46 results about "Grid computation" patented technology

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.

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 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.

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.

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 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 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 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 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.

The application discloses a method, system, product and medium for path planning of a UAV group, and relates to the field of non-electric variable control or regulation systems.The method comprises the following steps: collecting environmental data such as terrain height, obstacle distribution and dynamic targets within the detection range of a UAV, converting the environmental data into a grid cell space occupation state, dividing a search space into three-dimensional grids, calculating the unexplored probability value of each cell, extracting the time dimension change data and the gradient information between cells, identifying the dynamic change area of the environment, determining the boundary features and generating path node data.The node data is compressed into lightweight path information containing coordinates, priority and time sequence constraints, and a flight path sequence is generated in combination with the position of the UAV and is distributed.The method can improve the detection efficiency of the UAV.

The embodiment of the invention discloses a grid optimization method and equipment based on rotation parameters. The method comprises the following steps: inputting an initial grid, and calculating a local slope value of each grid point in the initial grid; judging a flat region and a steep region in the initial grid according to the local gradient value; optimizing a grid density function of the steep region based on a grid density rotation parameter to generate an optimized grid density function; and generating a grid in the steep region according to the optimized grid density function, thereby realizing collaborative optimization of the grid in the steep terrain region while maintaining the grid quality of the flat or simple terrain region, realizing targeted grid encryption, more accurately depicting the terrain forcing effect, and improving the terrain forcing effect. The simulation capability of key weather processes such as mountain circulation and terrain rainfall is improved; meanwhile, through reasonable grid transition distribution, computing resources are saved, and ideal technical support is provided for high-resolution region simulation.

The present application relates to the technical field of printed circuit control, and in particular to a multi-layer PCB winding pressing alignment method for high-frequency planar transformers. The method obtains a PCB layout and divides a grid, calculates the copper foil area proportion of each grid; determines the radial unit vector of each positioning pin based on the vector relationship between the positioning pin area and the layout geometric center; in the pressing process, the resin extrusion trend scalar is generated by combining the real-time obtained deformation height of each grid under pressure and the copper foil area proportion, and the two-dimensional flow vector is obtained through local space partial derivative analysis; then the vector and the radial unit vector are combined to calculate the radial extrusion component of each positioning pin area, and finally the pressing process is dynamically controlled according to the numerical distribution of all components to realize high-precision alignment control.

The embodiment of the invention discloses a reservoir over-standard flood inundation risk zoning method, device and equipment, and the method comprises the steps: determining a reservoir siltation influence probability factor and a reservoir dam break influence probability factor under a siltation condition; and on the basis of the reservoir siltation influence probability factor and the reservoir dam break influence probability factor, calibrating a reservoir inundation comprehensive risk degree of the siltation-dam break dual influence probability under the condition of the over-standard flood, and performing clustering analysis on the reservoir inundation comprehensive risk degree of each grid calculation unit by using a K-mean clustering algorithm to finally determine a flood risk level. The technical problem that in the prior art, the prediction zoning accuracy of the flood inundation risk of the reservoir area with the high sediment content and the weak desilting capacity is low is solved, and a scientific basis and a certain technical support are provided for reservoir flood inundation risk assessment and disaster prevention and reduction planning in the high sediment content basin area.

This invention provides a fluid simulation method that allows for easy comparison of fluid analysis results for multiple objects with different shapes. [Solution] This is a fluid simulation method. This method includes the step of calculating the physical quantities of a fluid using an object model 20 and a computational grid 30. The object model 20 includes a first object model 21 and a second object model. The first object model 21 has a first shape 11A and a first analytical coordinate system 21a. The second object model has a second shape and a second analytical coordinate system. The computational grid 30 includes a first computational grid 31 associated with the first object model 21 and a second computational grid associated with the second object model. When the first analytical coordinate system 21a and the second analytical coordinate system are aligned, the first computational grid 31 and the second computational grid include a common computational grid area 35 where nodes 26 or elements G(i) are in the same position relative to each other.

