87 results about "Grid computation" patented technology

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

The invention discloses an urban water supply management data trend analysis method based on space-time analysis, and relates to the field of data processing, and the method comprises the steps: collecting data in real time through an urban water supply pipe network sensor network, building a space-time unified coordinate system, building a space-time Kriging interpolation model based on pipe network topology, and achieving the space-time alignment of multi-source data; dividing an adaptive space-time grid by using a Voronoi diagram and a sliding window mechanism, and calculating multi-dimensional features; constructing a dynamic space-time diagram by taking a grid as a node, performing multi-step prediction in combination with a space-time diagram convolution circulation network, fusing a Kriging interpolation result, and evaluating an abnormal probability and a confidence interval through a Bayesian neural network; a monitoring layer, a prediction layer and a risk layer are overlaid in a three-dimensional GIS, a dynamic thermodynamic diagram is generated, an early warning path is optimized based on a Dijkstra algorithm, and a minimum risk topology path is output. The method has the advantages that through space-time analysis and accurate prediction, the intelligence, stability and emergency response efficiency of urban water supply management are remarkably improved, and powerful support is provided for smart city construction.

The invention relates to the technical field of soil erosion monitoring, in particular to a shallow mountain belt abrupt slope shrub land soil erosion monitoring method and system, and the method comprises the following steps: S1, collecting topographic point cloud data and vegetation reflectivity data; s2, spatial interpolation is carried out on the terrain point cloud data to generate three-dimensional terrain grid data, and meanwhile, boundary coordinates of a shrub coverage area are taken; s3, calculating a root system corrosion resistance strength value of each grid; s4, generating a real-time erosivity index of each grid; s5, extracting a real-time erosivity index of the grid where the corresponding node is located and a terrain parameter of the associated grid; and S6, calculating the soil erosion amount grid by grid, and generating a three-dimensional erosion space distribution diagram. According to the invention, through integration of multi-source data acquisition, real-time data processing and three-dimensional visual monitoring, accurate evaluation and dynamic early warning of the soil erosion process of the shrub forest land with the abrupt slope in the shallow mountain are realized, so that decision support is provided for water and soil conservation and ecological restoration.

A digital twin-based intelligent slope monitoring method, system, and storage medium are provided. The method includes obtaining point cloud data of a surface of a slope, creating a digital twin model; dividing the digital twin model to generate a plurality of first grids, calculating a displacement change value of each first grid during a target duration; defining the first grid with a displacement change value greater than a first threshold as a first region, dividing the target duration into a plurality of first durations with different lengths; setting a plurality of rainfall patterns, determining an optimal pattern for each first duration, calculating representative rainfall, constructing a prediction model, predicting representative rainfall for a future duration based on the optimal pattern and the representative rainfall of the first duration; generating a safety factor of the first region during the future duration based on the representative rainfall and a pore water pressure.

The invention belongs to the technical field of traffic control systems of aircrafts in a low-altitude airspace, and particularly relates to a grid division method and a grid division system for the low-altitude airspace. Dividing a low-altitude airspace by using grid units of different levels in the grid division method; and when the airspace in the current grid unit meets the splitting condition, splitting the airspace in the grid unit to the next level of grid unit, thereby performing more refined operation management. And when the airspace in the current grid unit meets the merging condition, the grid unit and the adjacent grid units with the same level are merged into the grid unit of the upper level, so that the calculation of the airspace grid is simplified, and the management efficiency is improved. According to the method, elastic features are given to the grids through splitting and merging of the grids, and a grid dynamic recombination mechanism is constructed, so that the refinement degree and the calculation efficiency of airspace management are balanced, the utilization rate of the airspace is improved, and the calculation complexity of conflict warning and conflict resolution strategies is reduced.

The invention discloses a digital rock elasticity modulus calculation method based on multi-scale data fusion. The method comprises the following steps: establishing a three-dimensional digital rock model; establishing a two-dimensional digital rock model; counting pore characteristics of each phase in the three-dimensional digital rock model and the two-dimensional digital rock model; calculating the equivalent elastic modulus of each phase in the three-dimensional digital rock model and the two-dimensional digital rock model; establishing a three-dimensional digital rock grid; and calculating the elastic modulus of the three-dimensional digital rock. A three-dimensional digital rock model and a two-dimensional digital rock model are established by adopting CT scanning and SEM scanning, a nano-resolution characterization method is combined, a multi-scale pore space and complex mineral components are characterized, and the pore characteristics of each mineral phase are accurately extracted. The digital rock elastic modulus calculation method based on multi-scale data fusion has the advantages that the microstructure of pores of the rock can be reflected more accurately, and the precision of digital rock elastic modulus numerical simulation is greatly improved.

