519 results about "Data splitting" patented technology

The invention relates to the technical field of construction engineering cost management, and discloses an intelligent engineering cost calculation system based on multi-source heterogeneous data fusion, and the system comprises a multi-source data collection module which is used for collecting structured data and unstructured data from a design file, a market database, a construction monitoring system, a contract document, and a historical project library; and the heterogeneous data fusion module is connected with the multi-source data acquisition module and analyzes the risk terms in the contract text by adopting a natural language processing technology. According to the invention, the multi-source data acquisition module is used for widely collecting data in multiple aspects of design, market, construction, contract and the like, the problems of data splitting and information isolated island in traditional cost management are solved, integration of multi-source heterogeneous data is realized, and the heterogeneous data fusion module utilizes advanced technologies of natural language processing, image recognition and the like, so that the cost management efficiency is improved. Contract texts and design drawings can be efficiently analyzed, the processing capacity of unstructured data is improved, and the error rate and omission rate of manual interpretation are reduced.

The invention discloses a screening and evaluating system and method for cognitive impairment of old people, and belongs to the technical field of intelligent medical treatment. According to the system, electroencephalogram, VR / AR interaction, physiology and gait data are collected through the multi-modal acquisition module, the data processing module carries out data processing, dynamically selects a scale and carries out fusion analysis, the man-machine interaction module realizes natural interaction, and the output module generates a visual report and carries out early warning. The core algorithm comprises dynamic scale selection, multi-modal fusion evaluation and the like. The evaluation method comprises the steps of data acquisition, scale selection, data fusion, confidence verification, output and the like. Compared with a traditional method, the method overcomes the defects that subjectivity is high, and static evaluation, data splitting and base layer application are limited. The cognitive impairment assessment method can accurately and dynamically assess cognitive impairment, improves assessment accuracy, realizes full utilization of data, is simple and convenient to operate, is suitable for various scenes, provides efficient and reliable support for diagnosis, monitoring and intervention of cognitive impairment, and promotes development of intelligent medical treatment.

The invention discloses an image-text content auditing method and system based on a multi-modal large model, and the method achieves the deep semantic understanding and cross-modal integration of unstructured data through the cooperative work of all modules. A semantic association graph is generated through a multi-modal large model, the association recognition precision of the system on situations and information of images, texts, audios and videos is improved, and the problem that an existing system is inaccurate in semantic understanding is solved; the multi-modal data integration module realizes unified alignment of cross-modal data and layered mapping of information density, situation correlation and semantic consistency, and constructs an image-text association vector space, so that data splitting in an auditing process is eliminated; the content abnormity quantification module is combined with the intelligent control module, multi-level auditing decision is carried out through quantitative calculation and comparison of an auditing weight value Hqwz and a content abnormity index Cxzs, manual rechecking is automatically triggered, automatic issuing is directly carried out, the auditing efficiency is effectively improved, and the manual auditing burden is reduced.

The invention discloses an enterprise multi-modal data intelligent processing system fused with an RAG technology and an intelligent processing method of the enterprise multi-modal data intelligent processing system, and relates to the technical field of enterprise-level multi-modal data intelligent processing. And the data processing module is configured to respectively process the structured data and the unstructured data through the dynamic heterogeneous encoder and output unified semantic representation by adopting a cross-modal adversarial alignment mechanism. According to the enterprise multi-modal data intelligent processing system fused with the RAG technology, the problem of enterprise multi-modal data splitting is solved through dynamic adversarial semantic alignment and a stepped fusion mechanism. Semantic gaps are eliminated through self-adaptive convergence of cross-modal features in a hidden space, deep association of heterogeneous data is achieved based on concept mapping and credibility arbitration of an ontology network, key information of unstructured data is accurately extracted and converted into structured knowledge, and the accuracy of cross-modal association analysis and decision reliability are improved.

The invention discloses an intelligent interaction system based on a large language model and a knowledge graph, and relates to the technical field of artificial intelligence and intelligent interaction. According to the system, data processed by a data acquisition and preprocessing module is stored in a local knowledge warehouse in a three-layer nested structure; the multi-modal semantic understanding module constructs a knowledge system in which a triple knowledge graph and a vector database are complementary by optimizing a BERT model and performing dual-channel analysis; the intelligent interaction module realizes natural language interaction and business task automatic triggering based on an RAG technology and a dialogue memory mechanism; the information change identification and analysis module generates a personnel change risk report and performs early warning; and the summary report automatic generation module outputs a structured report. According to the method, the problems of data splitting, complex interaction and slow response in traditional enterprise management are solved, the functions of system intelligent question answering, personnel change risk analysis, structured report automatic generation and the like are realized, and the management efficiency and the information consistency are improved.

