280 results about "Grid cell" patented technology

This utility model relates to the field of building structure engineering technology and discloses a prefabricated octagonal grid structure, including a connecting frame. A connecting mechanism is provided at the top of the connecting frame to connect it. Multiple support rods are equidistantly arranged around the bottom wall of the connecting frame, and an energy supply mechanism is provided on the outer wall of each support rod to achieve energy self-sufficiency for the structure. The connecting mechanism includes a connecting frame located at the top of the connecting frame. Multiple connecting slots are equidistantly formed on the top wall of the connecting frame, and these slots engage with the connecting frame. In this utility model, the outer connecting parts of the grid unit are precisely aligned with the mounting holes on the support rods. Bolts are passed through and tightened to firmly connect the grid unit to the support rods, enhancing the stability and load-bearing capacity of the structure. Furthermore, the octagonal grid shape enriches the visual effect of the building and meets diverse aesthetic needs.

The disclosure provides a point cloud data processing method and device, an intelligent chip, a storage medium and a vehicle, relates to the field of artificial intelligence, and in particular to the technical field of intelligent transportation, computer vision and automatic driving. The point cloud data processing method is executed by the intelligent chip, and the specific implementation scheme is: according to the width value and the height value in the point cloud data, the point cloud data is grid processed to obtain a target grid unit corresponding to the point cloud data in a predetermined grid; according to the depth value and the reflection intensity value of the point cloud data, the point cloud statistical data corresponding to the target grid unit is updated; and in response to completing the update of the point cloud statistical data corresponding to the grid unit in the predetermined grid according to a frame of point cloud data, a target task of computer vision is executed according to the point cloud statistical data corresponding to the grid unit in the predetermined grid.

Hardware unit (10) for determining a non-linear ground surface, the hardware unit (10) comprising: at least one data input interface (1) via which the hardware unit (10) receives measurement points (M) from a 3D point-supplying sensor (20); a computing device (2) which maps the measurement points (M) into a two-dimensional grid (G) and determines a height difference for each grid cell (C) based on the measurement points (M) assigned to that grid cell (C), and classifies one of these grid cells (C) as invalid if the respective height difference exceeds a predetermined threshold; if the respective height difference of one of these grid cells (C) does not exceed the threshold and the respective height difference of at least two grid cells (C) directly adjacent to that grid cell (C) also does not exceed the threshold, classifies that grid cell (C) as a flat surface;wherein the computing device (2) performs a connected component analysis stepwise over the grid cells (C) classified as planar surfaces, separating planar surfaces belonging to obstacles from planar surfaces belonging to a ground surface and obtaining the nonlinear ground surface; a data output interface (3) that outputs the nonlinear ground surface.

This application relates to an IoT-based intelligent land remediation monitoring method and system. The monitoring method includes: acquiring satellite remote sensing elevation data and historical soil composition data of the land area to be monitored; dividing the land area to be monitored into multiple grid units and assigning grid identifiers; deploying fixed soil sensor nodes and mobile drone nodes to generate a sensor network topology; collecting real-time soil parameters of each grid unit and performing noise filtering and anomaly detection to generate a soil composition dataset; inputting the soil composition dataset and historical soil composition data into a cloud-based prediction model to output a land degradation risk score and remediation strategy; controlling the execution equipment to perform land remediation operations and monitoring changes in soil parameters after execution in real time; updating the parameters of the cloud-based prediction model and optimizing the sensor network topology based on the deviation between the changes in soil parameters after execution and the expected values. This application improves agricultural production efficiency and soil health.

This invention discloses a method for outputting detailed OpenFOAM boundary surface mesh information. This method directly extracts mesh information from specified physical boundary surfaces based on OpenFOAM numerical simulation results. It automatically obtains geometric information such as coordinates, area, and normal vectors of all user-interested facets from a large number of complex topologically connected mesh cells; topological information such as the index number and mesh number of all facets; and physical field data information on all facets. The results are written to one or more data files in a format easily readable and visualized by common data post-processing software. This invention, employing the aforementioned method for outputting detailed OpenFOAM boundary surface mesh information, can flexibly adapt to various meshes, automates information extraction and output, reduces the complexity of post-processing operations, saves time and costs, supports subsequent boundary surface flux calculations, visualization analysis, and other tasks, and improves the efficiency and accuracy of post-processing for complex numerical simulations.