The invention discloses a low-altitude flight risk prediction method based on a grid neighborhood graph convolutional network, relates to the technical field of low-altitude flight risk prediction, and constructs the grid neighborhood graph convolutional network on the basis of a space-time integrated 4D coded low-altitude meteorological grid knowledge graph model. The grid neighborhood graph convolutional network comprises a graph neural network, a neighborhood grid calculation unit and a time evolution unit, the graph neural network is used for learning meteorological knowledge in a knowledge graph, and the meteorological knowledge comprises weather in a space grid of the graph neural network and influence of the weather in the neighborhood grid on the graph neural network; the neighborhood grid calculation unit is used for learning space, topology and environment information in a space grid, and the time evolution unit is used for learning time sequence evolution information in time grid coding to realize time sequence prediction reasoning. The average prediction accuracy of the grid prediction model disclosed by the invention in a short time reaches 90.73%, and the average prediction accuracy of the grid prediction model in a long time reaches 87.00%.

To prevent a data transfer time from being a system bottleneck.SOLUTION: A grid computing system 1 divides a job being a processing object into a plurality of units and performs processing in a pipeline where first transfer processing of transferring job data from a master device to vehicles 10 with respect to each of the units, arithmetic processing of each of the units in the vehicles 10, and second transfer processing of transferring arithmetic result data after the arithmetic processing from the vehicles 10 to the master device are in different stages.SELECTED DRAWING: Figure 6

An analogue simulation method for the oxidation behavior of a C / SiC composite material component comprises the following steps that A1, Abaqus software is used for modeling the component, space coordinates of all integration points of the component are obtained, and an oxidation starting surface is designated; a2, writing a Python program, dividing grids based on a Delaunay algorithm, calculating the shortest distance from any integral point to all oxidation starting surfaces, and outputting the shortest distance; a3, compiling a C / SiC composite material oxidation analysis Umat subprogram based on Abaqus software by adopting a Fortran language, and reading shortest distance information; and A4, based on an existing C / SiC composite material oxidation diffusion mathematical model, a C / SiC finite element analysis model is established, and the oxidation expansion process of the component under different loads and temperatures is obtained.

Embodiments of the present application provide a living body information detection method and apparatus. The detection method comprises: dividing a spatial region covered by a radar signal into a plurality of grid spaces; determining a radar signal at each spatial position in each grid space; for each grid space, calculating feature data of the radar signals in the grid space within a first time period, wherein the feature data is an average value of the variations of the radar signals at all spatial positions in the grid space at each moment within the first time period; and inputting the feature data corresponding to all grid spaces into a trained machine learning model so as to detect living body information. In the embodiments of the present application, by delineating grids on a radar coverage region, calculating the feature data for each grid, and outputting the feature data, good detection accuracy is ensured while a plurality of types of information of a living body are detected.

This invention relates to the field of geological exploration and 3D geological modeling technology, specifically a method and system for 3D modeling of ore bodies based on multi-source exploration geological data. The method includes: acquiring multi-source spatial discrete data and spatial continuous gradient data within a preset 3D spatial range, and constructing a spatial voxel mesh based on the multi-source spatial discrete data and spatial continuous gradient data; calculating the spatial metric tensor matrix of each voxel node in the spatial voxel mesh to generate a spatial topological barrier field; using the source point of the target object as the initial zero-order jump set to generate an initial symbolic distance field; extracting the zero isosurface of the initial symbolic distance field to obtain the Euclidean deviation residual; if the Euclidean deviation residual exceeds a preset residual threshold, continuing until the Euclidean deviation residual does not exceed the residual threshold; when the Euclidean deviation residual does not exceed the residual threshold, generating a 3D triangular mesh of the target object. This invention achieves simultaneous continuous generation of the ore body surface and fault blocking.

The present disclosure provides system (106) and method (500) for identifying Fixed Wireless Devices (FWDs) based traffic hotspots in a network environment. The system (106) employs a receiving module (304) to receive geographic information and user-defined queries. A data collection module (306) collects geospatial data from network users present within selected geographic area, which is then compiled to create data repository. An execution module (308) applies user-defined queries on data repository to obtain outputs. A grid computation module performs grid wise computation and filtering on outputs to provide a filtered dataset. A visualization module (312) visualizes filtered dataset on user device (102) in interactive visual format. A report generation module (314) generates a comprehensive report based on filtered dataset. The comprehensive report includes potential traffic hotspots for placing FWDs and user distribution pattern of the selected geographic area.