The invention discloses a flow field pressure gradient prediction method based on a graph attention network guided by a physical operator, and aims to rapidly and accurately predict the gradient distribution of a flow field. According to the method, a grid computational domain of computational fluid dynamics (CFD) is expressed as a graph structure, a graph neural network is adopted to carry out feature learning on grid nodes and adjacency relations, and a physical operator (such as a fluid control equation difference operator) is introduced in a model training process to carry out guide constraint on the network. Through the above technical scheme, the method can greatly improve the efficiency of flow field gradient prediction on the premise of ensuring the prediction precision and physical consistency, has the advantages of fast model calculation speed, strong adaptability to complex boundary conditions, and the prediction result meets the law of conservation of fluid mechanics, and is suitable for popularization and application. The method can be used for rapidly predicting the flow field gradient in the fields of aerospace fluid simulation, wind engineering and the like.

The invention discloses an ore body three-dimensional modeling method and device, and relates to the technical field of three-dimensional modeling. The method includes the following steps that geometric feature parameters of an ore body to be monitored are obtained, a three-dimensional boundary model is constructed, and the surface is divided into a plurality of equal-size grids; collecting point cloud data of the topographic surface of the ore body, mapping the point cloud data into a grid, analyzing the point cloud data through different modeling methods, generating a plurality of three-dimensional ore body structure models, and preferably forming a model set; coupling and analyzing the structural complexity, and screening out an information comparison grid; calculating accumulated differences between the point cloud surface features and the model features, and selecting the model with the minimum accumulated difference as a target ore body three-dimensional model; in combination with real-time mining position information, a construction influence range is determined as a monitoring area, the local structure of the target ore body model is dynamically updated by obtaining vibration information and area point cloud data of the monitoring area, the targets of real-time monitoring and dynamic management of the ore body are achieved, and mining safety and efficiency are improved.

Provided are a task processing method and apparatus, which relate to the technical field of computers, and can quickly process a grid computing task and thus improve the task processing efficiency. The method comprises: acquiring a grid computing task in an application, wherein the grid computing task comprises a plurality of sub-tasks, and the dependency relationship between the plurality of sub-tasks conforms to a dependency rule; analyzing the dependency relationship between a first sub-task and other sub-tasks among the plurality of sub-tasks, and determining the dependency rule; analyzing the dependency relationship between the other sub-tasks among the plurality of sub-tasks according to the dependency rule; and on the basis of the dependency relationship between the plurality of sub-tasks, allocating computing resources to the plurality of sub-tasks, and executing the plurality of sub-tasks.

The invention relates to the technical field of volume measurement, in particular to a volume change measurement method, a medium and equipment based on block network construction. And then, in order to ensure that the volume value calculated by combining the mesh grids constructed by the blocked point cloud is consistent with the volume value calculated by constructing the mesh grids at one time without blocking, interpolation is carried out at the inner boundaries of the blocks so as to ensure that the meshes constructed by the blocks are seamlessly fitted. Respectively calculating corresponding volume values according to the mesh grids in different periods, and inputting a plane range and a starting value z value when the volume is calculated; and finally, subtracting the volumes of the two different periods, and calculating the volume variation. According to the method, the efficiency of large-scale point cloud volume calculation is improved, the problems of cracks, holes, overlapping and the like of the mesh grids among the point cloud blocks are solved by the algorithm for constructing the mesh grids, and the precision of a volume calculation result is ensured.

The invention provides an adaptive grid generation method and system based on reinforcement learning, and belongs to the field of computer graphics and computational geometry, and the method comprises the steps: S1, according to the input of a known model, constructing a background grid, calculating the curvature characteristics and proximity characteristics of the known model, and generating a corresponding size field; s2, inputting a to-be-predicted unknown model into the information transfer neural network, and predicting to obtain a discrete size field of the unknown model; carrying out interpolation processing on the discrete size field to obtain a continuous size field of the unknown model; and S3, according to the continuous size field and the known model, introducing reinforcement learning, using a leading-edge propulsion method to generate an adaptive grid as a training data set for training the supervised training network, and generating an adaptive grid of an unknown model through the leading-edge propulsion method. On the premise of ensuring the rationality and geometric quality of the grid topological structure, the method remarkably improves the grid precision and overall generalization ability of the key area, and has a wide application prospect.

