144 results about "Data model (GIS)" patented technology

Embodiments of the present disclosure provide a three-dimensional scene reconstruction method and apparatus, a device, a medium, and a program product. The three-dimensional scene reconstruction method comprises: acquiring a scene image collected for a three-dimensional scene; on the basis of the scene image, determining sparse point cloud data and camera parameter information corresponding to the scene image; performing model initialization on the basis of the sparse point cloud data to obtain a current three-dimensional data model; performing rendering on the basis of the camera parameter information and the current three-dimensional data model to obtain a current color map, a current depth map and a current normal map from the perspective of the scene image, and determining a pseudo normal map from the perspective of the scene image on the basis of the current depth map; and on the basis of the current color map, the current normal map, the pseudo normal map, and an actual color map, training the current three-dimensional data model to obtain a trained target three-dimensional data model. By means of the technical solution provided by the embodiments of the present disclosure, higher-quality automatic reconstruction of three-dimensional scenes can be achieved, reducing reconstruction costs, and improving the level of detail and rendering quality of scene models.

The invention relates to the technical field of water network intelligent management and control, and discloses a water network management and control multi-source space digital intelligent fusion base construction and decision optimization method, which comprises the following steps: cooperatively obtaining multi-source space data; format conversion, coordinate system unification and systematic semantic annotation are carried out through a data preprocessing platform, and a normalized spatial data set is formed; constructing a data fusion model, quantitatively evaluating the quality of a data source by adopting a fuzzy comprehensive evaluation method so as to determine a fusion weight, and performing weighted fusion by adopting a specific algorithm aiming at different data types such as vectors, grids and three-dimensional models so as to generate a unified spatial data model; and finally, a decision optimization system performs decision scheme generation and iterative optimization based on the model in combination with a hydrodynamic model and a genetic optimization algorithm. By establishing a standardized data processing and targeted weighted fusion process, the problems that multi-source heterogeneous data is difficult to integrate and the fusion precision is not high are effectively solved, and a reliable data base is constructed.

The invention discloses a hydrological data model fusion analysis method based on water resource scheduling decision support, and relates to the field of water resource scheduling, and the method comprises the steps: loading an HMM-BP noise detection model, obtaining a multi-source data fusion model, and outputting a space-time grid data cube; constructing a water consumption behavior prediction unit through a TPB decision tree model, adding a water right transaction engine, and outputting a water consumption prediction value, a behavior of an intelligent contract protocol and a transaction cooperation model; an incremental method is adopted to generate N combined scene matrixes of rainfall and temperature rise correlation adjustment, an ecological stability evaluator is combined, a climate and ecological coupling model is constructed, and a scene and risk mapping table and a resource re-allocation weight are output; and constructing an intelligent rule base platform to obtain an executable decision logic tree. The system has the advantage that full-chain intelligentization of water resource scheduling is realized through modular integration. Therefore, social and market collaborative prediction, climate and ecological risk quantification and adaptive decision support are achieved.

The invention discloses a knowledge-data dual-drive urban inland inundation simulation method considering uncertainty. The method comprises the following steps: acquiring basic hydrological elements and geographic information data to construct a feature input set; constructing an urban inland inundation physical model based on a hydrological hydrodynamic principle; the physical model parameters are iteratively corrected based on actually measured rainfall-inundation data, and a water depth data set with parameter uncertainty constraints is output; correcting data uncertainty, and constructing an urban waterlogging data set; generating and training a sub-model group through self-service sampling, and fusing structural uncertainty and weight uncertainty by adopting an integration strategy; and quantifying the uncertainty of integrated prediction, outputting a prediction result with a confidence interval, and verifying the precision. According to the method, the interpretability of a physical model and the feature learning ability of a data model are effectively fused, high-resolution and interpretable waterlogging water depth prediction in a complex urban scene is realized through a multi-source uncertainty quantification mechanism, and reliable support is provided for early warning and intelligent scheduling of urban flood.

