159 results about "Digital elevation model" patented technology

The application discloses a kind of unmanned vehicle multispectral remote sensing water fine classification extraction method, it is related to remote sensing image processing technical field, the joint feature matrix including spectral feature, gray texture feature and elevation difference feature is creatively constructed in the present application, effectively eliminates redundant interference information, provides high-quality input with very distinguishing degree for multilayer perception machine model.Simultaneously, illumination geometry and digital elevation model are deeply coupled in the feature construction process, not only can accurately identify and reverse inhibit the shadow pseudo water body feature projected by complex terrain or building, break through the failure limitation of traditional single elevation filtering in flat shadow area, but also cooperate with the standardization closed operation process based on morphological dilation and corrosion filtering, eliminate the small holes and jagged artifacts in prediction result, realize the high-fidelity restoration of water body boundary, so as to improve the classification accuracy of complex water body such as narrow river, fragmented pit pond and urban waterlogging.

The application discloses a lake expansion contribution decomposition calculation method, extracts lake area and reverses water quantity change through remote sensing image and digital elevation model, discriminates precipitation phase state by using a temperature threshold method, estimates ice and snow ablation amount by combining a degree-day factor method, and calculates total glacier runoff; a single-layer evaporation model is constructed, net radiation, sensible heat, latent heat and water body heat storage and other fluxes are calculated based on a lake surface energy balance equation, and daily lake surface evaporation is obtained; quantile mapping and Bayesian fusion are combined to correct lake surface precipitation; non-glacier runoff is calculated according to a lake water balance equation; the stable period and the expansion period are divided according to the lake area trend, the stable period hydrological mean value is taken as a benchmark to calculate the expansion period abnormal value, and finally, the expansion contribution of each hydrological factor is determined according to the proportion of the abnormal value in the total water quantity increment. Through the method, the contribution intensity of different driving factors is clear, scientific support is provided for simulating lake change and predicting evolution, and ecological protection and management strategies are more targeted.

The present application relates to power transmission channel monitoring technical field, specifically provide a kind of power transmission channel topographic risk assessment method and device, comprising: based on the single view complex image of ascending track and descending track SAR satellite covering power transmission channel area determines the gradient observed by satellite in ascending track and descending track direction;Extract the slope angle matrix and slope direction angle matrix of pixel point in digital elevation model covering power transmission channel area, and construct the projection matrix that will be mapped to radar line-of-sight direction under the motion of topographic coordinate system based on the slope angle matrix and slope direction angle matrix;Based on the gradient observed by satellite in ascending track and descending track direction and the projection matrix, determine the soil along slope sliding gradient and soil vertical settlement gradient covering the power transmission channel area;Based on the soil along slope sliding gradient and soil vertical settlement gradient covering the power transmission channel area, power transmission channel topographic risk assessment is carried out.The technical scheme provided by the present application can realize the fine classification of power transmission tower foundation risk.

This invention provides a method, system, and storage medium for calculating the tree felling range of a high-voltage overhead transmission line's diversion line. This method can more accurately adapt to the spatial morphology of the diversion line, integrate a digital elevation model to achieve terrain-adaptive clearance calculation, and take into account both the natural growth height of trees and the safety verification of tree fall. It relates to the field of power transmission technology. The calculation method includes: obtaining relevant basic parameters of the current diversion line in the overhead transmission line for calculating the tree felling range; constructing a three-dimensional spatial model of the current diversion line and generating discrete point cloud data of the current diversion line; calculating the spatial coordinates of the treetop at each sampling point; generating square cells centered on each sampling point to be felled and with the sampling interval as the side length; merging adjacent or overlapping cells to form a continuous felling area surface to obtain the current tree felling range of the diversion line.

This invention provides a single-unit, mobile concrete placement device and its placement method. The device uses multi-modal sensors at the front end to fuse environmental and trench data, and a control center's path tracking algorithm drives the chassis to automatically traverse the trench and avoid obstacles. During operation, visual monitoring of the material inlet status enables automatic stopping when material is insufficient; simultaneously, a digital elevation model of the trench bottom is generated to analyze the center coordinates and volume compensation deviation of uneven target areas. Based on the analyzed data, the control center dynamically adjusts the spatial yaw and pitch angles of the placement pipe through inverse kinematics calculations to align with potholes, and dynamically adjusts the opening size of the hopper's opening and closing plate in conjunction with vehicle speed for precise quantitative filling, while simultaneously adjusting the vibration frequency to prevent arching. Sensors at the rear of the device continuously evaluate the root mean square error of the paved road surface's smoothness, triggering closed-loop feedback compensation when the error exceeds the standard. Furthermore, the device supports edge-end data feedback and cloud-based model iterative training, continuously optimizing the placement strategy. This invention achieves unmanned and precise trench backfilling operations, saving materials and eliminating the need for manual secondary leveling.

