13971 results about "Mesh grid" patented technology

The invention relates to the technical field of building construction, in particular to a building construction safety intelligent early warning system based on multi-sensor fusion and deep learning. Comprising a multi-source sensing unit; an intelligent fusion unit; a depth analysis unit; and a dynamic response unit. According to the method, through a mixed deep learning model, personnel-equipment-environment space association in a 1m * 1m * 0.5 m space grid is extracted through an improved U-Net network, and a space risk association map is output; modeling data of 10 sampling periods by using a bidirectional LSTM network, and outputting a short-term prediction value; and carrying out weighted fusion through an attention mechanism to form a risk feature vector, and removing invalid anomalies in cooperation with parameter anomaly judgment and cross validation. And then a risk grade evaluation module introduces multiple coefficients to calculate a risk grade index, and a grid diffusion range is delimited according to grades, so that real-time identification, quantitative evaluation and range pre-judgment of construction safety risks are realized, and the problem that risk identification evaluation lacks scenarized accuracy and comprehensiveness is solved.

The invention relates to the technical field of quality monitoring, and discloses a diamond high-strength micro-powder quality detection method and system based on artificial intelligence. The method comprises the steps of obtaining a two-dimensional projection image sequence of diamond micro-powder particles, calculating a projection matrix based on camera calibration parameters and geometric constraints, obtaining a multi-view image data set of the particles, establishing a pixel-level corresponding relation, extracting three-dimensional space coordinates of the surfaces of the particles, and reconstructing dense point cloud data of the particles. Establishing a local coordinate system based on the dense point cloud data, determining attitude parameters of particles in a three-dimensional space, if the attitude parameters deviate from a normal range, performing attitude compensation processing to obtain standardized point cloud data, and performing three-dimensional grid model construction on the standardized point cloud data; and calculating geometrical characteristic parameters of the particles based on the three-dimensional grid model, performing defect detection on the surfaces of the particles, and generating a crystal integrity evaluation report of the particles. The quality detection accuracy of the diamond high-strength micro-powder particles is improved.

A method for quality inspection of an etching paste material based on a spectral response difference, including: identifying a position of density mutation boundary through spectral collection and density gradient analysis. Applying a specific frequency beam to obtain the resonance response parameter, generating stress field reconstruction data. Performing a reverse optical tracking to obtain a defect formation path, generating degradation prediction data. Establishing a self-organizing optical monitoring grid, to form a hierarchical spectral fingerprint library. Constructing a multi-point linked defect blocking network, to form an interconnected optical energy field. Monitoring a cooperative response to obtain network stability data, Identifying abnormal position coordinates based on a material quality grade and the network stability data, obtaining the abnormal position coordinates. Performing a phase adjustment to obtain a phase difference spectral set, conducting a phase comparison marking on the abnormal position coordinates, completing the quality inspection of the etching paste material.

The invention discloses a fatigue life simulation evaluation method for a lightweight aluminum alloy material of a new energy automobile, and relates to the technical field of material life evaluation. A microstructure image is collected, coupling features are extracted through machine learning, and heterogeneous data fusion and enhancement are completed; generating a topological optimization structure based on a GAN, introducing a VPSC model to describe anisotropy according to a stress gradient dynamic grid, and constructing a dynamic finite element model; fusing vehicle driving data, predicting a load by using LSTM, performing VMD decomposition and environment correction, and realizing space-time correlation load spectrum reconstruction; a phase field model is used in a microcosmic mode, cracks are tracked in a macroscopic mode through XFEM, damage parameters are transmitted in a bidirectional coupling mode, and multi-physics field coupling simulation is carried out; fusing simulation and test data by adopting Bayesian reasoning, calculating life probability distribution, and correcting parameters when errors exceed the limit; according to the method, the fatigue life prediction error is finally reduced, the time consumption of single simulation is reduced, full-life-cycle evaluation and visual early warning are realized, an efficient scheme is provided for lightweight design, and industrial technology upgrading is promoted.

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 field soil heavy metal pollution health risk dynamic assessment and intelligent early warning system, and relates to the technical field of soil environment monitoring. The system comprises a multi-source data acquisition unit, a data preprocessing unit, a risk calculation engine and a visual interaction terminal. The key technical point is that a dynamic field evolution analysis module and an adaptive grid rendering control module are introduced; the dynamic field evolution analysis module constructs a pollution potential energy field matrix representing a pollutant migration trend based on soil heavy metal concentration and hydrogeological parameters, and calculates a space-time gradient change vector of the pollution potential energy field matrix; and the latter dynamically adjusts the grid local density according to the gradient vector module value, and automatically encrypts the computational nodes in the region with severe risk change. In cooperation with a time sequence prediction deduction and feedback correction mechanism, the method can simulate the dynamic evolution of the pollution plume in the porous medium in real time, solves the problems that a migration rule is difficult to capture and the calculation efficiency of a uniform grid is low in traditional static evaluation, and achieves three-dimensional dynamic risk early warning with high precision and low calculation power consumption.