This disclosure provides a data acquisition and processing method and apparatus for digital engineering exploration, relating to the field of data processing technology. The method includes: acquiring multi-source geological data of the area to be explored; determining a three-dimensional geological model corresponding to the area based on the multi-source geological data; determining multimodal features based on the multi-source geological data, geological report data of the area to be explored, and spatial structure data corresponding to the three-dimensional geological model; and determining the predicted geological state values ​​of each grid cell in the three-dimensional geological model; inputting the current geological state of the multi-source acquisition device at its current location and the control parameters of the multi-source acquisition device into a reinforcement learning-based feedback control model to generate acquisition control commands for the area to be explored, thereby controlling the multi-source acquisition device to continue acquiring multi-source data in the area based on the acquisition control commands. The method and apparatus proposed in this disclosure improve the overall accuracy of digital engineering exploration operations.

This application provides a method, medium, and electronic device for correcting a ship's navigation route. The method includes: constructing a digital twin scene corresponding to a waterway; receiving motion data reported by the ship; converting the current position into the digital twin scene to obtain a first mapping point, determining the projection point of the first mapping point on the target centerline, and calculating the distance from the first mapping point to the projection point as a lateral offset distance; based on the current speed and time interval, pushing the projection point forward along the target centerline and then laterally offsetting it by the lateral offset distance to obtain the target position; in the digital twin scene, generating a target correction path from the first mapping point to the target position based on the heading attributes of the grid cells, static obstacle markers, and dynamic obstacle information; and providing the target correction path to the ship to control the ship to navigate according to the target correction path. The embodiments of this application improve the smoothness, safety, and navigation efficiency of navigation planning paths.

The present disclosure provides a three-phase flow and heat transfer coupled simulation method. The method includes: initializing parameters; reconstructing a liquid-liquid interface; determining a fluid volume fraction at an (n+1)-th time; determining a boundary grid; and determining a signed distance function of a grid cell at an n-th time; determining an interface curvature of the interface grid cell; determining abrupt physical quantities at a smooth interface; determining a surface tension of the interface; determining an intermediate fluid velocity; acquiring the fluid volume fraction and the intermediate velocity in each grid cell in the computational domain; determining a particle velocity; determining a displacement of a p-th solid particle at the (n+1)-th time and a solid volume fraction in the grid cell at the (n+1)-th time; determining a final velocity of the computational domain at the (n+1)-th time; and solving a temperature and an interface heat flux density.

The application relates to the field of traditional Chinese medicine diagnosis and treatment, and discloses a disease acupoint rash image analysis system based on a body surface gridding coordinate system. The system comprises a system data acquisition module, a body surface gridding coordinate system construction module, a rash image feature extraction and analysis module, a dynamic pathological correlation analysis module and a dynamic risk early warning module. The back body surface image, physiological signals, clinical indexes and environmental data of a patient are collected. Then, the image data is used to calibrate anatomical mark points, and grid unit codes are stored by division. The gridded body surface data is subjected to multi-dimensional color space conversion and cross-modal feature fusion to obtain quantitative rash image feature data. The rash image dynamic deviation feature set is obtained by matching a preset database according to the rash image feature data, physiological signals, clinical index data and current environmental data, the network is constructed to predict disease conversion probability and analyze acupoint correlation. Finally, the visual analysis data is obtained, a heat map and ranking are generated, and early warning information is output according to the comparison result, thereby providing strong support for traditional Chinese medicine diagnosis and treatment.

The application provides a variable-grid three-dimensional longitudinal wave equation forward numerical simulation method, and the numerical simulation method comprises the following steps: S1, establishing an irregular grid division strategy; S2, under the irregular grid division strategy, constructing a regular grid function relationship in a Cartesian coordinate system; and S3, performing forward numerical simulation according to the regular grid function relationship. The method reduces the number of grid units and ensures the forward simulation precision, and realizes an efficient and high-precision variable-grid forward simulation method.