The application provides a multi-dimension evaluation method for an interference scene, which solves the problems of evaluation hysteresis, improves the consistency of evaluation, solves the single dimension of evaluation and the lack of consideration of terrain in the evaluation of the interference scene; the position accessibility analysis of terrain perception of a propagation path between a signal simulation device and a target device is carried out based on a digital elevation model; the device behavior compliance analysis is carried out in four dimensions of time domain, space domain, frequency domain and energy domain; if there is a moving route, the route coverage and signal continuity analysis are carried out in combination with the analysis results of the former two; finally, the analysis results of the three dimensions are weighted and fused to calculate the scene comprehensive effectiveness score and map it to high, medium and low three levels of confidence. Through the construction of the multi-dimension collaborative pre-evaluation system, the scientific and quantitative pre-evaluation of the training scene planning scheme is realized, the planning quality and efficiency are effectively improved, and the risk of waste of training resources is reduced.

This invention relates to the field of remote sensing mapping technology, specifically to a method and system for reconstructing ecological restoration zones in national land space based on remote sensing mapping. The method includes: acquiring real-time meteorological data and real-time electrical data from a mapping drone, calculating the dynamic resonance boundary frequency of the mapping drone; acquiring high-frequency acceleration data along the Z-axis, performing frequency domain analysis with the dynamic resonance boundary frequency as the upper limit of integration, and extracting the intensity of physical disturbances; calculating the dynamic process noise covariance based on the intensity of physical disturbances, and updating it to the process noise covariance matrix of the navigation system; extracting exterior orientation elements using the navigation system and constructing a digital elevation model (DEM); extracting landform indicators using the DEM, thereby delineating ecological restoration zones and generating reconstruction instructions. This invention effectively eliminates airflow disturbances and improves the accuracy of terrain reconstruction under extreme conditions.

The application provides a forest and grassland fire early identification and positioning method based on infrared thermal imaging and visible light fusion, and belongs to the technical field of forest and grassland resource protection and ecological safety monitoring. The method comprises the following steps: synchronously collecting infrared and visible light images and recording the space-time information of a monitoring platform; performing pixel-level registration on the two images; extracting a thermal anomaly suspected area from the infrared image based on a dynamic background temperature field, and extracting a smoke suspected area from the visible light image based on color, texture and motion features; performing spatial correlation analysis on the suspected areas extracted from the two channels, and combining the area growth rate and temperature rise rate of continuous multiple frames to construct a fire evolution model to confirm a fire point; calculating the three-dimensional geographic coordinates of the fire point based on the photogrammetry collinear equation and a digital elevation model; and generating and outputting alarm information containing the three-dimensional coordinates and fire intensity. The application realizes early and accurate identification and positioning of forest and grassland fires, and significantly reduces the false alarm rate.

This invention relates to the fields of wildfire monitoring, computer vision, and digital twin technology. It proposes a method and system for real-time wildfire spread simulation using digital twins and dynamic parameter inversion. The method dynamically inverts the surface combustible moisture content through white balance adaptive correction and HSV color feature extraction; maps physical camera parameters to a virtual camera; and uses a spatial ray casting algorithm and a digital elevation model to calculate the three-dimensional geographic coordinates of the fire point; it determines the wildfire spread direction by weighting the wind field vector and the maximum upslope vector in real time; it calculates the true slope of the dynamic path by taking points forward from the fire point as the starting point and using the grid accuracy of the digital elevation model as the step size; and it inputs the dynamic parameters into the wildfire spread model for simulation to generate the fire spread boundary. This invention significantly improves the physical realism and practical accuracy of wildfire spread simulation in complex environments through virtual-real fusion and physical correction mechanisms.

This invention discloses a GIS-based refined design method for blind drains, relating to the field of geotechnical engineering technology. The method includes the following steps: acquiring topographic data of the target area and constructing a Digital Elevation Model (DEM) based on the topographic data; performing hydrological analysis based on the DEM, extracting the gully network, and distinguishing between main gully lines and tributary gully lines; determining the blind drain layout scheme based on the gully network, where the main gully lines correspond to the locations of main blind drains and the tributary gully lines correspond to the locations of tributary blind drains; calculating the three-dimensional surface length of the blind drains along the actual terrain in the layout scheme based on the DEM; and performing engineering quantity statistics and output based on the three-dimensional surface length. This method deeply integrates the hydrological analysis module of a Geographic Information System (GIS) with blind drain engineering design, achieving automation and precision from gully identification to engineering quantity calculation.