The invention discloses an unmanned aerial vehicle group collaborative path planning method and system, a product and a medium, and relates to the field of non-electrical variable control or adjustment systems.The method comprises the steps that environmental data such as terrain height, obstacle distribution and dynamic targets in an unmanned aerial vehicle detection range are collected and converted into a grid unit space occupation state, a search space is divided into three-dimensional grids, and the three-dimensional grids are divided into three-dimensional data; and calculating an unexplored probability value of each unit, extracting time dimension change data of the value and gradient information between the units, identifying an environment dynamic change area, determining boundary features and generating path node data. Node data is compressed into lightweight path information containing coordinates, priority and time sequence constraints, and a track sequence is generated and distributed by combining the position of the unmanned aerial vehicle. By implementing the method, the detection efficiency of the unmanned aerial vehicle can be improved.

The invention discloses a community life circle delimiting method and device, equipment and a medium, and relates to the field of life circle planning, and the method comprises the steps: generating corresponding road meshes through linear ground features in a target area, and merging residential lands in the range of the road meshes to generate a residential area; constructing a hexagonal grid corresponding to the target area, and extracting the hexagonal grid to obtain a walking reachable grid; calculating a target growth origin based on the residential area and the walking reachable grid, and taking the target growth origin as a starting point to construct a target growth range so as to generate a corresponding hexagonal grid region, and obtaining a life circle initial range; and integrating the initial range of the life circle to obtain an integrated life circle, and carrying out structural division on the integrated life circle according to the activity intensity of the crowd to obtain community life circles containing areas with different densities. It can be seen from the above that the multi-source data is utilized in the method, and accurate demarcation and multi-dimensional evaluation of the community life circle of the whole province and city and other large areas are achieved.

This non-destructive inspection apparatus for inspecting the state of a pipe including a bending part comprises: a guided wave sensor which includes a plurality of elements capable of propagating guided waves through the pipe and receiving reflected waves of the guided waves; and an analysis device which analyzes a defect of the pipe on the basis of the reflected waves. The analysis device comprises: a grid creation unit for creating virtual grids including a plurality of grids by dividing the pipe along the axial direction and the circumferential direction; a propagation path calculation unit for calculating, on the basis of the virtual grids, a propagation path in which the guided waves are propagated through the pipe; a delay time calculation unit for calculating, for each of the plurality of elements, a delay time of the timing at which a reflected wave is received; a synthesis wave generation unit for generating a synthesis wave by correcting, on the basis of the delay time and the propagation path, the reflected waves received by each of the plurality of elements, and synthesizing the reflected waves; and an image generation unit for generating an image on the basis of the synthesis wave.

In order to solve the problems that feature points are difficult to extract and the extracted feature points are non-uniform in distribution when a fixed threshold value is used in a low-illumination scene in an ORB algorithm, the invention provides a self-adaptive balanced visual feature matching method for an unmanned aerial vehicle in a dark illumination scene. The method comprises the following steps: firstly, converting an original image into a grey-scale map, removing noise influence through Gaussian filtering, and carrying out image enhancement by using adaptive gamma correction and an unsharpened mask; secondly, dividing the image into grids with uniform sizes, calculating adaptive threshold values of the grids, and carrying out feature point extraction on the image; then, performing homogenization processing on the feature points in each grid by using quadtree decomposition, setting the maximum division depth of a quadtree to remove aggregated feature points, and calculating a local adaptive threshold for nodes with insufficient feature points to re-extract the feature points; and finally, accelerating the matching process by using the position information of the matching point pairs. According to the invention, the matching number of feature points in a dark illumination scene is effectively increased, and the distribution of the feature points is more uniform.