This application relates to a method, system, device, and medium for tracking droplets in a cross-flow jet. The method includes: obtaining a binary grid distribution by thresholding the liquid phase volume fraction of three-dimensional Eulerian grid cells; acquiring the three-dimensional liquid phase structure and its number by marking three-dimensional connected regions; and calculating its geometric and dynamic parameters to form a set of physical properties. Based on the spatial grid overlap relationship between the connected regions of the current time step and the connected regions of the previous time step, a cross-time step connectivity mapping relationship is constructed and assigned an evolutionary state label. For connected regions with evolutionary state labels indicating newly formed or fragmented structures, target regions satisfying droplet transformation criteria are selected according to the set of physical properties, and Lagrange particle injection is completed. This method can solve the technical problems of inaccurate droplet identification, inconsistent transformation, and discontinuous tracking, improving the accuracy and consistency of cross-flow jet droplet simulation.

This invention relates to the field of digital simulation of landslide evolution processes, and particularly to a method for digitally simulating landslide evolution processes based on the fusion of multi-source heterogeneous data. The method includes: collecting multi-source heterogeneous raw monitoring data and performing spatial and temporal standardization; mapping the standardized multi-source heterogeneous monitoring data to initial response values ​​of grid cells and performing preprocessing to output a set of cell response sequences; calculating the positive incremental response based on the cell response sequences and the fixed lag step size of the monitoring sources; calculating the lag phase convergence evolution potential based on the positive incremental response using a time-series incremental analysis algorithm; and obtaining the cell instability activity level based on the lag phase convergence evolution potential and the normalized initial response values ​​of the grid cells, and performing digital simulation and risk labeling of landslide evolution. This method solves the problems of delayed response to geological changes, unscientific multi-source data fusion, poor simulation accuracy, and difficulty in achieving real-time and accurate simulation of landslide evolution processes.

The application provides a CMP process optimization method, system, medium and product based on multi-physical field coupling. The target chip layout is divided by a three-level grid system, and the multi-scale characteristic quantization data of the micro grid unit is extracted. Combined with the physical simulation operation of the CMP multi-physical field full coupling mathematical model, the complex evolution law of the three-dimensional topography of the wafer surface under the advanced process can be fully described, the accuracy and consistency of the simulation result are improved, and the problem of large prediction deviation of the traditional model assumption simplification is overcome. At the same time, the multi-physical effects such as contact mechanics, chemical reaction and thermodynamics are included in the unified modeling framework, the multi-physical field coupling simulation is realized, and the scientific and systematic theoretical support is provided for process optimization. The simulation result data is compensated and corrected by using the machine learning intelligent compensation network, and the final prediction result and the corresponding confidence interval are output, the prediction accuracy is improved, and the prediction reliability is quantified, which provides risk basis for process decision.

The application provides a mangrove damage early warning method and system based on remote sensing, comprising the following steps: determining a research area and constructing a spatial index database; determining a baseline period and a mangrove distribution area; extracting a vector boundary layer from the mangrove distribution area according to the baseline period, thereby constructing a baseline database; downloading the latest remote sensing image of the research area every month from the baseline period, and calculating NDVI of each latest remote sensing image, thereby forming a time series NDVI dataset; comparing the difference between the monthly NDVI and the NDVI of the same period of the previous year based on each grid unit in the spatial index database; determining the mangrove damage risk according to the difference result; the early warning response is more timely and accurate; and the method is simple and easy to implement automatically.