The present application relates to a kind of single nozzle from plane to non-uniform slope surface water distribution conversion method, its method includes: based on the radial irrigation intensity of single nozzle in plane, establish single nozzle plane water distribution model, based on the digital elevation model of non-uniform slope surface, fit single nozzle radial direction non-uniform slope surface topographic curve, based on the water droplet motion trajectory model of passing through non-uniform slope surface certain point and non-uniform slope surface topographic curve, obtain the intersection of water droplet motion trajectory and plane passing through non-uniform slope surface certain point, according to single nozzle radial direction water conservation and non-uniform slope surface topographic curve, the irrigation intensity of intersection position corresponding single nozzle plane water distribution model is converted to the irrigation intensity of non-uniform slope surface certain point, can solve the problem that existing non-uniform slope surface water distribution conversion method cannot meet the need of non-uniform slope surface water distribution conversion, improve applicability, to simplify non-uniform slope surface water distribution measurement and be applied to hilly and mountainous water-saving irrigation.

The application discloses a large-size photovoltaic module hoisting path planning model construction method, and belongs to the technical field of photovoltaic module installation. The method comprises the following steps: acquiring high-precision three-dimensional point cloud data of a complex mountainous terrain, physical parameters of a large-size photovoltaic module and kinematic constraint parameters of a hoisting device; constructing a digital elevation model and superimposing the physical parameters of the module to generate a terrain passability cost map; defining a comprehensive optimization target comprising a total path duration, hoisting energy consumption, module attitude stability and spatial collision risk on the passability cost map; generating an initial collision-free path by using an improved heuristic search algorithm; establishing a multi-objective Pareto optimization model of the initial path, and jointly iteratively optimizing a spatial trajectory and a module attitude sequence in combination with the kinematic constraint parameters of the hoisting device to output an optimal hoisting path planning model.

The present application relates to photovoltaic planning technical field, especially to a kind of solar radiation resource evaluation method for photovoltaic power station.The method is first according to installed capacity target to determine ideal state laying area, and combined with the building coverage of target area and shading loss is modified, and delimitation redundant target area.Subsequently, candidate point is screened in area, using the energy efficiency evaluation index of expected radiation resource and three-dimensional topological grid line cost, point is divided into different spatial clustering cluster by clustering algorithm.Aiming at each cluster, the minimum circumscribed polygon area is fitted using the convex hull algorithm, and the site selection area set is formed.Further, the present application simulates dynamic shadow by digital elevation model and ray tracing algorithm, and calculates the actual radiation resource amount of each area;if the total resource amount does not meet the target, a multi-objective function is introduced for Pareto optimization iteration, and a matching solution is selected from the optimal solution set and the polygon boundary is adaptively adjusted until the demand is met.

The application discloses an infrared image adaptive atmospheric correction method and device based on a radiation transmission model, and belongs to the technical field of remote sensing image radiation correction. The method first extracts the spatial range, imaging time and observation geometry parameters of an image scene, constructs a scene-based atmospheric profile grid by distance inverse ratio weighted interpolation based on a reanalysis atmospheric profile, and combines a digital elevation model and a view zenith angle to correct and apply terrain and observation geometry constraints to generate control node input parameters. Then, the atmospheric radiation transmission model is called in batches to obtain the hyperspectral results of each control node, and the transmittance and path radiance parameters of the infrared target band are extracted by spectral response function convolution. Finally, the control node parameters are reprojected to the original image coordinates, the four-neighbor-domain bilinear interpolation and nine-neighbor-domain weighted interpolation results are adaptively fused for each pixel, the full-resolution atmospheric parameter field is recovered, and the observed radiance at the ground is inversed.

This invention discloses a mountain path planning method based on an improved A* algorithm, comprising: acquiring lidar or image data of the target area using a UAV and generating point cloud data to construct a digital elevation model containing elevation and slope information; subsequently, performing coordinate unification, noise reduction, and downsampling processing on the point cloud data, and combining the start and end points for region clipping and rasterization to construct a local raster map; employing the improved A* algorithm during path search, introducing a slope correction mechanism and an equivalent distance cost model, comprehensively incorporating distance, slope, and elevation factors into the path cost function, and dynamically adjusting the path cost based on the slope influence coefficient, while simultaneously constraining high-slope and impassable areas. This method can effectively reduce the search space and computational complexity, improve the efficiency and accuracy of path planning in complex mountainous environments, and is applicable to scenarios such as power transmission line planning and mountain engineering path design.