The invention discloses a three-stranded-wire electromagnetic pulse coupling response modeling and simulation analysis method, and relates to the technical field of transmission line simulation in an electromagnetic environment, and the method comprises the steps: building a three-stranded-wire-based parameter and a corresponding three-stranded-wire three-dimensional structure model; obtaining three-stranded wire attribute parameters and an application scene to construct a cable library model; determining a use scene, an erection condition and a position coordinate of the three-stranded wire; forming a stranded wire laying path according to the position coordinates of the three stranded wires and the erection conditions; obtaining electromagnetic environment related parameters required by simulation; setting model ground attributes and boundary conditions according to the environmental parameters; setting an excitation source input form, a pulse propagation direction and an electric field direction in electromagnetic simulation software according to the electromagnetic pulse parameters; completing three-dimensional modeling of the three-stranded wire according to the parameters; designing an equivalent circuit according to the twisted wire model schematic diagram, and arranging terminal pin positions; setting an equivalent circuit grounding mode and a load; three-dimensional model grid division is completed, and grid calculation solving requirements are met; a transient simulation task is established, a simulation frequency range is determined, and a solving mode is field-circuit co-simulation; simulation parameters are set, a stranded wire coupling simulation result is obtained by changing parameter variables in the joint simulation model and detecting electric signals at the load end of the model, and the parameter change influence condition is analyzed according to the coupling change rule.

A system and method for normal and mesh detail separation for photometric tangent map creation is provided. The system acquires a base three-dimensional (3D) mesh of an object and a photometric surface normal corresponding to the object. The system computes a mesh density map based on the base 3D mesh and a base normal map based on vertex normal information included in the base 3D mesh. The system determines a correction on the photometric surface normal based on the base normal map and the mesh density map. The system generates a corrected photometric surface normal based on an application of the correction.

This application provides a method and related equipment for preprocessing game trajectory data. The method includes: converting game trajectory data into a first grid sequence; merging high-frequency adjacent grids in the first grid sequence to calculate a second grid sequence; extracting embedding vectors from the second grid sequence to calculate an embedding vector sequence; and using the embedding vector sequence as a training set input to a deep learning model. This application's embodiment, by converting game trajectory data into a first grid sequence, merging high-frequency adjacent grids in the first grid sequence, and then extracting embedding vectors from the second grid sequence, can capture the prior influence of environmental factors on trajectory distribution and the potential contextual semantic information in the trajectory, achieving effective compression of long trajectory data.

Embodiments of the present application disclose a reservoir over-standard flood inundation risk zoning method, device and equipment, by determining the reservoir siltation influence probability factor and the reservoir dam break influence probability factor under the siltation condition, the reservoir siltation influence probability factor and the reservoir dam break influence probability factor are used to calibrate the reservoir inundation comprehensive risk degree of siltation-dam break double influence probability under the over-standard flood condition, and the K-means clustering algorithm is used to cluster and analyze the reservoir inundation comprehensive risk degree of each grid calculation unit, and finally the flood risk grade is determined. The technical problem of low accuracy of prediction and zoning of flood inundation risk in the prior art for the reservoir area with high sediment concentration and weak dredging capacity is solved, and a scientific basis and certain technical support are provided for reservoir flood inundation risk assessment and disaster prevention and mitigation planning in high sediment concentration basin areas.

The present invention provides a prospecting prediction system based on multi-scale big data fusion, the system comprising: a geological big data management module and a big data mining and analysis module, respectively for managing and mining and analyzing geological, geophysical, geochemical, remote sensing, and mineral data; a multi-factor extraction module for extracting geological elements from the mining and analysis results output by the big data mining and analysis module; a multi-scale grid calculation module for segmenting and assigning values ​​to geological elements using multi-scale multi-factor grid technology; an intelligent prospecting prediction module for compiling result maps; an intelligent prospecting evaluation module for compiling optimal decision diagrams; a decision-making support module for generating prospecting result reports; and a prospecting scheduling and command module for synchronously updating data in the prospecting scheduling and command module. By integrating a basic prospecting and prediction data set, a knowledge base, a model base, and an algorithm base, the present invention enables flexible scheduling and convenient use of various data, knowledge, models, and algorithm tools.

