1051 results about "Grid based" patented technology

The invention relates to a quick river flood forecasting method based on a physical information neural network, and belongs to the field of river flood forecasting. The method comprises the following steps: on the basis of a traditional physical information neural network (PINN), introducing a boundary condition parameter as an input variable, and enabling the PINN to learn a flood wave propagation rule under different boundary conditions. Furthermore, on this basis, a physical information neural network flood fast forecasting framework (RFF-PINN) integrated with a hydrodynamic method is provided, a numerical solution based on grid discretization is reconstructed into a continuous function in a time-space domain through a piecewise polynomial interpolation method, residual error loss between network output and a hydrodynamic model simulation value is constructed, and therefore, a flood fast forecasting result is obtained. The network parameters are optimized in cooperation with the PDE loss, and the problem that the network parameter optimization effect is reduced due to the fact that the PDE loss of the complex flow state area is difficult to converge is solved. The method has the beneficial effect that the water depth change process of each section of the river channel under any boundary condition can be accurately and quickly predicted.

The invention discloses a curved surface quadrilateral dominant grid generation method, device and equipment for an aircraft and a storage medium, and relates to the technical field of computational fluid mechanics, and the method comprises the steps: creating a surface unstructured grid based on surface grid generation parameters of a CAD file of the aircraft, carrying out the conformal mapping of the surface unstructured grid to a parameter domain plane, and calculating the vertex compression ratio of each grid vertex; selecting the current starting point with the minimum compression ratio and the maximum to-be-compared vertex in the adjacency list, and determining the current to-be-processed vertex with the minimum compression ratio in the adjacent vertexes and the advancing direction; determining to-be-processed discrete points according to the current compression ratio and the coordinate information to generate a current isoline, if the current compression ratio does not exceed a threshold value, iteratively updating the current starting point, and skipping to the step of determining the current to-be-processed vertex again; the discrete points are projected to the outer-layer isolines according to the isoline sequence, and the curved-surface quadrilateral dominant grid is generated based on the distance proportion between each discrete point and the projection point, so that the generation efficiency of the curved-surface quadrilateral grid is improved.

The invention relates to the technical field of wind field simulation, and provides a wind field numerical simulation method based on multiple meteorological data sources. The objective of the invention is to solve the problems of large simulation error, rough terrain boundary processing and poor turbulence model parameter adaptability caused by non-uniform coverage of a single data source, insufficient precision and unscientific multi-source fusion. The method is characterized by comprising the following steps: step 1, constructing a CFD three-dimensional grid based on a geometric model of a target area; 2, collecting original data of a ground station, satellite remote sensing, numerical forecasting and the like; 3, performing standardized preprocessing (abnormal value elimination, missing interpolation, radiation / geometric correction and resampling), determining a multi-source fusion weight by combining historical data analysis, and generating comprehensive meteorological data by adopting a weighted average method; and 4, inputting the comprehensive data into a CFD-RANS model, dynamically adjusting turbulence parameters, accurately setting terrain boundary conditions, and obtaining a wind field space-time distribution result through numerical solution. According to the invention, through combination of multi-source data fusion and CFD simulation, the wind field simulation precision and stability are improved.

The invention relates to the technical field of water conservancy management, and discloses a water conservancy dynamic decision-making method and system based on digital twinning and multi-source heterogeneous data, and the method comprises the steps: carrying out the real-time information capturing of a target water conservancy system, and generating a system operation information scheduling matrix based on a grid geographic model and a time dislocation mark; performing hierarchical slicing on the system operation information scheduling matrix according to a multi-scale time window to form a multi-channel flow framework of regional hydrological dynamic behaviors; analyzing the evolution trends of the water level, the flow and the water quality by using a multi-channel flowing framework and a dynamic fusion analysis operator; dividing a river reach, a reservoir and a regulation and control facility corresponding to the potential risk event as candidate scheduling areas; and based on the local risk coupling network, dynamically optimizing a scheduling strategy, a pump gate operation sequence and a data acquisition frequency, and generating a real-time scheduling and emergency response scheme of the candidate region. The method has the advantage of improving flood early warning accuracy and water supply scheduling efficiency.