This invention relates to low-altitude security in petrochemical plant areas, specifically to a method and system for creating a three-dimensional safety map of petrochemical plant areas. The method involves multi-level grid subdivision of the petrochemical plant area based on GeoSOT, matching grid accuracy according to target size, and generating a unique BeiDou grid code for each grid cell. Multi-source data is unified to the BeiDou grid code spatiotemporal reference, an error compensation model based on environmental perception is established to suppress multipath interference, and multi-source data fusion is performed. The grid status is dynamically updated, partially updated, and version-managed to achieve real-time updates and historical backtracking of the airspace situation. Target threat assessment is conducted, and countermeasure resources are scheduled for rapid countermeasures against threatening targets. A three-dimensional map visualization rendering is performed, intuitively presenting the airspace situation, target trajectories, and countermeasure equipment status. This invention effectively overcomes the shortcomings of two-dimensional control, such as airspace blind spots, insufficient positioning accuracy in complex environments, inability to achieve three-dimensional fusion of multi-source data, and low efficiency in dynamic control response.

This invention discloses a method for identifying geological hazard risk zones based on a local search strategy, belonging to the field of geological hazard monitoring and early warning technology. The method includes the following steps: locating seed points within a target area; finding similar developmental condition r grid cells within the local search window Ω of the seed point s, forming a similar developmental condition region; then, using the raster area where the seed point s is located as the initial region, iteratively performing morphological dilation, expanding the current region by a certain number of pixels during each iteration and intersecting it with the similar developmental condition region, updating the current region with the intersecting region; after iteration terminates, obtaining the similar neighborhood of the seed point; converting the similar neighborhood region raster of the seed point into vector polygons, and optimizing the boundary smoothing to obtain the risk zone identification range. This invention focuses on core area calculation, avoiding the low efficiency problem of full-domain analysis and identification, and is suitable for rapid screening and dynamic updating of large-scale risk zones.

The application discloses a kind of topological optimization method, device, medium and equipment based on CutFEM and SIMP, method includes: definition design domain, discrete design domain into background grid unit, with node density as design variable;Node density is converted into node level value;According to node level value, unit is divided into entity, blank and cutting unit;Subgrid division is carried out to cutting unit;Boundary is identified as inner boundary and outer boundary;Stiffness matrix assembly is carried out to the material area unit of entity unit and cutting unit, obtains node displacement;Solving topological optimization formula, calculating sensitivity updates design variable, until optimal structure is obtained.The application combines CutFEM and SIMP, can solve the problem of insufficient calculation accuracy and efficiency of existing SIMP method under complex geometry and boundary conditions.

The application relates to a fluid-solid simulation method, device and equipment considering normal and tangential interface effects, which comprises the following steps: after simulation initialization, iterative calculation is performed on physical quantities of each grid unit of a flow field and a solid, in each iteration process, boundary conditions are applied to a calculation domain range, a time step of current iteration is determined, high-precision reconstruction is performed on the physical quantities in each grid unit, after normal and tangential interface effects are applied to the boundaries of the grid units according to boundary types, initial physical quantities of a Riemann problem are corrected, then fluxes of each grid unit are obtained by solving the Riemann problem, the physical quantities of the current iteration are obtained according to the fluxes, and the next iteration calculation is entered until the iteration stopping requirement is met, and then the fluid-solid simulation is completed. The simulation efficiency is improved while the simulation precision is improved by considering the normal and tangential effects.

The application discloses a kind of unmanned plane surveying and mapping methods for reducing surveying and mapping error, it is related to unmanned plane surveying and mapping technical field, comprising: obtaining survey area image data, survey area image is regularly grid division, extract feature point and calculate the numerical vector for representing the local image features of feature point, the distance concentration between numerical vector is counted and matching vector direction standard deviation, when numerical vector distance concentration is greater than the determination threshold in descriptor set and matching vector direction standard deviation is less than direction dispersion determination threshold, corresponding grid unit is determined as periodic repeating texture area;Obtain inertial measurement unit attitude data, according to the exposure mode of each pixel row of camera determines the exposure time of each pixel row.The application identifies periodic repeating texture area and non-periodic repeating texture area in survey area image, and respectively constructs first matching set and second matching set, realizes the partition management of matching constraint under different texture structure.