The application belongs to the field of computational mechanics, and discloses a scale order reduction near-field finite element calculation acceleration method and implementation method for structure fracture analysis.The acceleration method comprises the following steps: firstly, geometric modeling is performed on a target structure; secondly, the split finite element is recorded as a fine scale element and constitutes a fine scale grid; thirdly, based on a spatial neighborhood relationship, the fine scale element is collected into a coarse scale element and constitutes a coarse scale grid; fourthly, an equivalent shape function of the coarse scale element is obtained; fifthly, the overall stiffness matrix and the load vector of the coarse scale grid are calculated; sixthly, the overall node displacement of the coarse scale and fine scale grid is solved; seventhly, it is judged whether the current loading step or time step reaches the maximum loading step or time step; if yes, the displacement nephogram and equivalent damage nephogram of the target structure are output; if not, the key state of all fine scale near-field elements is updated; and finally, the implementation method is that the acceleration method is taken as a core calculation module to be implemented in different scenes.The application significantly improves the calculation efficiency of near-field dynamics in large-scale simulation analysis.

The invention discloses a radar point cloud data processing method and device. The method is applied to an FPGA and comprises the steps that the grid address of a first grid is acquired, and radar point cloud data in the same grid belong to the same cluster; determining a data storage address corresponding to the first grid; acquiring grid data corresponding to the first grid from the data storage address corresponding to the first grid; under the condition that the first grid is determined to be the initial grid, grid data corresponding to a second grid is obtained from a data storage address of the second grid, and the second grid is a grid adjacent to the first grid; and when data storage addresses of other grids adjacent to the first grid are calculated, performing neighborhood analysis on the grid data corresponding to the first grid and the grid data corresponding to the second grid in parallel to determine whether the grid data corresponding to the first grid and the grid data corresponding to the second grid belong to the same cluster. According to the scheme provided by the embodiment of the invention, the processing efficiency of the radar point cloud data can be effectively improved.

The invention discloses a three-dimensional non-rigid image splicing method, system and equipment applied to the medical field and a storage medium, and the method comprises the steps: enabling a collected three-dimensional image to form a two-dimensional redundant data maximum value intensity projection drawing based on a reserved redundant depth, and carrying out the registration of the projection drawing through employing an FFD transformation model, performing pixel resampling on the two-dimensional redundant data maximum value intensity projection drawing according to the coordinate offset to obtain a deformation field; performing nonlinear fitting on all the obtained deformation fields by using a sigmoid function to obtain a fitted deformation field; applying the fitted deformation field to an originally acquired three-dimensional image to perform XY direction deformation, and completing deformation correction processing of the three-dimensional image in the XY direction; according to the method, a three-dimensional non-rigid image with data dislocation is obtained, Z-direction deformation is converted into a maximum similarity search problem, then the number of similar layers of a three-dimensional data block under each grid is calculated through grid division, and correction of the three-dimensional non-rigid image with data dislocation is achieved through fusion in a distance weighting mode. Compared with a current image splicing technology, the method has the advantages that the splicing precision and the splicing speed are considered at the same time, and TB-level data can be efficiently processed while micron-level three-dimensional non-rigid image deformation correction can be achieved.

The application discloses a kind of ore body three-dimensional modeling method and device, and the application relates to three-dimensional modeling technical field.The application includes the following steps: obtaining the geometric characteristic parameters of the ore body to be monitored, constructing a three-dimensional boundary model, and dividing the surface into several equal-sized grids;Collecting point cloud data of the ore body terrain surface and mapping it into the grid, analyzing the point cloud data by different modeling methods, generating multiple three-dimensional ore body structure models and optimizing the model set;Coupled analysis of its structure complexity, select information comparison grid;Calculate the cumulative difference between the point cloud surface features and the features of each model, and select the model with the smallest cumulative difference as the target ore body three-dimensional model;Determine the construction impact range as the monitoring area by combining real-time mining location information, obtain the vibration information and regional point cloud data of the monitoring area, dynamically update the local structure of the target ore body model, realize real-time monitoring and dynamic management of the ore body, and improve the safety and efficiency of mining.

The invention relates to the technical field of regional planning, in particular to a regional planning method based on grid calculation and multi-objective optimization. According to the method, the target area is recursively divided into the multi-level grid units, the unique space-time identifier is allocated, the static attribute data and the dynamic attribute data are stored, and data are provided for planning of the target area. Taking the processed dynamic attribute data and the processed static attribute data as full-amount input data, and inputting the full-amount input data into a multi-objective optimization model consisting of an economic benefit objective function, an ecological bearing capacity objective function, a traffic capacity objective function and a social satisfaction objective function; and carrying out optimization solution on the multi-objective optimization model by adopting an improved multi-objective optimization algorithm, and outputting a planning scheme of all grid units, thereby realizing accurate planning on target areas such as ports, cities, bases and the like.