The invention discloses a complex system data visualization modeling method based on GIS and topological graph fusion, and relates to the technical field of data visualization modeling, and the method comprises data fusion modeling, space-time anomaly reasoning, state propagation modeling and multi-dimensional visualization enhancement. The method comprises the following steps: performing unified access, cleaning and standardization processing on operation data, topological relation data, geographic space data, function configuration data and environment data of a complex system, and constructing a unified data model fusing geographic attributes and topological attributes; realizing abnormal root cause reasoning and spatial constraint propagation modeling of a system state by using a convolutional time sequence modeling method combined with a graph neural network; a dynamic evolution rule of a node state is described through a time gating mechanism, and interactive display is realized; according to the method, global visualization of the operation state of a complex system, dynamic backtracking of an abnormal propagation path and hierarchical analysis of key nodes can be realized, and the intelligent monitoring, situation awareness and decision support capabilities of the system are improved.

This invention relates to the field of short-term meteorological forecasting technology, specifically to a forecasting model architecture based on point cloud data and a spatiotemporal frequency domain joint attention mechanism. This forecasting model architecture includes a Z-coordinate system three-dimensional point cloud visualization data model and a P-coordinate system four-dimensional spatiotemporal frequency domain joint attention model. The three-dimensional point cloud visualization data model directly represents the three-dimensional distribution of meteorological elements. Combined with the DEM trust propagation completion algorithm, the observation coverage of a 1km resolution area is increased by 40%, significantly improving the forecast accuracy in complex terrain areas (such as mountainous regions). Then, a decision tree model and satellite observation data are used to fuse precipitation data, filling in the gaps in precipitation observation data for areas without monitoring stations. Finally, based on the Earth's rotation period and P-coordinate system four-dimensional spatiotemporal time domain data, a Fourier transform + phase modulation module enhances the frequency domain capture capability of precipitation cycle signals, significantly improving the TS score for severe convective weather.

The invention discloses a glass-based circuit board defect detection method and system, and relates to the technical field of glass substrate defect detection.The method comprises the steps that an optical coherence tomography system with the fixed scanning resolution of 320 * 320 is used for collecting a tomographic image of a target area, three-dimensional reconstruction is conducted on the tomographic image, and a three-dimensional body data model is obtained; extracting a plurality of three-dimensional morphological characteristics such as defect depth, transverse distribution profile and defect internal refractive index unevenness from the model; and inputting the features into a defect classifier constructed based on a three-dimensional convolutional neural network for identification, and performing spatial position verification in combination with a known design layout to generate a final detection report. According to the method, the standardization of the detection process is realized through the fixed scanning resolution, and the efficiency and the result consistency are improved; by quantifying the refractive index non-uniformity in the defect, the optical property variation type defect in the material is effectively identified, and the detection depth and accuracy are enhanced.

The invention provides a visual network topological graph dynamic drawing and layout method based on Antv / X6, relates to the technical field of front-end graph visualization, and solves the problems of insufficient dynamics, low layout efficiency, poor interaction experience and poor integration expansibility in the existing network topology drawing technology. The method comprises the following steps: firstly, constructing a standardized data model decoupled from a rendering layer, and describing a network topology structure; initializing a canvas instance based on an Antv / X6 graphic engine, instantiating the standardized data model into a graphic object, and adding the graphic object into a canvas; through selection and application of various layout strategies, executing a layout algorithm to calculate node coordinates and trigger animation transition, and generating a visual network topological graph which can be operated by a user; when a user performs multi-dimensional dynamic interaction with the topological graph, data changes are managed and monitored, and re-rendering or re-layout is triggered. According to the method, the requirements of automatic drawing, dynamic layout optimization, smooth interaction, high maintainability and the like of the topological graph can be smoothly met.

The invention provides a horizontal lifeline inspection method and system based on an inspection robot, and the method comprises the steps: collecting and fusing positioning data and line distance data to construct a three-dimensional space data model, and providing a space reference for an inspection process; through obtaining historical detection data and electric quantity data of the inspection robot, an inspection route is generated based on a three-dimensional space data model, and pertinence and rationality of inspection are realized; the inspection robot is controlled to inspect according to a planned route and collect all-round image data, the view angle limitation of an existing inspection mode is broken through, the problems that the view field of manual inspection is limited and all-round details are difficult to observe by an unmanned aerial vehicle are solved, and a comprehensive image basis is provided for subsequent defect recognition; and inputting all-round image data into the defect identification model to output defect identification data, and associating the position of the three-dimensional space data model to form a report, so that the intelligence of defect identification and the precision of positioning are realized, and the problem of poor inspection effect of the horizontal lifeline in the prior art is solved.