The present disclosure discloses a method for reconstructing the working face of coal mine based on search space pruning and multi-population dynamic adjustment, which involves the technical field of working face reconstruction of coal mine under incomplete projection conditions, comprising: based on prior knowledge of the working face reconstruction model structure, an initial grid partitioning of the exploration area is performed. Subsequently, multi-scale grid partitioning is achieved through search space pruning, guided by the sum of ray intercepts within each grid unit; to meet the requirements of population diversity and rapid convergence in the multi-population genetic algorithm, a multi-scale reconstruction objective function is constructed based on the partitioned multi-scale grids, this objective function is then solved using a dynamic multi-population genetic algorithm. Therefore, the above-mentioned method for reconstructing the working face of coal mine based on search space pruning and multi-population dynamic adjustment may dynamically adjust and optimize the number of populations, to ensure that the diversity of populations may be maintained, and the search efficiency may be improved, thereby improving the stability and convergence speed of the working face reconstruction operation.

This invention relates to the field of ecological environment assessment and spatial simulation technology, and discloses a method for grassland degradation ecological risk assessment based on a multi-agent model. The method includes a spatial risk assessment module that acquires multi-source basic data and divides it into discrete grid cells, calculating a landscape ecological risk index to generate spatial distribution results; a driving mechanism identification module that extracts driving factors to construct an improved regression tree model and outputs nonlinear response rules; and a multi-agent dynamic simulation module that constructs grassland environmental entities based on grid cells, injects risk indices and response rules, generates herder behavior entities, and inputs management policy parameters. Iterative calculations are performed using these two types of entities to simulate the dynamic process of herder relocation and resource consumption. After the iteration reaches the target year, the grid landscape attributes are reclassified according to the remaining grass cover, and the data is re-input into the assessment module for aggregation calculations, outputting a spatial distribution map to complete the evolution assessment. This invention can intuitively test the intervention effect of management policies on grassland degradation.

A vehicle mileage estimation method based on remote sensing imagery and deep learning includes: constructing a self-labeled dataset by dividing high-resolution satellite images into grid cells; estimating vehicle density using a YOLO-based deep learning model, which achieves multi-scale feature fusion through a three-layer pyramid network for accurate vehicle detection; abstracting the urban road network as a graph structure and employing a cross-temporal graph neural network (CrossGraphNet) to build a model of the relationship between vehicle density and speed for accurate speed prediction; and training a semi-supervised graph neural network vehicle mileage estimation model using traffic count data from ground monitoring stations as ground truth. This model combines vehicle density and speed data with road topology relationships and uses a message passing algorithm to accurately estimate vehicle mileage. This invention overcomes the limitations of traditional methods, effectively improves the efficiency and accuracy of traffic monitoring, and provides strong data support for traffic management and planning.

The application discloses a kind of image recognition method and system under complex illumination environment, the method includes: obtaining the image to be identified needing to carry out image recognition, the illumination influence area is obtained by analyzing the image to be identified, and the illumination influence area is divided into a plurality of grid units according to pre-set rule by grid division;Respectively, randomly select pixel points from illumination influence area and non-illumination influence area, and obtain corresponding pixel block based on pre-set window size;The similarity weight between the pixel block of illumination influence area and non-illumination influence area is calculated respectively, to denoise the image to be identified, and the denoising identification image is input into pre-set image recognition model to obtain corresponding image recognition result.The application solves the problem of low image recognition efficiency in the prior art under complex illumination environment.

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 relates to the field of power grid coordinated control technology, and particularly to a method, system, and medium for assessing the load potential of electric vehicles through a coordinated approach between the main grid, distribution network, and microgrid. The method includes: acquiring power grid topology information, charging behavior data, user travel data, and power grid operation data; forming grid cells from the distribution network; constructing a coordinated architecture of the main grid layer, distribution network layer, and microgrid layer based on the grid cells; generating user behavior profiles based on the charging behavior data and user travel data; predicting the charging load of each grid cell based on the user behavior profiles and power grid operation data; aggregating the adjustable power of the electric vehicle group, constructing a generalized energy storage equivalent model, and determining the regulation potential boundary; generating a guidance strategy and outputting charging load adjustment instructions, and continuously correcting the electric vehicle charging load and regulation potential boundary. This invention effectively solves the problems of inaccurate electric vehicle load prediction and distorted regulation potential assessment, which make it difficult to support refined power grid control.

