dispersion, lack of association and static stiffness of the model in a traditional method are solved, automatic construction and dynamic evolution from multi-source heterogeneous data to an intelligent decision-making model are realized, and the accuracy, real-time performance and intelligent level of project management are remarkably improved.

The invention relates to the technical field of communication network operation and maintenance, in particular to a 5GC core network-oriented network health degree assessment method and system, and the method comprises the following steps: multi-source data collection and preprocessing, multi-dimensional health assessment model construction, and dynamic verification and report generation. The method has the beneficial effects that the problems of data dispersion and single evaluation dimension in a traditional method are solved, intelligent and multi-dimensional dynamic evaluation of the network health degree is realized, and the operation and maintenance efficiency and the risk pre-judgment capability of the core network are remarkably improved.

The invention discloses an intelligent carbon anode quality detection system, particularly relates to the field of electrolytic aluminum, and comprises a data acquisition module, a data preprocessing module, a data analysis module and a comprehensive judgment module. According to the method, a full-process data acquisition system covering raw materials, forming, roasting and appearance is constructed, accurate acquisition of multi-source data is realized by using equipment such as an X-ray fluorescence spectrometer and a hydraulic sensor, the problem of dispersion of traditional detection data is solved, and the detection accuracy of the multi-source data is improved through multi-stage pretreatment methods such as outlier elimination, sliding window filtering, temperature compensation and wavelet noise reduction. Dimension difference and sensor noise interference are effectively eliminated, and data reliability is improved. A multi-level evaluation model composed of a raw material comprehensive index, forming energy density, roasting maturity and appearance integrity is innovatively established, and intelligent comprehensive evaluation and accurate grading management and control of the carbon anode quality are achieved in combination with a dynamic weighting comprehensive quality index formula and a four-level grading mechanism.

The invention relates to the technical field of power two-ticket management, and discloses a two-ticket full life cycle optimization and management method and system based on workflow, and the method comprises the steps: obtaining the basic data of personnel qualification, equipment state and flow rule, and constructing a typical work ticket library and a typical operation ticket library; calling a work ticket template or an operation ticket template to perform information supplement, performing double verification, and then completing graded auditing and electronic signature according to preset nodes to generate an effective work ticket and an executable operation ticket; and monitoring the execution process of the effective work ticket and the executable operation ticket, and archiving execution data to a historical database to realize multi-dimensional two-ticket full-process data query, generation of an analysis report, update of basic data, a work ticket typical ticket library and an operation ticket typical ticket library. The standardized typical ticket library is constructed by integrating basic data, monitoring and archiving traceability of two tickets are achieved, standardized intelligent management of the two tickets is achieved, and the problems that existing data are scattered, compliance is poor, traceability is difficult, and no improved closed loop exists are solved.

The invention relates to the technical field of VR, AI and psychological therapy crossing, and discloses a psychological universe intelligent psychological tutoring integrated platform which comprises a holographic sensing module used for acquiring multi-modal data of a user in real time; the intelligent psychological engine module is used for receiving and analyzing the multi-modal data and generating a multi-dimensional psychological state vector; and the dynamic meta universe scene and personalized intervention module is used for adjusting virtual scene parameters and behaviors of the intelligent non-player character in real time according to the multi-dimensional psychological state vector. According to the method, multi-modal data such as behaviors, eye movement and physiology are acquired and deployed at edge computing nodes, and attention weight calculation is adopted to carry out weighted fusion and comprehensive analysis on the multi-modal data, so that a unified multi-dimensional psychological state vector is generated; therefore, the technical defects that in the prior art, data are dispersed, and effective integrated analysis cannot be carried out are overcome, and objective, quantitative and comprehensive evaluation on the psychological state of the user is achieved.

The invention discloses a human and house data comprehensive treatment method, system and equipment based on a multi-level address model, and a medium, belongs to the technical field of data treatment, and aims to solve the technical problem of how to effectively integrate human and house data sources of multiple parties and improve the accuracy, consistency and availability of human and house data. The defects that in the prior art, people and house data are scattered, address description is not standard, the incidence relation is inaccurate, data quality is uneven and a unified identification system is lacked are overcome. According to the technical scheme, the method comprises the steps that a five-level core data table comprising a community table, a building table, a house table, a people and house relation table and a personnel information table is constructed; the method comprises the following steps: accessing original human and house data from a plurality of data sources, performing intelligent analysis and standardization processing on address information, and obtaining data after standardization processing; establishing a house unique identification system and a human-house multi-dimensional relation model based on the standardized data; evaluating and repairing the data quality; and standardized human and house data service is provided for the outside through the data service interface.