The application discloses a data model and data standard mapping method, device, equipment and medium, wherein the data model and data standard mapping method comprises: obtaining data standard information of metadata corresponding to each data type through a standard source end; based on a data standard template corresponding to the data type, using the data standard information to define governance attributes of the metadata corresponding to the data type, so as to generate preliminary data standards corresponding to all the metadata; a review end returns public data standards corresponding to the metadata based on the preliminary standards; any data model is obtained, the semantic distance between the data model and the public data standards is calculated, and based on the semantic distance, the mapping relationship between the data model and the public data standards is confirmed. The method can improve the efficiency of extracting general standards for different data models offline in advance in the process of formulating data standards, and intelligently establishes the associated mapping relationship between the data model and the data standards.

The embodiment of the invention discloses a drawing analysis method and device for an electric power tower, equipment and a storage medium, and the method comprises the steps: obtaining an original image of a two-dimensional engineering drawing of the tower, and carrying out the preprocessing of the original image to generate a standardized image; performing layout analysis on the standardized image, and identifying a plurality of functional areas; for a graphic region in the functional region, extracting graphic elements of the graphic region, and analyzing a topological relation between the graphic elements to construct a geometric model representing a tower structure; performing text recognition and semantic analysis on the text contained in the functional region to extract structured semantic attribute information; based on the geometric model and the semantic attribute information, establishing a corresponding relationship between the graphic elements and the semantic attribute information to generate structured data containing geometric and semantic information; and outputting the structured data as a data model in a preset format. In this way, high-precision information extraction is achieved, and the automatic analysis capacity and digital modeling efficiency of tower drawings are remarkably improved.

The invention discloses a method and system for constructing a universal digital twin asset data model for multi-source heterogeneous data exchange and sharing, and belongs to the technical field of digital twin. The method comprises the following steps: obtaining three-dimensional data structures and three-dimensional data indexes of different geometric forms in a digital twin model, the spatial topological relation between the three-dimensional data structures is identified; converting texture map information of the three-dimensional data structure into a unified format, normalizing coordinates of the texture map information, and unifying vertex coloring information of the three-dimensional data structure to a standard color space; and performing material analysis and description on different material characteristics of the digital twin model, dynamically calling node objects corresponding to the different material characteristics to obtain real material information, and finally dynamically outputting to obtain a general three-dimensional data model. According to the invention, the problem that a unified digital twin floor scene is difficult to generate due to different sources and structures of current model data can be solved.

The invention relates to the technical field of natural resource management, in particular to a marine park natural resource right confirmation management system and method based on three-dimensional modeling. Comprising the following steps of 1, constructing a three-dimensional data model; step 2, performing visual representation; step 3, spatial analysis and calculation; 4, establishing a database and a management interface; and constructing a three-dimensional right confirmation registration unit body data model of the natural resources, and realizing three-dimensional space distribution feature description, reserve estimation, ownership boundary division and visual representation of the natural resources. The problems that traditional two-dimensional data is insufficient in precision, poor in visualization effect and low in management efficiency are solved, the precision and efficiency of natural resource management are remarkably improved, and powerful technical support is provided for overground and underground space integrated management of natural resources.

The present invention discloses a mobile real-time geological survey data acquisition and analysis system for complex terrain, which relates to the field of geological survey technology. The acquisition and analysis system includes: a mobile acquisition terminal, an integrated multi-platform acquisition device and sensor that adapts to complex terrain, a historical data template library, which stores multi-dimensional historical geological data that has undergone standardization processing. The standardization processing includes data cleaning, feature extraction, and time-space coordinate calibration, and supports template retrieval and reuse based on feature similarity. A historical data reuse module realizes the reuse of historical templates, the semantic association of multi-source data, and the real-time adjustment of new data of the basic template through template matching, data fusion, and incremental updates. This system reuses the overlapping parts of historical geological survey data, thereby reducing the redundant analysis of newly collected geological data. It only needs to match the reused data model and update the model in combination with the new data to complete more efficient geological survey data acquisition and analysis.