This disclosure relates to the field of remote sensing and mapping technology, and provides an adaptive distributed scatterer interferometry method, apparatus, and medium for mountainous areas. The method includes: acquiring radar image data and digital elevation model (DEM) data of the target monitoring mountainous area; calculating the radar vegetation index of each pixel in the dual-polarization synthetic aperture radar (DAP) image sequence and classifying it into multiple vegetation coverage levels to obtain a vegetation coverage grading atlas; identifying statistically homogeneous pixels in each image scene under the spatial constraints of vegetation coverage levels according to the grading atlas to determine a candidate set of distributed scatterers; further, using the grading atlas, performing adaptive coherence threshold filtering on each candidate point to obtain multiple distributed scatterers; and determining the long-term surface deformation results of the mountainous area based on the multiple distributed scatterers, the DAP image sequence, and the DEM data. This embodiment effectively improves the accuracy and reliability of distributed scatterer extraction and is suitable for deformation monitoring in complex mountainous areas.

The application discloses a remote sensing image change detection method, system, device, medium and product based on a multi-task deep learning network model, relates to the field of remote sensing image processing, and comprises the following steps: acquiring double-time multi-source space data of a target area; the double-time multi-source space data comprises double-time optical images, double-time SAR images and a double-time digital elevation model; dividing the target area into multiple height levels according to the double-time digital elevation model and generating a height coding map; based on the double-time multi-source space data and the height coding map, a pre-trained multi-task deep learning network model is used to output a change detection map, a change type map and a height change map, so that remote sensing image change detection is realized; the multi-task deep learning network model comprises an encoder, an alignment and fusion module, a four-dimensional neighborhood difference convolution module and a stereo gradient enhancement decoder. The application can realize high-precision and quantifiable remote sensing image change detection in a stereo scene.

This invention discloses a remote sensing classification method and device for periglacial landforms. The method includes: establishing remote sensing classification rules for periglacial landforms, dividing periglacial landforms into primary and secondary periglacial landform types; collecting remote sensing images and digital elevation model data of the target area in permafrost regions at various resolutions, and performing radiometric calibration and atmospheric correction on the remote sensing images; performing first-scale segmentation and second-scale segmentation on the processed data to generate two-level image object layers, with the first-scale segmentation generating a primary image object layer corresponding to the primary periglacial landform type and the second-scale segmentation generating a secondary image object layer corresponding to the secondary periglacial landform type; extracting and analyzing features for each image object in the primary and secondary image object layers; and, based on the remote sensing classification rules for periglacial landforms, classifying the image objects in the primary and secondary image object layers into the corresponding primary and secondary periglacial landform types, respectively, and outputting a remote sensing classification map of periglacial landforms.

The application discloses a landslide susceptibility prediction method combining terrain combined features and partition explainable analysis, and relates to the technical field of geological disaster evaluation. Slope, plane curvature and profile curvature factors are extracted from a digital elevation model of a research area, and after standardization, Gaussian mixture model is used for unsupervised clustering. The class labels obtained by clustering are taken as terrain combined features and are coded, and are combined with landslide influence factors to form an input feature set. The input feature set is input into an XGBoost model for training and the hyperparameters are optimized through grid search. Based on the trained model, the SHAP method is used to calculate the global feature contribution degree, and the contribution degrees of various factors are calculated according to terrain combination types, and the spatial differences of the factors under different terrain units are analyzed. The terrain types obtained by clustering are used as explicit features to participate in model training, and the spatial heterogeneity of the factors is revealed through grouped contribution degree analysis, which provides a new technical means for landslide susceptibility evaluation.

The present application relates to the technical field of remote sensing information extraction and snow monitoring, and particularly relates to a sub-pixel snow mapping method based on medium-resolution remote sensing data, comprising the following steps: obtaining medium-resolution remote sensing images, a digital elevation model, and ground meteorological station snow observation data, and preprocessing the remote sensing images to obtain surface reflectivity; identifying cloud-covered pixels, filling in the cloud-free dataset by temporal and spatial interpolation and ground object spectral similarity matching; selecting snow, vegetation, and water as spectral endmembers and extracting features; constructing a linear mixing model, and using the least square method to retrieve the snow proportion in the pixel to obtain preliminary data; and generating a high temporal and spatial accuracy snow distribution map through meteorological station data verification, digital elevation model terrain correction, and model parameter optimization, which solves the problems of mixed pixels, cloud coverage, terrain errors, and the lack of accuracy verification.