The invention discloses a supply chain collaborative management method and system for a whole-industry link platform, and the method comprises the steps: constructing a distributed supply chain data warehouse through employing a block chain and lightweight encryption; generating a multi-dimensional matching degree score table to recommend suppliers; decrypting and storing the encrypted bidding file, and calculating a comprehensive score according to a quantitative index and an expert qualitative index; constructing a hierarchical prediction model, and outputting a three-dimensional prediction result; calculating a supply-demand gap according to a supply-demand elastic coefficient coupling algorithm, automatically generating an order, and synchronizing the order to each end in real time; building a supply chain digital twinborn model, and dynamically planning an optimal transportation route through an intelligent fusion road condition algorithm; early warning information is automatically sent to generate a coping strategy, and full-link operation data are integrated for visual display; the objective of the invention is to solve the problems of existing supply chain data splitting, low supplier matching efficiency, low demand prediction precision, rigid logistics planning, risk monitoring lagging and poor collaboration of all links.

The invention provides a hydropower station AI supervision system and method based on a multi-modal large model, and relates to the technical field of intelligent hydropower. The system comprises a multi-modal data acquisition module, a cross-modal space-time alignment module, a multi-modal feature extraction module, a multi-modal large model processing module and an intelligent reasoning and decision module. A neural differential equation model is introduced to carry out space-time alignment on asynchronous sensing data, networks such as Vision Transformer, MelCNN, TCN and the like are utilized to extract multi-modal features, cross-modal fusion analysis is realized by combining a local and global attention mechanism and dynamic weight distribution, and equipment abnormality is further reasoned based on a reconstruction error, a mahalanobis distance and a knowledge graph and a maintenance strategy is generated. According to the method, high-precision anomaly detection, fault root cause positioning and dynamic maintenance optimization of key equipment of the hydropower station are realized, diagnosis errors caused by traditional manual inspection and data splitting are avoided, and the operation and maintenance intelligence level and the equipment operation reliability are improved.

The invention discloses a geological disaster risk intelligent pre-judgment method based on deep learning, and relates to the technical field of geological disaster monitoring and early warning. According to the method, high-precision alignment and feature extraction can be automatically performed on monitoring data with different temporal-spatial resolutions and different physical meanings, such as optical remote sensing, radar measurement, laser point cloud and the like, uniform and information-rich representations are generated, a solid data foundation is laid for subsequent accurate prediction, and the limitation of data splitting application in a traditional method is overcome; a space-time diagram with slope units as nodes is constructed, an attention mechanism diagram convolutional network with hydrological directivity introduced is utilized, and the model can accurately describe the spatial propagation process that slope substances migrate and accumulate along with a confluence path and block a river channel under the rainfall condition; meanwhile, the time sequence module effectively learns the influence of the past hydrological state on the future evolution trend.

The invention relates to a gold mine air-ground-in-well rapid collaborative exploration method, belongs to the field of geological exploration, and aims to solve the technical problems of data splitting, low target area positioning precision, insufficient deep prediction capability and the like in traditional gold mine exploration. By integrating air remote sensing, surface geological survey and underground detection data, a multi-source data standardization processing flow is established, and a progressive exploration system from wide-area screening to accurate positioning is realized by combining geological, geophysical and geochemical comprehensive analysis methods. The system adopts a dynamic feedback mechanism to optimize an exploration process, forms closed-loop analysis and prediction, improves exploration efficiency and accuracy, and reduces resource waste and exploration cost. The method is suitable for gold ore resource exploration under complex geological conditions, has remarkable economic benefits and application value, and can be widely applied to the field of mineral resource development.

The invention provides a drug identification information efficient query method and system based on distributed cache. The method comprises the following steps: firstly, receiving and analyzing a drug identifier query request to generate a dynamic cache routing key, then positioning a target cache node, then matching a cache data block corresponding to a drug unique code in the target cache node, if matching succeeds, extracting a drug full life cycle record in the cache data block, and sending the drug full life cycle record to the target cache node; if the matching fails, initiating a cross-node retrieval request to the drug block chain database to return drug source data, splitting the drug source data into a core attribute set and an extended track set, and finally executing a dynamic combination operation on the core attribute set and the extended track set to generate a drug tracing result set and returning the drug tracing result set to the user terminal; according to the technical scheme provided by the invention, the query fluctuation defect of a single storage architecture is eliminated from the source, so that the whole system simultaneously meets three drug traceability core requirements of high concurrency, cross-mechanism and tamper-proofing.