The invention provides a remote sensing-based land utilization carbon emission evaluation method, device and equipment and a medium, and the method comprises the steps: carrying out the radiometric calibration and spatial registration of obtained multi-source remote sensing data, and obtaining a standardized raster data set; generating a land utilization classification grid map based on the standardized grid data set; generating a land change vector layer through a continuous multi-stage land utilization classification grid map; generating a dynamic evaluation unit vector boundary according to the land utilization classification grid map and the land change vector layer; correcting a vegetation carbon absorption coefficient and an industrial emission coefficient in real time based on remote sensing inversion data, and constructing a spatial carbon transfer model; and inputting the land utilization classification grid map, the dynamic evaluation unit vector boundary and the spatial carbon transfer model into a layered mixed carbon emission evaluation model to obtain a carbon emission intensity distribution map. By adopting the scheme, the carbon emission under different land utilization modes can be accurately evaluated, and the scientificity and policy applicability of regional carbon balance evaluation are improved.

A dynamic prediction method for the residual gas content of a pre-extraction coal seam comprises the steps that on-site working conditions are considered, parameters such as gas content changes and related geological factors and extraction factors are collected, and a dynamic monitoring data set is constructed; screening main control factors based on grey relational degree, and determining the main control factors influencing the residual gas content after extraction; a main control factor of the residual gas content is used as an independent variable, a pre-pumping dynamic correction factor is combined, a dynamic prediction model is established, and actually measured data is adopted regularly to verify and optimize parameters of the dynamic prediction model; dividing a pre-extraction working face into uniform grid units, and calculating the residual gas content of each grid based on a dynamic prediction model; an extraction blind area is judged according to a quantitative standard and is visually presented; and formulating a differentiated drilling optimization scheme according to the blind area distribution. According to the method, the residual gas content prediction model dynamically responding to mining condition changes is constructed, extraction blind area prediction and drilling optimization are achieved, the coal seam gas extraction efficiency can be improved, and gas disasters are reduced.

The invention discloses a multi-microgrid system distributed optimization scheduling method based on an electric power-carbon market, and the method comprises the steps: constructing an energy consumption equipment model and a carbon quota transaction model based on the energy flow and carbon quota transaction process in a microgrid; a dynamic collaborative pricing model is constructed based on the power and carbon quota market supply-demand relationship; constructing an operation cost optimization model of a single micro-grid system based on the above models, and constructing a multi-micro-grid collaborative optimization scheduling problem with the goal of minimizing the total operation cost of all micro-grids based on a Nash bargaining game framework; and solving by adopting an accelerated prediction-correction alternating direction multiplier method algorithm to obtain an optimal scheduling scheme based on power-carbon market coupling, thereby realizing energy operation scheduling of the multi-microgrid. Through power-carbon market coupling, dynamic pricing, game theory optimization and an efficient distributed algorithm, the operation cost of the micro-grid system is reduced, and the reduction of the operation cost assists in improving the operation income of the micro-grid system.

A system for extracting a number of data elements from one or more data sources. A text representing tables using a markdown language is extracted from spreadsheets and or other grid-based documents. The text is provided to a language model with a prompt. The prompt may be a chain-of-thoughts prompt. The prompt includes several requests and / or steps that cause the language model to extract one or more tables from the spreadsheet and output the tables using the markdown language or a different markdown language. The tables extracted from the spreadsheet are converted into table chunks and indexed for retrieval by a retrieval augmented architecture. When a prompt to extract particular information from the spreadsheet is provided, one or more relevant table chunks are identified and provided to a language model for extraction. Using the language model to separate tables improves information extraction accuracy while maintaining downstream instructions.

The invention relates to an earthwork balance calculation method, system and device and a storage medium, and relates to the technical field of earthwork balance design. The method comprises the steps of performing fusion processing on oblique photography data and laser radar point cloud data to generate a live-action three-dimensional model; performing grid division on the live-action three-dimensional model to obtain a grid model; based on the gridding model, defining a decision variable set including the design elevation of each grid point, the overall slope of the site, the slope height of each slope unit and the earthwork allocation amount, and constructing a comprehensive objective function including an earthwork balance objective, an economical objective and a safety objective; and under the engineering constraint condition, performing multi-objective optimization solution on the comprehensive objective function to obtain a Pareto optimal solution set, and selecting a final implementation scheme from the Pareto optimal solution set. According to the method, the problem of topographic data missing of the dense vegetation region is effectively solved, the limitation of traditional single-target optimization is broken through, and the maximization of comprehensive benefits is realized.