This invention discloses a fully automated atmospheric and topographic radiometric correction method and device for high-resolution remote sensing imagery, belonging to the field of remote sensing science and technology. The method includes: constructing a fully automated batch processing framework; developing an atmospheric correction module based on the 6S radiative transfer model to automatically retrieve atmospheric parameters and eliminate their influence; and developing a topographic radiometric correction module based on the digital elevation model (DEM) and VECA model to compensate for radiometric distortion caused by complex terrain. The key innovation lies in constructing a joint correction framework and integrating a geomorphic feature recognition algorithm, which can automatically identify and select to execute either single atmospheric correction or a combined atmospheric-topographic correction process based on the degree of topographic relief in the image. This invention achieves fully automated batch processing from data input to result output, requiring no manual intervention, significantly improving the processing efficiency, intelligence level, and adaptability to different terrain scenarios in high-resolution image radiometric correction.

The application discloses a kind of sand dust particulate matter three-dimensional visualization forecasting method and related device, belong to atmospheric environment forecast and three-dimensional visualization technical field, method includes: extracting particulate matter concentration data and model height data from atmospheric pollutant concentration forecast model;High-resolution digital elevation model data is obtained and matched with model grid, and real terrain height is obtained;Particulate matter concentration data is interpolated based on real terrain height, generates three-dimensional concentration distribution data and carries out three-dimensional rendering display;According to receptor point position extraction particulate matter concentration data, when exceeding threshold, push risk prompt information.The application improves the real sense and interactivity of particulate matter concentration spatial distribution by fusing high-precision terrain data and three-dimensional visualization technology, and realizes the closed loop from visualization display to business early warning by combining with automatic risk early warning, improves the response timeliness of sand weather environment management.

The present application relates to the technical field of image enhancement, in particular to a remote sensing image enhancement method for forest fire monitoring, which specifically comprises the following steps: firstly, pre-processing multispectral images, digital elevation models and fire point labels to obtain multi-source training samples; then, performing differentiated enhancement on different bands in combination with terrain shadow intensity, normalized burning ratio and short-wave infrared local anomaly response; then, generating a spatially restricted fire line expansion area based on wind direction, slope direction and vegetation conditions, and performing thermal radiation enhancement and smoke plume shielding modulation to obtain physically simulated augmented samples; finally, constructing a double-branch dynamic receptive field network for decoupling fire points and smoke, and jointly training the network using focal loss and boundary consistency loss, and outputting a pixel-level fire danger probability map. The present application can improve the detection accuracy of forest fires under complex terrain and the enhanced results can be directly used for fire point detection or auxiliary manual interpretation.

The present application provides a kind of open-pit mine step line high-precision extraction method, device and electronic equipment, wherein the method comprises: using Gaussian filter and bilateral filter to carry out denoising processing to the target model of open-pit mine;The target model includes digital surface model, digital elevation model;The second derivative of the target model after denoising is calculated, and the initial discrete points of step line are extracted based on the second derivative;The initial discrete points of step line are corrected, and the step line discrete points obtained by correction are split to obtain the step line discrete point set of different height steps;Each step line discrete point in the step line discrete point set is sorted and smoothed, and the target step line is connected to obtain. By the present application, the open-pit mine step line is extracted with high precision and automation, and the problem of weak anti-interference ability and low extraction precision in the existing related technology is solved.

The present disclosure relates to a method, device, electronic equipment and storage medium for digital terrain model data, the method comprising: obtaining digital elevation model data in a target operation area; generating the digital elevation model data into target digital elevation model data with multiple resolutions; obtaining target terrain factors of the target digital elevation model data at different resolutions; and obtaining digital terrain model data with multiple resolutions based on the target digital elevation model data and the target terrain factors. Since the embodiments of the present disclosure can generate digital terrain model data containing target terrain factors and having multiple resolutions, the safety and efficiency of driving can be greatly improved when an unmanned vehicle operates in a target operation area based on a map containing the digital terrain model data.