The invention discloses an intelligent data splitting and optimizing method and system based on multiple dimensions. The invention relates to the technical field of data splitting. And dividing the number and size of the sub-tasks based on dimensions and metrics required to be split, and dynamically scheduling the dependency relationship and the execution sequence among the sub-tasks. Based on the execution efficiency of the dimension combination and the data skew condition, dynamically adjusting the splitting strategy of the dimension combination, for example, increasing the number of subtasks of hot dimension combinations, optimizing the processing logic of the dimension combination with serious data skew, and the like; through a task splitting and dynamic scheduling mechanism, a large task is decomposed into a plurality of small tasks to be executed in parallel, distributed computing resources are fully utilized, and data processing and analysis time is remarkably shortened. By optimizing the data storage structure and utilizing the ETL tool to clean and compress the data, the occupied physical storage space is reduced, the storage cost is reduced, and meanwhile, the data access speed is increased.

The invention relates to an optimization method for intelligent ISO drawing output based on an external platform. The optimization method comprises the following steps: S1, importing a model and judging a model type; importing a model, and judging whether the model is a two-dimensional model or a three-dimensional model; s2, verifying the three-dimensional model: verifying the three-dimensional model; s3, model data splitting: splitting the verified three-dimensional model; s4, generating a pipeline component file; s5, processing the generated PCF file through an ISO # algorithm; s6, generating an ISO map of the pipeline according to the data processed by the ISO # algorithm; s7, generating a unique reference number and coordinates; S8, establishing data version management, and establishing a data version management mechanism; s9, when the three-dimensional model is modified, automatically updating the two-dimensional model data and the ISO map; and S10, auditing and publishing: auditing the generated ISO map. By efficiently processing two-dimensional and three-dimensional model data in an engineering project, automatic generation of the ISO drawing is achieved, the method is widely applied to the field of CAD design and the like, and the working efficiency and the drawing accuracy are improved.

The invention discloses a coal mine underground equipment personnel collaborative safety monitoring and risk early warning method, which comprises the following steps: deploying a sensing network, and collecting and processing personnel data and equipment data; evaluating the health state of the equipment based on the equipment data; cleaning the personnel data and then constructing a trajectory model; performing risk coupling analysis based on the three-dimensional risk identification model to obtain a comprehensive risk value; and performing grading response based on the comprehensive risk value and judging whether to perform model optimization or not. The invention further discloses a coal mine underground equipment personnel collaborative safety monitoring and risk early warning system which comprises a sensing layer, the sensing layer is connected with an analysis layer through a network layer, the analysis layer is connected with an execution layer, and the execution layer is connected with the sensing layer. The invention discloses a coal mine underground equipment personnel collaborative safety monitoring and risk early warning method and system, solves the technical bottlenecks of data splitting, response lag and poor environmental adaptability of a traditional monitoring system, and reduces the accident false alarm rate by more than 35% through spatial coupling analysis.

The invention relates to the field of emerging software and information technology service, in particular to an artificial intelligence-based application system integrated management method, which comprises the following steps of: analyzing an API (Application Program Interface) log, structured data, an unstructured document, business work order data and business image data by pre-training a large model, and generating a unified semantic representation in combination with multi-modal contrast learning; a knowledge distillation technology is adopted to migrate the large model capability to a lightweight neural network, and a domain knowledge base is generated based on fine tuning of business work order data; a user multi-mode instruction is analyzed, a DAG service agent template library is matched, and an execution chain is dynamically combined based on a reinforcement learning strategy, so that text processing, multi-system collaborative reasoning and RPA service process automation are realized; and collecting an execution log, and updating lightweight network parameters and an intelligent agent strategy library through an online distillation algorithm to form a closed-loop optimization mechanism. According to the method, the service response efficiency can be improved, and the problems of enterprise multi-service system data splitting and process stiffness are solved.