The invention provides an orphan insurance policy customer historical information abstract processing method, and relates to the technical field of data processing, and the method comprises the steps: setting an insurance policy monitoring state flow control point if it is detected that an insurance policy state is changed into an orphan insurance policy; the process control point is located at an initial triggering node of policy state change, an instant node for confirming the orphan policy state and a starting node of the service handover process; based on matching analysis of the flow control points and the monitoring time sequence nodes, a geometric control area is obtained, and gridding segmentation is carried out on the geometric control area; obtaining a data collection adjustment value based on the distribution characteristics of the grids; performing optimization adjustment on the cross-source heterogeneous historical data according to the adjustment value; and based on the adjusted cross-source heterogeneous historical data, obtaining a customer interaction timeline through semantic alignment and time sequence reconstruction processing. According to the invention, customer active characteristics and service preferences can be quantified, and the service handover efficiency and customer service quality are improved.

The invention relates to a multi-scene facility site selection method based on a gridding population mapping and hybrid optimization algorithm, and the method comprises the following steps: S1, constructing regular rectangular grids covering a research area, each network having a unique grid identifier, a centroid abscissa and a centroid ordinate; s2, obtaining different forms of population data, performing conversion processing, integrating the population data into regular rectangular grids, and calculating the population quantity for each network to obtain a grid data set with standardized population weight; and S3, based on the data set and the coverage determination function, respectively constructing target functions of three scenes of full-facility re-optimization, partial-facility optimization and newly-added facility site selection, and solving the target functions to obtain optimal multi-scene facility site selection results of the three scenes. Compared with the prior art, the method has the advantages of improving the calculation efficiency of the optimal facility number range and the site selection position and the like.

The invention relates to the technical field of computer vision, in particular to a method for generating a blind person navigation obstacle avoidance map. The method comprises the following steps: driving a blind guiding robot to a preset inspection point, and collecting a surrounding environment image in real time; generating a three-dimensional point cloud according to the environment image, and constructing an environment map; extracting feature points based on the surrounding environment image, performing feature matching, and outputting a feature matching result; evaluating an inter-frame motion state by using a feature matching result; determining pose features of the blind guiding robot according to the inter-frame motion state; semantic segmentation is carried out by using the pose features, and an obstacle area is determined; acquiring an obstacle image of the obstacle area, and fusing the obstacle image with the surrounding environment image to generate an obstacle map; and constructing a dynamic occupancy grid based on the obstacle map. According to the invention, real-time updating and intelligent obstacle avoidance functions of the blind navigation map are realized based on the computer vision technology, and the navigation safety and the path planning accuracy are improved.

The invention relates to the technical field of operation machinery, and provides a topological optimization method applied to a suspension arm, the suspension arm, a hoisting arm frame device and a self-loading and self-unloading transport vehicle, and the method comprises the following steps: establishing an initial model of the suspension arm, dividing grids based on the initial model, and defining a design domain; applying constraint conditions to the initial model of the suspension arm in a corresponding design domain; determining a topological optimization method of the suspension arm according to the constraint conditions, and setting corresponding initial topological optimization parameters; based on the initial topological optimization parameters, sensitivity analysis and optimization iterative calculation are carried out on the topological optimization finite element model, and target topological optimization parameters are obtained; obtaining a model of the target suspension arm based on the target topological optimization parameters; and extracting the optimized density distribution for checking, and carrying out finite element analysis on the sealing distribution which does not meet the requirement again until a manufacturable geometric model is generated. On the premise that the mechanical property is guaranteed, the balance of light weight and high strength of the suspension arm can be achieved through topological optimization design.

The invention provides a physiological mechanism driving and data fusion method and system for sitting posture human body modeling, and relates to the technical field of digital twinning and biomechanics crossing. The method comprises the following steps: mapping human body macroscopic parameters into biomechanical attribute parameters; generating a basic three-dimensional human body grid based on the human body macroscopic parameters; generating a deformed three-dimensional human body grid in combination with the basic three-dimensional human body grid and the human body macroscopic parameters; solving an optimal attitude based on the vehicle geometric parameters, the task scene identifier and the biomechanical attribute parameters; finally, the deformed three-dimensional human body grid and the optimal posture are integrated, the high-fidelity sitting posture digital twinborn body is generated, end-to-end automatic modeling from macroscopic parameters to the digital twinborn body is achieved, and the core problems that the form and the posture are not matched, crowd coverage is insufficient and task adaptability is poor are solved.