A kind of geotechnical engineering application analysis system based on BIM and GIS combination, it is related to geographic information technology field, it is characterized in that the system includes: data integration module, model fine presentation module, evaluation analysis module and attribute data modeling module, each module is sequentially connected, data integration module carries out integrated display to the various data of multi-source heterogeneous;Evaluation analysis module carries out evaluation analysis to pile foundation model according to the spatial position and attribute information of pile foundation model layer and engineering geology model layer in three-dimensional scene;Attribute data modeling module carries out modeling to the attribute field of geotechnical investigation design information model according to modeling parameter, and modeling result is rendered and exported in three-dimensional scene.Optical advantage: system realizes to "BIM+GIS" integrated technology as foundation, to multi-source heterogeneous data visualized integration, quantification analysis, collaborative application as goal, forms set above, ground, underground geotechnical engineering multi-source data three-dimensional visualized integrated display.

The invention relates to a map element data generation method and device, equipment, a medium and a program product, and relates to the technical field of map generation. The method comprises the steps of obtaining at least one kind of map data of a target region; the map data comprises elevation data and image data; the elevation data corresponds to at least one data model category; for the elevation data of the same data model category, dividing the elevation data into first precision data and second precision data, and performing precision fusion on the first precision data and the second precision data to obtain precision fusion data; the data precision of the first precision data is greater than that of the second precision data; extracting perception semantic data of a semantic object in the target region from the image data; and generating map element data according to the perceptual semantic data and the precision fusion data of each data model category. By adopting the method, the data quality and the generation efficiency of the map element data can be improved.

The invention discloses a construction supervision method and system based on a squat silo, and relates to the technical field of construction digital monitoring, and the method comprises the steps: collecting geometric and image data, building a design reference model, generating a check point according to a fixed arc length, unifying actual measurement coordinates to design coordinates through image recognition and homonymy point rigid body transformation, and carrying out the calculation of the design coordinates; and on the basis of the knowledge graph, determining unique mapping of the actually measured coordinates and the design coordinates by process consistency, adjacent topology and geometric dissimilarity, and calculating a deviation to generate a report. According to the method, the comparison consistency is improved and the mismatching rate is reduced based on the unified aperture and the coordinate system, the robustness is enhanced through hierarchical semantic constraint and geometric discrimination, manual setting is reduced through threshold determination, the out-of-limit determination accuracy is improved, the local increment updating and versioning storage functions are achieved, and the efficiency and the traceability are better.

The present application discloses a method and device for identifying and predicting micro-rainfall weather processes, which belongs to the field of environmental monitoring technology. The method collects cloud data from Ka-band cloud radar, precipitation data from X-band rain radar, and data from automatic weather stations. A nonlinear model is established, and the data output by the nonlinear model are grouped according to the time axis and radar type. A fitting curve for the micro-rainfall weather process is established to calculate the coefficient of determination and generate eigenvalues, and the prediction result is determined based on the eigenvalues. The output data of the nonlinear model is corrected based on the data from the automatic weather station and the eigenvalues, and the corrected coefficient of determination and eigenvalues ​​are input into the historical data model library as prediction conditions. The judgment results under the same conditions are screened out and compared with the prediction results. If the comparison result is valid, an alarm information push is generated. The method and device for identifying and predicting micro-rainfall weather processes provided by the present application realize the full-process observation and prediction of water vapor-cloud-precipitation, significantly reducing the false alarm rate.

The invention discloses an enterprise-level multi-dimensional project digital intelligent management and analysis system for geotechnical engineering investigation, and the system integrates a project data center module, a multi-dimensional visualization and analysis engine, a process collaboration and monitoring module, an enterprise-level knowledge base module, and a unified authority and safety control module. Unified standardized storage and linkage of full-period multi-source data of a project are achieved through a mixed data model, two-dimensional and three-dimensional integrated visualization and cross-project analysis functions are provided based on a geographic information system engine, and full-process digital collaboration and real-time monitoring of the project are driven by means of a configurable workflow engine. Intelligent reuse of enterprise-level knowledge is realized through knowledge association retrieval, and refined authority control and operation auditing are implemented in combination with role and data sensitivity. The comprehensive efficiency and the achievement quality of enterprise project management are remarkably improved, the operation cost and the data safety risk are reduced, and a powerful core supporting tool is provided for digital-intelligent transformation of geotechnical engineering investigation enterprises.

Context-based tabular data models use a context to evaluate a queried data point. Rather than a randomized or full context of domain data points, a local context of data points is selected that is customized for a particular data query. The system uses a pre-trained model, such as a TabPFN, that is trained on a classification for different types of data sets along with a “context” for applying the model with the nearest neighbors of that data point. The number of neighbors may vary and may be determined based on the distance of data points to the query point. The system also optimizes fine-tuning of tabular data models with neighborhood data so that local context can be used to select training batches of data using a common context. This allows local context fine-tuning without excess training costs of single-item training batches.