The invention discloses an optical fiber network intelligent regular checking and fault closed-loop processing system, method and device, and belongs to the technical field of optical fiber communication network intelligent operation and maintenance. The method comprises the following steps: collecting and fusing multi-source heterogeneous data such as resource management, fault network management, distributed sensing and geographic information; a multi-modal model based on a convolutional neural network and a graph neural network is utilized to analyze fusion data, meter-scale accurate positioning of faults is achieved, and a regular inspection plan is dynamically optimized by adopting a long and short-term memory network model; and based on an analysis decision result, a fault list, a mode list and a maintenance list are automatically created, circulated and associated, and a whole-process closed loop from diagnosis list sending to repair verification is realized. According to the scheme, the problems of data dispersion, single analysis dimension and lack of closed loop in the process in the prior art are solved, and the accuracy, efficiency and automation level of optical fiber network operation and maintenance are remarkably improved.

The invention discloses a power generation equipment intelligent diagnosis method and system fused with a knowledge graph, and relates to the technical field of equipment diagnosis. The method comprises the following steps: collecting multi-source operation data and historical fault records of power generation equipment, and constructing a power generation equipment fault knowledge graph; real-time operation data of the power generation equipment are monitored in real time, feature extraction and semantic association are carried out on the real-time operation data of the power generation equipment based on the power generation equipment fault knowledge graph, and a power generation equipment operation state vector is generated; reasoning and analyzing the operation state vector of the power generation equipment, and mining a potential fault mode and an equipment fault causal chain of the equipment; and performing fault positioning diagnosis based on the equipment potential fault mode and the equipment fault causal chain, and determining a power generation equipment diagnosis result. The technical problem that in the prior art, operation data of power generation equipment are scattered, and fault mechanisms are difficult to express explicitly, so that the diagnosis accuracy is low is solved, and the technical effect that potential fault modes are intelligently mined through the graph neural network, so that the fault diagnosis accuracy is improved is achieved.

The invention relates to the technical field of data measurement and calculation, in particular to an ecological system carbon source sink rapid calculation method for a mining area scale. The method comprises the following steps: acquiring mining area remote sensing image data, ground actual measurement data and mining area mining activity records, and constructing a multi-source mining area basic data set; performing spatial registration and time alignment on the multi-source mining area basic data set to obtain an aligned multi-source fusion data set; based on the aligned multi-source fusion data set, mine occupied map spots are identified, land utilization type information of the map spots is extracted, a land utilization type data set is formed, and a carbon library classification data set is generated in combination with mining area carbon library type definition; therefore, by integrating multi-source data, optimizing space and time alignment and refining the carbon reserve calculation process, the problems of data dispersion, inaccurate calculation and the like in a traditional method are solved, and the scientificity and reliability of carbon source sink measurement and calculation of the mining area ecosystem are improved.

The invention relates to the technical field of radio frequency chip performance testing, and particularly provides a real-time visualization method and visualization system for radio frequency chip performance testing, traditional single-thread sequence control is replaced by a multi-thread asynchronous acquisition architecture, and the testing efficiency is remarkably improved; through adding a timestamp label mechanism to each piece of test data, the cross-device data synchronization precision reaches a microsecond level, and the problem of asynchronous triggering of a radio frequency signal and direct current bias is solved. The radio frequency index data table constructed by automatic association realizes intelligent aggregation analysis of multiple parameters under multiple combinations, and avoids manual matching errors caused by data dispersed storage in a traditional scheme. Based on an automatic threshold setting and real-time judgment function of a test protocol, intelligent switching of judgment standards under a multi-protocol standard is supported, errors caused by manual configuration are reduced, and modification during protocol updating is avoided. And real-time visual rendering enables a user to dynamically observe a multi-parameter association change trend, so that the problem positioning efficiency is improved.

The invention discloses a new media operation optimization method and system based on a data closed loop. The system comprises a data acquisition module, a three-dimensional label system module, an intelligent analysis module and a closed loop optimization module. The data acquisition module synchronizes core operation data through an API, and captures unstructured comment data through an RPA; the three-dimensional tag system module is used for carrying out tagging processing on platform characteristics, content forms and user behaviors on the data; the intelligent analysis module generates and outputs optimization suggestions through content diagnosis, flow prediction and strategy; and the closed-loop optimization module feeds back an analysis result to an external content generation system, and new content data is transmitted back to form a closed loop. According to the system, the problems of operation data dispersion, insufficient analysis and optimization lag are solved, automatic data acquisition, structured analysis and dynamic optimization are realized, and the operation efficiency and the traffic conversion effect are improved.