The application discloses a kind of wind farm transport road automatic line selection method based on digital elevation.The steps include: S1, obtaining the vector data of wind field range and ground object distribution, as design limit area and obstacle respectively;S2, obtain DEM data and carry out slope analysis, and determine the slope limit area as the slope limit area;S3, determine the avoidance condition by comprehensively considering the above conditions, discretize the wind field range into grid units and calculate the passing cost of each unit, and use A* algorithm to search the optimal path from the starting point to the end point with the minimum total road construction cost as the target;S4, take the wind turbine point as the starting point, connect the existing road network as the target, and generate a new road line selection scheme based on the optimal path.The application realizes automatic line selection of wind farm road by integrating digital elevation model and intelligent algorithm, can accurately avoid unfavorable terrain and optimize construction cost, thereby improving design efficiency, engineering safety and economy.

This invention discloses a coupled simulation and prediction system for regional water and carbon cycle processes, relating to the field of watershed carbon cycle simulation. The system includes a data acquisition module that determines the watershed extent and identifies riverbank areas within a unified grid system. Simultaneously, vegetation type and soil organic carbon are mapped to riverbank grid cells, consistently expressing the spatial location of carbon sources in relation to hydrological watershed migration. This facilitates subsequent clarification of carbon source distribution. Based on a DEM (Digital Elevation Model), flow direction and confluence paths are constructed. Runoff in each grid is calculated under meteorological conditions and gradually converges into the river channel, establishing hydrodynamic transport paths with clear upstream and downstream relationships. This provides a physical carrier for carbon transport. Based on soil organic carbon and vegetation type in the riverbank grids, the system quantifies the differences in carbon supply capacity of different riverbank areas during regional water migration. Riverbank carbon sources are traced along the confluence paths. Spatial weights are constructed using distance attenuation and connectivity, mapping carbon sources to each grid cell. Carbon flux is then coupled with runoff to calculate and accumulate through gradual transport.

The application discloses a reconfigurable ground-based MIMO three-dimensional deformation interferometric radar system and method, relates to the field of ground-based synthetic aperture radar interferometry, and comprises a radar host module, an electromechanical reconfigurable extension arm mechanism, a secondary rotating mechanism and an extended antenna unit. In view of physical space displacement errors introduced by mechanical reconfiguration, the host fixed array which is not affected by reconfiguration is taken as an absolute space reference, an error mapping model is constructed in combination with scene high-coherent point echo phases, mechanical tolerance phase errors are compensated in a signal processing domain through reverse inversion, after self-calibration, the system generates a three-dimensional digital elevation model in combination with multi-baseline fusion unwrapping, and finally calculates radar line-of-sight micro-deformation fields superimposed on three-dimensional space coordinates. The application has low cost, high tolerance and sub-millimeter three-dimensional monitoring precision, and is suitable for structural health monitoring of high and steep slopes, dams and buildings.

The present application relates to the field of geographic information system and geochemical exploration data processing technology, in particular to a geochemical anomaly spatial evaluation method based on geographic information system, comprising: obtaining a spatial node attribute database, digital elevation model data and multi-modal environmental attribute data of a target area; extracting slope gradient and water flow direction according to the digital elevation model data, establishing upstream and downstream catchment relationship, and constructing a directed acyclic spatial topology graph database; filtering chemical element concentration values in combination with environmental attributes and a preset characteristic background threshold value library to obtain effective anomaly nodes; performing reverse graph traversal on the effective anomaly nodes, combining characteristic attenuation coefficients and node catchment weights to obtain a source tracing characteristic distribution dataset; performing spatial clustering analysis on the dataset to generate a target spatial probability distribution model, and extracting a high-probability target area and a spatial coordinate set; the present application can realize anomaly migration and source tracing, improve the positioning stability of deep ore source target areas and the hit rate of high exploration tests.

The present application introduces a kind of intelligent prediction method of coal mine water inflow quantity fusing multi-dimensional factors and deep time sequence model, it is related to wisdom mine and industrial big data analysis and prediction technical field, specific steps are: S100: the acquisition and feature engineering of multi-dimensional heterogeneous data;S200: data preprocessing and space-time alignment based on digital elevation model DEM;S300: feature dynamic weighted fusion based on gated attention mechanism;S400: water inflow quantity inference prediction based on deep time sequence model;S500: online closed-loop self-correction based on reinforcement learning.The present application compared with traditional single data source method, prediction accuracy is improved;Through digital elevation model, the space-time alignment relationship of surface water to downhole catchment point conduction is constructed, the prediction result is more in line with objective law;The unique reinforcement learning self-correction mechanism makes the model can learn and optimize independently according to real-time feedback, realizes the continuous evolution effect of more and more accurate, without manual intervention can adapt to the dynamic change of mine.