The invention discloses a bow-shaped echo associated convection early warning method. The method comprises the following steps: receiving multi-dimensional weather forecast data input; calculating vertical shear rate data grid by grid by using a central difference method; analyzing the vertical shear rate data of each horizontal grid point, and detecting a vertical shear layer conforming to a condition by adopting a sliding window method; carrying out thermal parameter coupling and verification on the screened shear rate sequence; optimal window selection is carried out aiming at a plurality of shear rate sequences which possibly appear in each grid and meet conditions, and the sequence with the maximum product is selected as final output; and drawing the flow trigger intensity of the finally output shear sequence on a forecast reflectivity image in a scattered point manner. The method is realized based on mathematical module construction and method of theoretical innovation; a shear rate distribution normality test is introduced to eliminate an abnormal disturbance layer; the convection trigger potential is quantified in a physical quantity product form; and automatic layered feature identification of the three-dimensional meteorological field is realized.

The embodiment of the invention provides a life entity information detection method and device. The detection method comprises the following steps: dividing a space region covered by radar signals into a plurality of grid spaces; determining a radar signal of each spatial position in each grid space; for each grid space, calculating feature data of the radar signals in the grid space in the first time period, the feature data being a mean value of variations of the radar signals at all spatial positions in the grid space at each moment in the first time period; and inputting the feature data corresponding to all the grid spaces into a trained machine learning model to detect life body information. According to the embodiment of the invention, the radar coverage area is gridded, and the feature data is calculated and output for each grid, so that the good detection precision is ensured while various information of the life body is detected.

This method improves the accuracy of predicting the state of a coating film by considering the behavior of the solvent and particulate components during the drying process, targeting coating films containing particulate matter. [Solution] In a drying model, the steps include: dividing the computational domain into multiple computational grids; performing a calculation of the movement of particulate components; assuming that the solvent volatilizes from the top surface of the computational grid located in the outermost layer, and that the solvent concentration decreases as it moves from the substrate side to the surface layer computational grid; taking the diffusion coefficient of the solvent, the volatilization rate, and the interaction coefficient of each solvent in the mixed solvent as input information; calculating the volatilization flux using the diffusion coefficient of the solvent; and calculating the amount of volatilization using the product of the volatilization rate, the area of ​​the top surface of the computational grid located in the outermost layer, the solvent concentration, and the interaction coefficient of each solvent in the mixed solvent; and performing a calculation of the solvent diffusion state and the amount of volatilization.

The invention relates to a surface fracture development prediction method and device, a medium, equipment and a program product, and relates to the technical field of coal mining, and the method comprises the steps: carrying out the grid division of an overlying rock layer of a coal mining area in a horizontal direction and a vertical direction; sequentially determining the grid points meeting the ground fracture criterion in the grid points of each layer of grid along the vertical direction of grid division, and determining the grid point with the maximum mining-induced strain component in the grid points meeting the ground fracture criterion in each layer of grid; and under the condition of meeting a grid calculation termination condition, determining development information of the earth surface fracture according to the grid points meeting the earth fracture criterion and the grid point with the maximum mining-induced strain component in each layer of grid. According to the scheme, development prediction can be carried out on the surface cracks possibly generated by the overlying strata of the coal mining area on the basis of grid division, so that the accuracy of checking the surface cracks of the mining area is improved, and disaster prevention and control can be carried out in time.

The invention belongs to the technical field of potential earthquake risk prediction analysis, and discloses an earthquake risk analysis method considering historical earthquake energy release, which comprises the following steps: constructing a strain energy three-dimensional grid of a research area; calculating historical earthquake energy release and a release range; calculating accumulated strain energy of each grid; calculating residual strain energy and identifying a potential earthquake generation area; and earthquake risk analysis. According to the method, an original analysis method of a numerical simulation result is broken through, energy release of historical earthquakes and energy accumulation between earthquakes are considered from a new perspective and method, and a new thought for carrying out earthquake risk analysis based on the numerical simulation result is provided.