The invention provides a bedding structure rock finite element model reconstruction method based on a rock core digital image, and belongs to the technical field of digital rock cores, and the method comprises the following steps: S1, obtaining a gray level image of a rock sample; s2, calculating a transverse mean value of the analysis area to obtain a longitudinal gray level distribution curve; s3, applying moving average filtering and smooth filtering to obtain a smooth gray curve; s4, first-order difference is carried out on the smooth gray level curve, the position with the absolute difference value larger than a threshold value is taken as an initial stripe boundary candidate, and starting and stopping pixels, the width and the average gray level of each stripe are determined; s5, mapping each clustering label interval into a physical interval based on FEM grid partition; and S6, constructing a sample finite element model, and generating a reconstructed finite element model with real partition information. According to the method, the macrostructure features of the rock can be efficiently recognized and extracted by directly utilizing the pictures and combining gray profile analysis, and efficient and low-cost reconstruction of the finite element model of the bedding structure rock is achieved.

The invention discloses a method for constructing an evaluation model for the influence of climate change on biodiversity, and particularly relates to the technical field of ecological modeling and climate response analysis. The method comprises the following steps: generating a high-resolution characteristic grid based on microclimate disturbance data and a remote sensing image, extracting ecological plaques and establishing a heterogeneity spatial index model, constructing a connectivity map and a coupling response path library, extracting a typical species response mode by using nonlinear dimension reduction and spectral clustering, and performing dynamic fitting in combination with biological survey data. And finally, generating a diversity attenuation trend prediction curve and a risk thermodynamic diagram, identifying a biodiversity collapse critical point and outputting an intervention priority, and the method can be widely applied to regional ecological early warning and protection planning.

The invention belongs to the technical field of engineering simulation data processing, and particularly discloses a finite element grid graph structure construction method and system, a terminal and a medium. Comprising the following steps: analyzing original full-amount grid data exported by finite element simulation, segmenting unstructured grid data into a grid vertex coordinate set and a grid unit mark number set, and constructing a graph edge topological structure corresponding to a grid based on a unit mark number relationship; on the basis, loading physical field data and adopting a tolerance-based coordinate matching algorithm to realize accurate mapping of physical field labels and material attributes with grid nodes; and generating standardized finite element grid graph data which can be directly used for graph neural network processing. By means of the method, high-consistency and high-physical-reliability conversion from the finite element simulation data to the graph structure data is achieved, and the physical field modeling and simulation acceleration capacity based on graph learning is improved.

A facial expression recognition method based on grid attention and pyramid segmentation attention belongs to the technical field of deep learning image processing and emotion calculation, and comprises the following steps: introducing a grid attention mechanism and a pyramid segmentation attention mechanism on a ResNet101 large model, capturing local expression detail features through a grid attention module, establishing multi-scale global feature association by using a pyramid segmentation attention mechanism; hierarchical segmentation is carried out on the backbone network, and information from multiple hierarchies is effectively fused; and dynamically balancing the contribution degree of each level of features through learnable parameters, and integrating the extracted features to judge the expression category. Experiments show that the model achieves the recognition accuracy superior to that of a traditional model on a public data set in natural scenes such as complex illumination and posture change. According to the method, a solution with high robustness is provided for facial expression recognition in a complex environment, and the method has important application value in the fields of intelligent human-computer interaction, mental health assessment and the like.

The invention discloses a fine-grained QoS isolation method and device for NVMe-oF storage, relates to the technical field of data transmission, and mainly aims to solve the problem of tail delay amplification caused by cross-tenant I / O interference in a multi-tenant environment. The method comprises the following steps: acquiring system telemetry data and a multi-tenant I / O request stream in a multi-tenant scene; performing micro-slice processing on the multi-tenant I / O request stream, and importing each obtained micro-slice into a corresponding virtual queue; determining a two-dimensional credit vector for controlling each virtual queue based on the system telemetry data; and on the basis of the two-dimensional credit vector of each virtual queue, performing scheduling and gating release on the micro-slices in each virtual queue on a preset time grid. According to the invention, the micro burst is effectively inhibited at the RNIC near end, the delay amplification path is cut off, the I / O tail delay is reduced, and the service quality predictability in the shared storage environment is improved.

The invention is suitable for the technical field of thunderstorm prediction, and provides a strong thunderstorm potential risk and intensity prediction method based on an artificial neural network, and the method comprises the steps: obtaining the ground-to-ground lightning data of a target region, determining the time distribution characteristics of a thunderstorm event, and recognizing the time valley of the thunderstorm event; collecting multi-source meteorological data in a target area, and screening meteorological prediction factor data; performing space-time alignment processing on the ground-to-ground lightning data and the meteorological prediction factor data, and constructing a grid unit day-by-day sample set based on the aligned data; constructing a probability classification model of a strong thunderstorm event based on the grid unit day-by-day sample set; building a regression neural network model based on the grid units which are judged to be strong thunderstorm high risks by a probability classification model; and a collaborative prediction result is output, a predicted value of a geometric mean value of the ground-to-ground flash frequency and the lightning current amplitude is synchronously output, and a risk assessment basis of classification discrimination and numerical prediction capability is provided for extreme weather early warning and power grid disaster prevention and reduction through double-order modeling.