The invention discloses a brand propagation index construction system, and particularly relates to the technical field of brand analysis. A data processing system; an analysis model system; a visualization system; a feedback optimization system; and dynamically updating the system. By constructing a full-link intelligent closed-loop system, the problems of data splitting and strategy lagging in traditional brand propagation analysis are solved, the system integrates cross-platform data sources to achieve efficient fusion of multi-source heterogeneous data, the limitation of data islands is broken through, the collaborative application of dynamic factor analysis and generative adversarial networks is achieved, and the analysis efficiency is improved. The system can perceive propagation scene changes in real time, dynamically adjust data weights and model parameters and ensure that analysis results are adaptively optimized along with market situations, meanwhile, a linkage mechanism of an A / B test engine and a genetic algorithm enables strategy recommendation, parameter optimization and version iteration to be automatic, decision response time is remarkably shortened to the minute level, and the market development efficiency is improved. And real-time and accurate decision support is provided for brand management.

The invention discloses a building engineering multi-dimensional monitoring system based on panoramic imaging, and relates to the technical field of building engineering monitoring and sensing. Comprising a panoramic image acquisition module, an image splicing and panoramic reconstruction module, a multi-source data synchronous acquisition module, an image-data fusion construction module, an image-physical association modeling module and a risk identification and intelligent response module, an image acquisition array formed by high-resolution cameras is installed at key positions of a building structure, images of all the cameras are obtained, and an original image sequence covering a monitoring area is output. According to the invention, through fusion of the panoramic image and the multi-source sensing data, visualization, intelligent identification and risk prediction of the structure state are realized, a closed-loop monitoring system is constructed, the problems of single traditional monitoring means, data splitting and the like are solved, and the safety monitoring intelligent level of constructional engineering is improved.

The invention relates to the technical field of rural space governance and intelligent decision making, in particular to a rural space planning method and related equipment, and the method comprises the steps: obtaining multi-source data of a target rural, the multi-source data comprising land data, population data and rural economic data of the target rural; performing fusion processing of space-time alignment on the multi-source data to obtain fusion data; constructing a spatio-temporal knowledge graph based on the fused data, and extracting entity attributes and spatial relationships; and inputting the entity attributes and the spatial relationship into a pre-trained planning optimization model, iteratively optimizing a rural space matching strategy according to rigid constraints, and outputting an optimal planning result, the technical problems that in the prior art, rural planning faces data splitting, element analysis isolation, planning scheme staticization and actual development requirements are disjointed, the decision making process depends on subjective experience, and economic-ecological benefit tradeoff is difficult to quantify are effectively solved.

The invention relates to the field of intelligent control, and discloses a refrigerator multi-parameter collaborative awareness and resonance intelligent wakeup control method, which comprises the following steps: dynamically acquiring temperature, humidity and door state signals and adjusting the weights of the signals, extracting the resonant frequency offset by combining the vibration spectrum of a compressor, and performing intelligent wakeup and refrigeration duration prediction based on the characteristics. And credibility evaluation, a self-learning mapping model and an interference filtering mechanism are introduced. Compared with a traditional single-parameter or fixed threshold value control mode, the control logic is driven through physical quantity changes, under triggering of a door state event, a three-dimensional linkage relation of an environment state, a physical signal and a control decision is formed, timely sensing and accurate response to changes of the internal thermal characteristics of the refrigerator are achieved, and the problems of data splitting and lag control are solved.

The invention discloses an electronic medical record intelligent coding method, device and system, and a storage medium. The method comprises the following steps: respectively carrying out entity extraction, feature coding and homomorphic encryption transmission on an electronic medical record text, a medical image and structured inspection data; according to the preprocessed data, performing multi-modal feature alignment, ICD semantic mapping and real-time medical insurance rule injection through a dynamic knowledge fusion coding engine; generating a three-dimensional visual evidence chain of the text evidence, the image evidence and the policy evidence through the interpretable traceability matrix; through a multi-role cooperative workflow engine, generating a code according to a confidence threshold routing AI, and auditing the code to a clinician or a professional coder; rare disease data are synthesized through an adversarial training enhancement module, and policy mutation is simulated for model adaptability training. By adopting the technical scheme of the invention, the problems of multi-modal data splitting, policy lag and non-traceability in the prior art are solved.

The invention discloses a compression method and device for generic semiconductor industry operation and maintenance data, electronic equipment and a medium, and relates to the technical field of data compression. The method comprises the following steps: acquiring to-be-compressed generic semiconductor industrial operation and maintenance data; identifying the time sequence of the generic semiconductor industrial operation and maintenance data to be compressed, and judging whether the generic semiconductor industrial operation and maintenance data is time sequence data or not according to the time sequence; and if the to-be-compressed generic semiconductor industrial operation and maintenance data is time series data, splitting the to-be-compressed generic semiconductor industrial operation and maintenance data into a time data set and a feature data set, and compressing the time data set and the feature data set respectively. According to the compression method, different compression strategies are adopted for different types of data, the compression efficiency of the data is improved, and the balance between the compression rate and the calculation efficiency is optimized.