The invention belongs to the technical field of traditional Chinese medicine information processing, and provides a traditional Chinese medicine disease medical case database construction and management system, which comprises a data acquisition module for acquiring original traditional Chinese medicine medical case data from a plurality of heterogeneous data sources; the data processing module is used for sequentially carrying out preprocessing, standardization and deep structured processing on the original data; the knowledge graph engine module is responsible for constructing, storing and managing a traditional Chinese medicine case knowledge graph; the database storage module adopts a distributed storage architecture to store standardized medical case data and a knowledge graph; and the intelligent query and analysis module receives a request input by a user in a natural language or a structured query condition, executes multi-hop association retrieval and bidirectional path reasoning based on the traditional Chinese medicine medical case knowledge graph, and outputs medical case data meeting the condition and an association knowledge reasoning result. According to the system and the method, systematized integration and deep mining are performed on traditional Chinese medicine case data, and through cooperative work of multiple modules, the limitations of data dispersion, different formats and low retrieval efficiency in traditional medical case management are broken through.

The invention relates to an aircraft component intelligent assembly data management system based on compliance verification, and belongs to the technical field of aerospace manufacturing. In order to solve the problems of data dispersion, low verification efficiency and difficulty in quality tracing in the aircraft component assembly process, the system comprises a standard process library construction unit used for constructing an aircraft component assembly standard process library which is clear in classification and contains detailed specifications; the assembly information acquisition unit is used for collecting assembly data in multiple channels and processing the assembly data into a structured data set; the data management system unit is used for integrating multi-source data and analyzing historical data and verification results to form a trend table so as to realize overall management; and the qualification checking unit is used for checking real-time data in multiple dimensions, generating a report and performing synchronous early warning. According to the system, intelligent management of the aircraft component assembly process is realized, the data processing efficiency and accuracy are improved, and the assembly quality and the safety and reliability of an aircraft are guaranteed.

The invention relates to the technical field of data storage processing, and discloses an insurance policy system data migration method, device and equipment based on an MQ message queue, and a medium, and the method comprises the steps: carrying out the fragmentation of data according to the data characteristics of a health insurance policy system, the insurance policy type, the time range and the customer region, and carrying out the parallel processing of the fragmented data; performing format conversion on the processed data, and after the data format is determined to be consistent with the format supported by the message queue, packaging the converted data into a message and sending the message to the MQ message queue; parameters of the MQ message queue are configured according to actual requirements, and the MQ message queue is partitioned and copied. The method can be applied to development of business systems such as financial science and technology, medical health, old-age care and the like, massive insurance policy data are stored in a scattered mode through data fragmentation, and the stability and reliability of the system, the data processing efficiency and the throughput capacity are improved through a partitioning and duplicating mechanism of a message queue (MQ).

The invention relates to the technical field of medical health informatization, and discloses a chronic disease tracking management system, which is characterized in that a data acquisition module, a data analysis module, a health monitoring module, a user interaction module, a control module and a tracking management optimization module are established, key factors of physiology, life and environment influencing chronic diseases are comprehensively covered; the data analysis module is used for deeply mining data values based on a scientific calculation formula and accurately identifying potential health risks; the health monitoring module realizes automatic and personalized health early warning and management suggestion pushing according to an analysis result and threshold setting, all the modules cooperate closely, and finally the system has the advantages of data comprehensiveness, risk pre-judgment accuracy, management personalization and service continuity. The problems of data dispersion, risk assessment lagging and single intervention measure in traditional chronic disease management are solved, and a whole-process and intelligent health management service is provided for chronic disease patients.

The invention discloses a cognitive function assessment data acquisition method and device, relates to the field of medical health, and is used for improving the convenience, efficiency and accuracy of assessment. Aiming at ADHD children, concentrated attention data, continuous attention data, selective attention data, alternate attention data, dispersive attention data, work memory ability data, suppression control ability data and cognitive flexibility ability data are respectively acquired by developing multiple rounds of interactive tasks. According to the invention, the portability of evaluation facilities is improved, and the accuracy and efficiency of data acquisition and evaluation are improved.