The invention provides a matched tobacco appliance identification method and system based on a metal heating inductor, and belongs to the technical field of data identification. In the process of heating the metal heating inductor, a plurality of temperature points are set, real-time temperature parameters and electromagnetic parameters of the metal heating inductor are obtained, and a temperature-electromagnetic mapping table is established; constructing a three-dimensional parameter grid based on the electromagnetic parameters, performing mean division on the three-dimensional parameter grid to obtain a mean grid, and constructing a coupling change rate matrix according to the mean grid; performing eigenvalue decomposition on the parameter coupling change rate matrix to obtain a deformation eigenvector, and comparing the deformation eigenvector with a pre-stored appliance mode recognition vector to obtain a mode similarity score; acquiring an appliance judgment mode based on the mode similarity score, and executing a mode mechanism according to the appliance judgment mode; the interference of temperature drift on an identification result is reduced, the problem that a traditional identification mode depends on voltage, current and resistance value detection is solved, and the misjudgment probability is reduced.

The invention discloses an intelligent inspection method and system for a construction site, and belongs to the technical field of image processing. The method comprises the following steps: processing a remote sensing image of a construction site cement pavement, and positioning a pavement pixel area; calculating a relative difference value of each pixel point according to a pixel mean value of the region, and generating a difference value distribution image; and extracting a maximum value and a minimum value in each window region of the distribution image to respectively obtain a high-difference value compressed image and a low-difference value compressed image. Then, marking a non-pavement pixel region as an abnormal point, carrying out grid division on the two types of compressed images, calculating a difference characteristic value based on the abnormal point in a grid, and forming a high and low difference characteristic matrix; respectively calculating the joint deviation degree of each grid difference characteristic value to obtain a high joint deviation matrix and a low joint deviation matrix; and finally, processing the matrix through a pavement defect feature evaluation network, and outputting a pavement quality score. According to the invention, through multi-dimensional feature extraction and intelligent evaluation, the precision of pavement evaluation is effectively improved.

The invention provides a game rendering method and system capable of eliminating volume cloud and mist in real time and electronic equipment, and belongs to the technical field of game development. The method comprises the steps that a cloud and mist area is set, the set cloud and mist area is divided into a plurality of equal-size grids, and each grid stores an elimination state and an elimination progress value; dynamically updating vertex concentration textures; calculating and storing cloud and mist concentration values of vertexes around each grid based on the grid elimination progress; view cone optimization rendering: determining a visible cloud range, combining adjacent grids to be rendered into a rectangular region in a two-dimensional plane, expanding the rectangular region into a cube, and projecting the cube to a screen space to calculate a bounding box; and shader sampling: for pixels in the screen bounding box, calculating cloud transparency and color through ray stepping sampling. According to the method, through grid dynamic management, rendering range optimization and shader efficient sampling, low-consumption and real-time elimination high-quality volume cloud and mist rendering can be realized at a mobile terminal, and performance and game interaction experience are considered.

The invention relates to the technical field of automatic driving, in particular to a multi-modal three-dimensional target detection method, which comprises the following steps of: in a first stage, firstly acquiring neighbor depth information of point cloud to enhance image features, and then further enhancing image edges and reducing semantic confusion by utilizing wavelet transform; and then a cross attention mechanism is introduced to realize effective fusion of the enhanced image features and the point cloud, an initial region suggestion is obtained, and bounding box classification and prediction in the first stage are realized. And in the second stage, designing a double-attention module based on grid features to supplement more geometric detail information, acquiring more context information and position information by utilizing the initially suggested spatial features and channel features generated in the first stage, and then introducing a self-attention mechanism to dynamically distribute interaction weights of the grid features, so as to realize the self-attention interaction of the grid features. Rich context information is effectively captured, a local geometric structure is better coded, information loss is reduced, and the detection precision of the model is improved.