The invention relates to the technical field of power equipment safety inspection. The power inspection fault diagnosis method and system based on the unmanned aerial vehicle multispectral image are provided, and the method comprises the steps: carrying out the multispectral data collection of power equipment, and obtaining a visible light image, multispectral reflectivity data and infrared thermal image data; dynamically correcting emissivity change caused by oxidation or dirt on the surface of the equipment to generate a dynamic emissivity correction coefficient table; according to the dynamic emissivity correction coefficient table, temperature calibration is carried out on the infrared thermal image data, and a calibrated temperature distribution diagram is generated; and fusing the calibrated temperature distribution diagram, the preprocessed visible light image and a multispectral reflectivity distribution diagram obtained by preprocessing the multispectral reflectivity data, performing multimodal fault diagnosis, and outputting fault types and positions, so as to solve the problems that single spectral data is easy to misjudge, emissivity static assumption errors are large, and the accuracy is high in the prior art. And the problem of insufficient confidence caused by multi-modal data splitting analysis is solved.

Embodiments of the present application provide a data splitting method and apparatus, a device, a storage medium, and a program product. The method comprises: parsing a request message sent by a sending end to obtain a cluster diversion address and an inner layer protocol header; determining a gateway cluster corresponding to the cluster diversion address, and acquiring an address set corresponding to a plurality of gateway nodes in the gateway cluster; selecting from the address set a target address matching the inner layer protocol header, sending the request message to a target gateway node corresponding to the target address, so that the target gateway node adds to the request message a node diversion address corresponding to the target gateway node, and sends the request message to a receiving end; and receiving from the receiving end a reply message carrying the node diversion address; and sending the reply message to the target gateway node corresponding to the node diversion address, so that the target gateway node sends the reply message to the sending end.

The invention relates to the technical field of data cache management, and discloses a segmented multi-level data cache management method and device, computer equipment and a storage medium. The method comprises the following steps: defining a hierarchical data management module, wherein the data management module comprises a first-level data interaction sub-module and a second-level cache hit management sub-module; receiving an upper-layer data access request, and performing data splitting according to the logic address relationship; querying the module state of the position according to the actual situation, and marking the cache hit management module state of the corresponding position; if the second-level cache hit management sub-modules to which the first-level data interaction sub-modules belong are all hit, realizing data communication with lower-layer storage equipment according to large granularity; and if part of data enters the cache, according to the continuity of the data hit state, respectively constructing commands with corresponding lengths to lower-layer storage equipment. By implementing the method provided by the invention, access requirements of different types of data can be effectively realized, the cache hit rate is improved, and better performance improvement is obtained.

The embodiment of the invention discloses a security deployment method and device for enterprise-level applications and a medium, and relates to the technical field of security deployment, and the method comprises the steps: obtaining application topological graph data generated by a preset visual development platform, so as to split the application topological graph data into an atomized micro-service unit set through a quantization deconstruction engine, generating a micro-service dependency tree; scanning the target deployment environment, extracting an environment feature fingerprint of the target deployment environment, and generating an environment adaptation layer code according to the environment feature fingerprint; injecting an environment adaptation layer code into each atomized micro-service unit to generate an environment perception type micro-service package, and constructing a cross-cloud communication link matrix based on the micro-service dependency tree; and based on the environment-aware micro-service packet and the cross-cloud communication link matrix, executing a deployment verification test in the sandbox environment, generating a deployment verification report, and according to the deployment verification report, distributing the environment-aware micro-service packet to a target deployment environment node.

The invention provides an industrial inspection-oriented defect autonomous decision-making method, device and equipment and a medium, and belongs to the technical field of intelligent manufacturing. The equipment defect autonomous decision-making method comprises the following steps: acquiring equipment operation state information of industrial equipment by using a multispectral fusion terminal, and uploading the equipment operation state information to a cloud server; a built-in cross-modal deep analysis model of the cloud server is used to carry out cross-modal learning on the equipment operation state information according to the double-flow heterogeneous deep network architecture, and joint distribution of visual-text features of the industrial equipment is learned to obtain defect feature vectors of the industrial equipment; performing multi-dimensional matching on the defect feature vectors and similar cases in a maintenance knowledge base, and screening treatment schemes corresponding to the defect feature vectors to obtain a maintenance strategy; and issuing the defect information corresponding to the defect feature vector and the maintenance strategy to a communication terminal of a maintainer. According to the method and the device, the problem of low cross-modal information utilization rate caused by multi-modal data splitting and no feature level fusion in the prior art can be solved.