The invention discloses a method and equipment for simulating rugged topography to carry out forward modeling, and the method comprises the steps: building a curved coordinate system according to the form of a target rugged topography, and obtaining the number of curved coordinate systems of each calculation node under the curved coordinate system; electromagnetic parameters required by forward modeling simulation are set, and a radar wave fluctuation equation under the curved coordinate system is split to obtain a plurality of split equations which can be independently calculated; according to the number of the curved coordinate systems and the structure of the splitting equation, the deployment positions of the electric field intensity and the magnetic field intensity in the staggered grids are optimized, so that the staggered grids are matched with the spatial characteristics of the curved coordinate systems and the number of the curved coordinate systems; staggered grid calculation is carried out on the splitting equations, calculation results of the splitting equations are recombined and added, the calculation results are stored in grid units according to a staggered rule, and high-precision forward modeling of the rugged topography is achieved. According to the method, the problems of stepped angular points and derived frequency dispersion and scattering generated when the rugged topography is simulated by a conventional regular grid can be effectively avoided, and the wave field simulation precision is greatly improved.

This invention relates to a pipeline network monitoring method, and more particularly to a method and system for monitoring pipeline network slow-flow and overflow areas. The method includes the following steps: selecting monitoring nodes, installing online liquid level monitoring devices, and establishing a pipeline network node liquid level monitoring network; combining urban pipeline network design, construction survey maps, and geographic information base data to complete coding, classification, and spatial data collection, and establishing a basic information database; constructing a spatial data equidistant calculation model to screen for discrepancies; identifying overflow nodes; and on-site handling. This invention, through IoT-based pipeline network node monitoring and using grid computing to determine the extent of slow-flow and overflow areas in urban underground pipeline networks, solves the problems of high difficulty, high cost, and long cycle in existing urban underground pipeline network blockage detection, significantly improving the transport efficiency of urban underground drainage networks and achieving the goal of improving the quality and efficiency of urban drainage network supervision.

The invention provides a submarine cable burial depth monitoring method, a program product and electronic equipment. The submarine cable burial depth monitoring method comprises the following steps: acquiring load data and temperature data of a to-be-measured space point in a first submarine cable in at least one load change process; obtaining a load characteristic value based on the load data; obtaining a temperature response characteristic value based on the temperature data; obtaining a feature set of the spatial point to be measured according to the load feature value and the temperature response feature value; and inputting the feature set into a burial depth monitoring model to obtain burial depth data of the to-be-measured spatial point. The burial depth monitoring model is used for reasoning the feature set to obtain the burial depth data of the to-be-measured space point, and the heat dissipation condition does not need to be calculated, so that errors caused by parameter estimation in the calculation are reduced, a large amount of grid calculation is avoided, calculation resources are saved, the burial depth measurement complexity of the submarine cable is reduced, and the calculation time consumption is reduced; and the burial depth measuring and calculating efficiency is improved. And the mode is lower in use threshold and convenient to operate.

This application discloses a hybrid acceleration method and related apparatus for computational fluid dynamics simulation based on data dimensionality reduction and multigrid interpolation, relating to the field of computational fluid dynamics technology. The method includes: calling a reduced-order prediction model based on the fine-grid physical field data of the current time step to generate a coarse-grid predicted physical field for the current time step; spatially interpolating the coarse-grid predicted physical field of the current time step and mapping it onto a fine-grid to generate initial fine-grid field data for the current time step; using the initial fine-grid field data of the current time step as initial conditions, continuing to perform computational fluid dynamics solutions for the next number of time steps on the fine-grid to generate updated fine-grid physical field data; using the updated fine-grid physical field data as the benchmark for the next iteration cycle until a preset total simulation time step is reached, and outputting the final simulation result of the target physical field. This application fundamentally reduces the dependence of high-fidelity simulation on fine-grid computational resources.

This application relates to an adaptive cross-tree mesh computation method and apparatus for complex microscale structures. The method is applicable to efficient numerical solutions in automatically generated cross-tree meshes for complex micro-surfaces. Addressing the problems of large local geometric scale spans, complex microstructure surface morphology, difficulty in generating high-quality meshes near boundaries, and insufficient adaptability of traditional solvers to special meshes in complex microscale structure scenarios of aircraft, this invention constructs an adaptive cross-tree mesh computation method for complex microscale structures. By combining the adaptive cross-tree mesh with a flux-solving algorithm, stable and efficient numerical solutions for flow fields of complex shapes can be achieved, thereby improving the flexibility of mesh generation, flow field resolution, and overall computational efficiency under complex configuration conditions.

Generating volumetric effect images (e.g. smoke, fog, sand, water, avalanche, rockslide, fire) comprises using a 3D grid to sample (410) (e.g. using a frustrum voxel grid) computer-generated volumetri