The invention provides a three-dimensional modeling method and device, electronic equipment and a storage medium. The method comprises the steps of obtaining multi-source data of a to-be-constructed model; dividing the initial grid based on the geometric feature density of the to-be-constructed model to obtain an initial grid frame of the to-be-constructed model; optimizing the grid density of the initial grid frame based on the curvatures of different positions of the to-be-constructed model; fusing the multi-source data to the optimized grid vertexes to obtain a grid model after each vertex is fused with the multi-source data; carrying out iterative optimization on a grid topological structure of the grid model; and outputting the three-dimensional model obtained by final iteration through a preset format. According to the invention, by dynamically adjusting the grid density and fusing the multi-source data, the precision and efficiency of three-dimensional modeling are improved.

The invention relates to the technical field of meteorological disaster early warning, and provides an urban waterlogging early warning method and system based on grid meteorological prediction and an intelligent terminal, and the method comprises a data collection and local prediction step, a cloud fusion and regional prediction step, and a waterlogging evaluation and early warning response step. The lightweight AI model is deployed at an edge sensing terminal and an early warning terminal through a cloud edge-end collaborative architecture, local real-time prediction of meteorological data and dynamic fusion evaluation of waterlogging risks are realized, and the accuracy and efficiency of urban waterlogging early warning can be significantly improved.

The invention discloses a micro-grid capacity optimization configuration method based on an improved grey wolf algorithm. The method comprises the following steps: S1, constructing a capacity optimization configuration model of a micro-grid based on each distributed power supply of the micro-grid; s2, setting a micro-grid operation scheduling strategy; s3, under the microgrid operation scheduling strategy, solving the capacity optimization configuration model through an improved grey wolf algorithm to obtain an optimal configuration scheme; wherein the solving process comprises the following steps of: initializing a population by adopting a good point set, and confirming an initial configuration scheme; self-adaptive weight coefficients in different advancing directions are determined according to gray wolf positions, and population updating is carried out in combination with convergence factors; using a lens reverse learning strategy to update an optimal individual, and introducing a greedy strategy to carry out individual screening; the optimal configuration scheme is obtained through iteration; the method has higher optimization precision and better optimization stability, and can effectively reduce the annual value comprehensive cost and the power deviation rate of the micro-grid.

The invention relates to the technical field of automatic control, in particular to a depth control system and method for a seeder in a hilly and mountainous area, and the system comprises a visual module which is configured to collect a visual image of a to-be-sown area according to a first preset frequency; a data processing module configured to: convert the visual image into a depth map using an image processing model; performing gridding processing on the visual image; for each column of grids, determining at least one piece of target surface elevation data corresponding to the grid based on the depth map; determining at least one first adjustment instruction based on the preset seeding depth and the at least one piece of target surface elevation data; and the control instruction output module is configured to issue at least one first adjusting instruction corresponding to each column of grids to the corresponding depth limiting adjusting mechanism. According to the system, independent and accurate control over the ditching depth of each ditcher can be achieved through the visual preview and intelligent control technology, so that the seedling emergence uniformity and the crop yield are improved.

The invention discloses a seepage field adaptive analysis method and device based on a flexible polygon unit, and the method comprises the steps: dividing the polygon unit into a plurality of sub-regions, and constructing an internal water head field of each sub-region; recognizing a free water surface according to water head features extracted from the internal water head field of each sub-region; if the free water surface is recognized for the first time at present, or the error of the positions of the free water surfaces recognized by two adjacent rounds of iteration does not meet a preset condition, quadtree decomposition is carried out on the free water surface to obtain new sub-regions; returning to the step of extracting the water head features according to the internal water head field of each sub-region until the error of the positions of the free water surfaces identified by two adjacent rounds of iteration meets a preset condition, and obtaining a grid division result of the polygon unit; and performing seepage field analysis on the polygon units based on a grid division result to obtain a seepage field analysis result. According to the method, the complex seepage field is accurately simulated, and the optimal balance between high-precision discretization near the free water surface and the overall calculation efficiency is realized.

The invention provides a multi-modal fusion real-time tracking system and method for a low-speed small target in a complex low-altitude environment. The method comprises the steps that S1, sensor data of a radar, a visible light camera and an infrared camera are collected and preprocessed; the sensor data comprises a visible light image, an infrared image and a radar echo signal; s2, fusing the visible light image and the infrared image to obtain a fused image; generating a joint region of interest as a target recognition region according to the radar echo signal; s3, based on the target identification area and the fusion image, fusion is carried out, and an information fusion grid is obtained; and S4, matching a target based on the information fusion grid, and updating the trajectory of the target. According to the method, the detectability and the tracking stability of the target under complicated conditions such as shielding, severe weather and night are remarkably improved.