The present application relates to the technical field of water ecological early warning, and discloses a mountain city water ecological safety early warning method based on multi-level division, comprising the following steps: step 1, obtaining multi-source heterogeneous spatio-temporal data of a target mountain city; step 2, identifying topographic and geomorphic units through a topographic analysis algorithm; step 3, constructing a three-level stereoscopic spatial data model for mountain city water ecological safety early warning, which comprises a mountain ecological barrier layer, a water system network layer and a city fusion layer; step 4, converting index values into score values; and step 5, using a weighted summation model to calculate early warning values and a comprehensive early warning index at each level according to the score values and mountain adaptability comprehensive weights, determining an early warning level and generating an early warning result. The present application can realize systematic and stereoscopic quantitative evaluation and dynamic early warning of mountain city water ecological safety, and is helpful to improve the accuracy and applicability of evaluation results in complex mountain environments.

The invention belongs to the technical field of road surface detection, and relates to a multi-dimensional radar map construction method based on electromagnetic signals, which comprises the following steps: S1, scanning a target area through high-frequency three-dimensional ground penetrating radar equipment, acquiring electromagnetic reflection signals, and preprocessing the acquired signals; s2, converting the time domain data of the preprocessed electromagnetic reflection signal into spatial domain data, and generating a three-dimensional data model; s3, blank data in the three-dimensional data model are complemented through an interpolation method, and high-resolution three-dimensional grid data are generated; s4, extracting a disease area based on a reflection intensity threshold value and performing type identification; and S5, constructing a three-dimensional disease visualization model, and mapping disease characteristic parameters by adopting color coding. According to the method provided by the invention, the depth resolution and the spatial positioning precision of disease detection are improved, and the real distribution and form of the diseases in the pavement can be reflected more comprehensively.

The present invention discloses a space-time two-dimensional processing method for airborne radar based on linear frequency modulation (LFM) signals, which relates to the field of signal processing technology. A space-time clutter ring data model of the LFM signal is obtained based on the LFM echo signal. A space-time two-dimensional processing model based on the LFM signal is established based on a narrowband space-time two-dimensional processing (STAP) model. A space-time two-dimensional processing method based on the LFM signal is obtained through phase information compensation. The performance of the space-time two-dimensional clutter suppression improvement factor based on the LFM signal is analyzed, and an mDT processing method for LFM signals for practical engineering applications is provided. The present invention uses the above method to perform range phase compensation on the space-time two-dimensional processing model of the LFM signal and compensate for the coupled phase errors of platform motion and array element spacing to obtain a STAP processing method for the LFM signal. The implementation of the LFM signal under the fixed dimensionality reduction method (mDT) for space-time two-dimensional processing is derived and analyzed from the perspective of engineering application.

The invention discloses a data conversion and integration method and system, and the method comprises the following steps: 1, extracting product research and development data from an IPD system through a standard interface, wherein the product research and development data comprises a product structure, technological process design and technological parameters; 2, mapping the extracted product research and development data to a unified data model, wherein the unified data model is subjected to hierarchical structured storage according to the product, the working procedure, the working step and the technological parameters; 3, based on a preset mapping rule and a semantic conversion function, converting the unified data model data into standard process flow data which can be identified by an MES system; and 4, synchronously pushing the converted data to an MES system through an adaptive interface, and recording a data version and an operation log. Through the implementation of the invention, the data model is unified, IPD and MES data semantics are unified, the problems of system isolation and data obstruction are solved, and the automatic conversion rate of research and development data is remarkably improved.

The embodiment of the invention provides a modular building generation and optimization method and system based on a BIM graphic data model. The method is applied to the technical field of building information models and computer aided design, and comprises the following steps: acquiring spatial layout information of a modular building based on a building information model to obtain model data; converting the extracted BIM model data into a graph data model, and generating graph data containing space nodes and connecting edges; based on the optimization target, a multi-target optimization method is adopted to optimize the graphic data model, and a plurality of alternative design schemes are obtained; and scoring the alternative design schemes by adopting the fitness evaluation model, converting the design scheme with the highest score into an operable BIM format file, and outputting the operable BIM format file through the cloud data to complete the design process. Through deep fusion of the BIM and the graph data model, the dynamic optimization algorithm and the cloud collaboration technology, the technical problems that a three-dimensional modeling method is complex in process and insufficient in precision are solved.