The invention discloses a facility agriculture land use system, and relates to the technical field of facility agriculture land use, and the system comprises a vector data processing unit which generates an initial pattern spot data set with a coincidence degree identifier; the field intelligent proof unit is used for generating a proof data packet with a unique file number; the third-level joint review unit is used for performing third-level review; the structured achievement management unit is used for establishing an associated index and a structured database; and the cross-module data pushing unit is used for outputting an audit completion voucher and realizing a data closed loop. According to the method, a systematic architecture of vector data processing, field intelligent proof, three-level joint review, structured achievement management and cross-module data pushing is constructed, pattern spot extraction, proof verification and trend analysis intelligentization are achieved through an AI algorithm, a typed template, layered review and an automatic pushing mechanism are used, and the system and the method are suitable for large-scale popularization and application. The problems that traditional facility agriculture land management is scattered in data, split in process and low in efficiency are solved, and a traceable integrated management closed loop is formed.

The invention discloses a complex medical quality management and control index automatic calculation method based on an intelligent agent. According to the index semantic model construction method provided by the invention, the automatic conversion of the medical quality control indexes from a natural language to structured semantics is realized, so that the index definition has computability and mobility, the dependence of manual analysis and script configuration is eliminated, and the standardization, generalization and reuse efficiency of the index definition is remarkably improved. Through multi-source data semantic packaging and an MCP service abstraction mechanism, semantic unification and interface standardization of multi-source heterogeneous data such as electronic medical records, inspection information, disease course records and medical advice management are achieved, and a semantic data layer capable of achieving cross-system access is constructed; the problems of data dispersion, field isomerism and interface incompatibility in a traditional system are effectively solved.

The invention discloses a track retrieval method and device, computer equipment and a storage medium, and belongs to the technical field of artificial intelligence. By introducing multi-source data fusion, space-time knowledge graph construction, graph neural network feature propagation and attention mechanism semantic fusion in the track retrieval process, the problems of data dispersion, low retrieval efficiency, difficulty in unified modeling of cross-modal information and the like in traditional security retrieval are effectively solved. According to the method, cross-modal fusion and efficient retrieval of the trajectory are realized, and the intelligent level of event tracing and real-time analysis in a security scene is remarkably improved.

The invention discloses a coal type sales planning and sales time collaborative management and control method and system based on a coal enterprise, and relates to the technical field of coal sales management. Multi-source data are integrated through technologies such as a data fusion algorithm, the problems of data dispersion and different formats are solved, high-quality data support is provided for follow-up analysis, the sales trend and price fluctuation are accurately predicted by applying a long-short-term memory neural network and a regression analysis model, enterprises are assisted in optimizing sales strategies, the inventory overstock risk is reduced, and the sales quality is improved. By means of linear programming and reinforcement learning algorithms, sales tasks are dynamically adjusted in combination with real-time data, market response speed and sales efficiency are improved, scientificity and flexibility of sales management of coal enterprises are effectively improved, and market competitiveness is enhanced.

The invention relates to the technical field of power infrastructure construction management, and discloses a constructor ability assessment method and system based on an intelligent model, and the method sequentially comprises a multi-source data collection and preprocessing step, an intelligent assessment model construction and training step, and a dynamic early warning mechanism triggering step. The system corresponds to the method. According to the construction personnel capability assessment method and system based on the intelligent model, the multi-dimensional capability associated data is collected and subjected to standardized processing, the traditional data dispersion barrier is broken through, and a high-quality data basis is provided for assessment; secondly, an evaluation result is generated through three-level quantitative transmission, and the limitation that traditional evaluation depends on subjective experience is broken; besides, risk possibilities are output and signals are pushed by constructing an early warning model, so that risk prospective prevention and control are realized, and the actual requirements of electric power infrastructure construction on accurate capability assessment and safety management and control of constructors are met.

The invention provides a smart city data linkage method based on digital twinning, and the method comprises the steps: constructing a fusion modeling layer, constructing a lightweight digital twinning model through CIM, BIM and GIS technologies, packaging a scenarized simulation model through a micro-service architecture, and forming a data linkage space carrier; establishing a space-time-event double-main-line data linkage mechanism by taking the scene as a reference, accessing multi-source data through a stream processing engine and associating the multi-source data to a space coordinate system to form a dynamic data link; a semantic mapping layer based on Ontology unifies data modes and associates and maps the data modes, a cross-domain data linkage channel is constructed, and heterogeneous data semantic-level linkage is achieved; recognizing the state change of the facility through a time sequence model, and generating a cross-department automatic instruction chain in combination with spatial association to form scenarized closed-loop linkage; and constructing a decision support linkage system by using feedback data, integrating a quantitative model and a deduction engine, and converting the data into visual decision information to complete a full-chain scenarized closed loop. The method solves the problems of traditional data dispersion and the like, improves the linkage accuracy and processing efficiency, and provides support for urban governance.