This application discloses a method, device, terminal, and storage medium for simulating the electrical characteristics of integrated circuits. The method includes acquiring a model of the integrated circuit to be simulated; meshing the model to obtain an integrated circuit mesh dataset composed of multiple mesh cells; constructing corresponding charge basis functions and current basis functions based on the mesh cells; using the charge basis functions as the fusion object, progressively merging and updating the charge basis functions; simultaneously, merging and updating the current basis functions through geometric mapping; after all fusion and updates are completed, acquiring the integrated circuit basis function dataset; and performing electrical characteristic simulation on the integrated circuit to be simulated based on the integrated circuit basis function dataset. This achieves rapid updating and low-order representation of complex coupling capacitance matrices, reducing the theoretical complexity from O(n^2) to O(n^2) of traditional back-end order reduction methods. 3 The time complexity is reduced to O(n), while the model accuracy and order reduction effect are maintained, and the efficiency of model order reduction is greatly improved.

The application provides a step-by-step decomposition-space mapping three-dimensional material point material parameter random field generation method, and belongs to the technical field of water conservancy and hydropower. First, a three-dimensional geometric model of a structure is established according to engineering geological data, high-precision mesh division is carried out, each mesh is converted into a material point carrying mass and volume, and a material point model is obtained. Second, a background mesh element is determined, and a background mesh covering the space occupied by the entire structure is generated. Third, a correlation function reflecting the material parameter properties is selected, a step-by-step decomposition method is used, and a material parameter random field on the background mesh element is generated. Finally, the value of the material parameter of the material point model is determined through a space mapping technology, and a three-dimensional material point material parameter random field is generated. The application is based on the material point method, and realizes the generation of a three-dimensional random field of a geotechnical engineering material parameter through the joint application of a step-by-step decomposition-space mapping technology, thereby providing technical support for the simulation of large deformation of a geotechnical engineering considering spatial variability.

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 belongs to the technical field of water supply network risk analysis, and discloses a water supply network risk probability prediction model building method fusing multi-source data, which obtains water supply network data of a target area and classifies open source map data, then combines spatial buffer analysis and priority rule determination to realize extraction of external environment characteristics; then rule grid units are constructed within the spatial range of the water supply network, the maintenance spatial density of each grid unit is calculated, and the maintenance spatial density of the grid unit is mapped to each pipe section according to the maintenance spatial density, so that the extraction of the maintenance spatial density characteristics is realized; finally, the machine learning risk prediction model is constructed by integrating the pipe network itself attributes, external environment and maintenance spatial density characteristics, and the risk probability of the pipe section level is directly output. The application fuses open source map data spatial analysis, fault point density clustering and integrated learning prediction, and is suitable for risk probability prediction, high-risk pipe section identification and preventive maintenance decision support of urban water supply networks.

This invention discloses a method for joint allocation and optimization of multiple water sources in underground reservoirs, specifically relating to the field of water resource allocation technology. The method includes basic parameter acquisition and spatial coordinate alignment, grid cell dual-accessibility attribute labeling, grid-based reservoir capacity effectiveness classification and twin mapping construction, full-cycle supply and demand parameter collection and time-period segmentation, and time-period supply and demand matching and allocation scheme generation. This invention unifies the spatial benchmark of multi-source parameters through cross-data source spatial coordinate matching and alignment, achieving precise spatial correspondence between grid-level hydrogeological and engineering node parameters. It links the spatial matching of single grid cells with recharge and extraction nodes to aquifer parameters for accessibility labeling, classifies reservoir capacity effectiveness based on dual thresholds, constructs a reservoir capacity mapping with dual constraints, segments the entire cycle into equal-length time periods for matching supply and demand parameters, completes time-period supply and demand matching and reservoir capacity iterative updates, and achieves temporal linkage between recharge and extraction, accurately matching the spatiotemporal distribution of multi-source water supply and irrigation water demand.