The invention provides a highway bridge comprehensive monitoring system based on big data, and relates to the field of intelligent monitoring. A data processing technology based on big data is adopted to carry out data splitting and time sequence feature extraction on a time data set of key health data of a bridge so as to obtain dynamic parameter time sequence correlation implicit coding features and environmental parameter time sequence correlation implicit coding features; and obtaining an intelligent auxiliary evaluation result based on heterogeneous multi-source parameter feature interaction coding representation between the dynamic parameter time sequence correlation implicit coding feature and the environment parameter time sequence correlation implicit coding feature. Thus, by processing the bridge monitoring data in real time and fully considering the non-linear relationship between different bridge monitoring data during processing, the health condition of the bridge can be evaluated more accurately, and the requirements of accuracy, timeliness and comprehensiveness of highway bridge monitoring are met.

The invention discloses an enterprise archive informatization intelligent management system based on big data. The system comprises a data acquisition module which is used for acquiring enterprise archive data from each business system in an enterprise and an external data source; relates to the technical field of archive management, complete enterprise archive data are split into multiple pieces of fragmented archive information data, and the fragmented archive information data are classified and stored by a fragmented archive information data classification storage module, so that the fragmented archive information data can be directly mined and processed subsequently, and the archive management efficiency is improved. During transmission, small data of a plurality of pieces of fragmented archive information data is beneficial to stable transmission; when a user initiates a request for generating enterprise archive data, a first-level authority user can directly retrieve all fragmented archive information data and generate a complete archive, and a second-level authority user can generate an archive independently or in a combined mode. Users with different permissions can conveniently obtain required archives, and enterprise archive data can be flexibly recovered.

The present invention relates to the technical field of medical imaging. Disclosed are a method, system and apparatus for oral cavity CBCT ultralow-dose imaging. The method comprises: collection of high-dose oral cavity CBCT image data, data splitting processing, data three-dimensional reconstruction processing, model training, image data inputting, image enhancement, and image data outputting; and the specific process involves: performing three-dimensional reconstruction processing on oral cavity CBCT two-dimensional projection data in an ultralow-dose mode of a patient, so as to obtain ultralow-dose oral cavity CBCT three-dimensional reconstruction image data, inputting same into an oral cavity CBCT ultralow-dose imaging image enhancement network model, and performing outputting to obtain high-quality oral cavity CBCT image data for a subsequent clinical diagnosis and treatment process. The present invention can significantly reduce a radiation dose for imaging and accelerate an imaging speed while ensuring the imaging quality, thereby improving the safety of oral cavity CBCT imaging, and having broad clinical application prospects.

The invention discloses an electric power data acquisition control method and device, and a storage medium. The method comprises the following steps: receiving a control instruction; executing a control action according to the type of the control instruction, which comprises any one of the following steps: if the control instruction is a data acquisition instruction, acquiring acquisition data, splitting the acquisition data into a structured data unit by taking a measurement point dimension as a unit, and storing the structured data unit into a task data table; and if the control instruction is a data reporting instruction, obtaining corresponding structured data units in a task data table in batches to generate task data group packets, and reporting the task data group packets to a server. According to the method, integrated fine control of electric power data acquisition, storage and reporting is realized through a measurement point dimension structured data splitting and dynamic packaging mechanism, the data transmission efficiency, the data analysis capability and the acquisition reliability are synchronously improved, and the technical effect of matching of service requirements and storage structures is fundamentally realized.

The invention relates to the technical field of engineering digitization and information, and discloses a water conveyance tunnel BIM model engineering management business application method, which comprises the following steps: carrying out management business carding, and determining an engineering unit hierarchical structure; uniformly coding the data information related to the management service and the hierarchical structure data of the engineering unit to form a service data coding result and an engineering division coding result; creating a water conveyance tunnel BIM model, and endowing model components with the codes to form BIM data carrying code information; inputting the business data and the BIM data carrying the coding information into a digital construction and management system, and associating the business data and the BIM data by using a common coding identifier; based on the association, business management digital applications of investment, progress, quality, safety and the like are carried out in a digital construction and management system. Through standardized data sorting and coding, fusion of the BIM model and engineering management business is realized, the problem of data splitting is solved, and the refinement and digitization level of water conveyance tunnel engineering management is improved.