The invention provides an intelligent feeding optimization system and method based on multi-dimensional data fusion, relates to the technical field of intelligent breeding, and solves the technical problems of low overall precision and poor adaptive capacity of the system due to data dispersion and isolation, static and rigid decision-making mechanism and neglect of environmental dynamic influence in the existing intelligent feeding technology. The system comprises a data acquisition layer used for acquiring multi-dimensional data of poultry; the data fusion layer is used for carrying out cleaning, standardization and time sequence alignment processing on the multi-dimensional data and extracting key features to construct a fusion feature vector; the intelligent decision-making layer is used for generating an optimal feeding scheme through a growth prediction model and a feeding scheme optimization model based on the fusion feature vector; and the execution control layer is used for controlling the automatic feeding equipment to execute the optimal feeding scheme, collecting feedback data and returning the feedback data to the data fusion layer. The method is used in the intelligent breeding process.

The invention discloses a park equipment full life cycle management and control system and method based on Internet of Things and digital twinning, and relates to the technical field of smart park operation and maintenance. The method comprises the steps that an equipment sensing unit collects equipment operation parameters and state data; the data aggregation unit synchronously stores the data and the static information of the equipment according to a time sequence; the digital twinborn platform constructs a multi-dimensional digital twinborn body for physical equipment; the prediction module generates an equipment health index based on the twinborn dynamic data and outputs fault risk estimation; when the health index is lower than a threshold value or the fault risk is higher than a threshold value, the operation and maintenance module automatically generates a predictive maintenance work order and intelligently schedules resources; and the feedback module receives the work order execution result and the field feedback, and updates the dynamic state of the corresponding digital twinborn body. According to the method, the problems of equipment state splitting, insufficient predictive maintenance capability and non-cooperative resource scheduling caused by data dispersion and lack of uniform identification can be solved.

The invention discloses an integrated GIS (Geographic Information System) data management system, which relates to the technical field of data management and comprises a multi-source data access module configured to establish connection import with data and perform data format conversion and check screening; the data comprises urban satellite images and urban unmanned aerial vehicle surveying and mapping data; the storage module is configured to store and manage the imported data and store the data on a plurality of storage nodes in a dispersed manner based on a distributed storage architecture; extracting and calling the data based on the data index; and the intelligent processing module is configured to perform deep processing and analysis on the stored data and mine rules from the obtained data. Data storage, management and rapid extraction are achieved through data indexing, the storage capacity and reliability are improved, the intelligent processing module carries out deep processing analysis and rule mining on the stored data, a scientific basis is provided for urban planning and layout, scientific decision making is assisted, and the visualization module presents the processed data in a visual mode.

A hardware accelerator and acceleration method based on a VisionTransformer neural network, the accelerator is to deploy the VisionTransformer neural network on a ZYNQ development platform; the acceleration method is: an ARM processor stores a feature picture into a DDR memory, the read data is dispersed to an input cache and a weight cache, the processed feature picture is input to an on-chip cache unit, the processed data is sent to a PL end, the hardware IP of the PL end is configured, and read-write operation is performed at the same time, the final calculation result is obtained, written into the DDR memory, the data in the DDR memory is taken out and probability operation is completed, the probability operation result is transmitted to a PC, a PetaLinux operating system is transplanted to the hardware accelerator system of the VisionTransformer neural network, and a prediction result of inference is obtained from the PC; the neural network structure is optimized through the parallel method of multiple input and multiple output channels, the calculation speed is fast, the hardware resource occupation is low, the recognition accuracy is high, and the image classification task can be efficiently completed.

The invention belongs to the field of financial settlement, and mainly relates to an accounting archive data query method based on big data, and the method comprises the steps: collecting multi-source heterogeneous data from different systems, and carrying out the unified representation of all data items through a grid algorithm and time-space coordinates; on this basis, association between the space-time anchor points and the service entities is established, and accurate matching and screening are performed on the data in combination with multi-dimensional information such as time, position and amount; the method comprises the following steps of: evaluating the correlation of data entries by calculating process data such as equipment operation duration, and screening the data entries highly matched with an actual business event; an amount logic consistency verification rule is introduced to verify the consistency among data such as contracts, payments and invoices, and potential abnormities are found in time through balance drift analysis; the method can effectively solve the problems of data dispersion, chaos of naming, tedious manual splicing and the like in traditional accounting archive query, and manual intervention is reduced.