The application relates to a map element data generation method, device, equipment, medium and program product, and relates to the technical field of map generation. The method comprises the following steps: acquiring at least one kind of map data of a target region; the map data comprises elevation data and image data; the elevation data corresponds to at least one kind of data model category; for the elevation data of the same data model category, the elevation data is divided into first-precision data and second-precision data, and the first-precision data and the second-precision data are fused in precision to obtain precision fusion data; the data precision of the first-precision data is higher than that of the second-precision data; perception semantic data of semantic objects in the target region is extracted from the image data; and map element data is generated according to the perception semantic data and the precision fusion data of each data model category. By using the method, the data quality and generation efficiency of the map element data can be improved.

The application provides a space-time model direct positioning method and system based on medium and low orbit satellite fusion, comprising: position rough measurement; constructing a direct positioning scene and a satellite receiving data model; constructing a space-time model of satellite receiving data; deriving a maximum likelihood estimator target function based on a least square estimation criterion; introducing an optimal weight vector, solving the weight vector according to a minimum variance distortionless response criterion, and deriving a target function based on the minimum variance distortionless criterion; drawing a space spectrum diagram according to the target function value, performing spectrum peak search, and determining the position of a ground radiation source. The application reduces the search range and the calculation amount by using the rough estimation result of single satellite direction finding positioning to obtain the direct positioning area to be searched; the space-time direct positioning model based on the angle of arrival and the Doppler frequency shift is established by using Doppler information, high-precision positioning can be realized under low signal-to-noise ratio, and high resolution can still be realized when the ground radiation sources are very close.

A system and method includes identifying a first plurality of projection images of an object acquired by an imaging system, each of the first projection images associated with a respective one of a plurality of projection angles; reconstructing a three-dimensional image of the object based on the first projection image; forward-projecting the three-dimensional image at the plurality of projection angles to generate second projection images, each of the second projection images being associated with a respective one of the projection angles; determining a first CDF image for a first projection angle in the projection angles based on a first projection image in the first projection images and a second projection image in the second projection images; determining a pixel corresponding to the difference in the first CDF image; and combining the determined pixels with the first one of the first projection images to generate a first combined image.

The application specifically relates to a passive synthetic aperture sonar direction finding method based on variational message passing, and belongs to the technical field of signal processing. The application adopts a broken line model to fit a distorted array shape, and establishes an array receiving data model containing array shape disturbance, in view of the problems that a traditional algorithm can only process space-time coherent signals, is sensitive to array shape distortion, and has high operation complexity; a spatial domain super-complete dictionary is constructed to convert a direction finding problem into a sparse reconstruction problem, a layered probability model is established by using a Gaussian scale mixed model and is expressed as a factor graph; each parameter posterior probability is solved by using variational message passing iteration, high-dimensional matrix inversion is avoided, and angle fine estimation is realized by combining Laplace interpolation. The application can jointly estimate a signal source direction and array shape distortion parameters, keeps high precision in a random signal and distorted array shape environment, significantly reduces operation complexity, and is suitable for underwater passive synthetic aperture high-resolution direction finding engineering application.

The application relates to a power distribution network operation and industry expansion engineering multi-source business data fusion method and system, which comprises the following steps: S1: a unified data access and adaptation platform is constructed to realize full-coverage access of power distribution network operation and industry expansion engineering related data; S2: based on the accessed data, an enterprise-level master data management system covering the whole domain of power distribution network operation and industry expansion engineering is established; S3: a knowledge graph in the field of power distribution network operation and industry expansion engineering is constructed; S4: based on the knowledge graph in the field of power distribution network operation and industry expansion engineering, a whole-process digital process model of power distribution network operation and industry expansion engineering is constructed based on business process management technology, and intelligent management of the business process is realized; and S5: based on the knowledge graph in the field of power distribution network operation and industry expansion engineering, a time-space integrated data fusion framework is constructed, business data, geographic space information and time sequence information are deeply fused, and a four-dimensional data model is formed. The application realizes whole-process data fusion and cooperation of power distribution network operation and industry expansion engineering.