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

The invention relates to the technical field of three-dimensional reconstruction and simulation, and discloses a foam material porous structure three-dimensional reconstruction and simulation system, which comprises a scanning imaging module used for carrying out scanning imaging on a foam material sample to obtain pore image data; the pore boundary recognition module is used for performing pore boundary recognition based on the pore image data to obtain a pore boundary recognition result; the three-dimensional reconstruction module is used for executing three-dimensional reconstruction of bubble evolution physical constraints according to the pore boundary recognition result to obtain a three-dimensional reconstruction model; the coupling simulation module is used for performing grid division and coupling simulation on the three-dimensional reconstruction model to obtain mechanical simulation data; and the parameter solving module is used for carrying out density field optimization and parameter solving based on the mechanical simulation data to obtain optimal gap design parameters, so that seamless connection from simulation analysis to optimization design is realized, the structural design period of the foaming material is shortened, and the design precision and consistency are improved.

The invention provides a double-pulse high-frequency switching power supply control method and system for precise electroplating, and relates to the field of electroplating, and the method comprises the steps: collecting area surface data through a three-dimensional scanner, and obtaining a three-dimensional model; extracting a high-curvature area grid according to the three-dimensional model, and calculating to obtain a surface concave-convex degree index; performing current field simulation, and calculating current density vector distribution; when the deviation of the current density vector distribution exceeds a preset deviation threshold value, pulse parameters are optimized through a genetic algorithm; selecting a pulse parameter which is most matched with the surface concave-convex degree index, and carrying out iterative calculation to obtain updated current density vector distribution; based on the difference between the updated current density vector distribution and the initial distribution, predicting a coating thickness value, and determining a preliminary evaluation index; and optimizing pulse parameters to obtain a final control scheme of uniform current distribution. According to the method, pulse parameters can be dynamically optimized according to the geometrical shape of the workpiece, and uniform current distribution and stable plating quality are realized.

The embodiment of the invention relates to the technical field of data modeling analysis, and discloses a tunnel rock stratum large deformation analysis method and system based on three-dimensional modeling, and the method comprises the steps: collecting initial three-dimensional point cloud data through three-dimensional laser scanning; constructing an initial three-dimensional geologic model containing spatial morphological characteristics and a rock stratum interface geometric topological relation through space coordinate matching and curved surface reconstruction; finite element unstructured mesh generation is carried out on the model, and a rock stratum mechanical analysis model is established in combination with physical and mechanical parameters; inputting construction parameters and process information, activating unit nodes in sequence, and solving a force balance equation to simulate stress distribution; identifying a potential deformation area through iterative calculation, and adjusting boundary conditions to predict a deformation trend; the three-dimensional space distribution cloud atlas, the time evolution curve and the position marks are fused to generate multi-view deformation early warning information, the accuracy and the visualization degree of tunnel rock stratum deformation analysis are improved, and support is provided for construction safety.

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.

Disclosed in the present invention are a low-altitude air route risk map construction method and system based on hexagonal grid cells. The method comprises: on the basis of management and control requirements for different types of airspace, forming low-altitude airspace three-dimensional hexagonal hierarchical grids by means of multi-scale partitioning of an airspace horizontal plane and multi-scale partitioning of an airspace vertical plane; constructing an unmanned aerial vehicle flight risk assessment indicator system for the low-altitude airspace three-dimensional hexagonal hierarchical grids, and after optimization, constructing an unmanned aerial vehicle operational risk assessment model based on a dynamic Bayesian network, so as to generate multi-scale grid risk values; and combining the multi-scale grid risk values with geographic location information of a region, designing a hexagonal grid code index, and generating a dynamic multi-scale low-altitude air route three-dimensional hexagonal risk map. The present invention can improve the accuracy and real-time performance of unmanned aerial vehicle flight risk assessment of grids, quickly obtain low-risk grids of an unmanned aerial vehicle in a target region, and improve the safety of air route planning.

The invention discloses an efficient optical flow estimation method and device based on Mama, and the method comprises the steps: carrying out the normalization and size alignment of two adjacent frames of images, and extracting the dense features of a fixed down-sampling rate through a shared weight convolution encoder; the two-frame features are sent to a multi-level feature enhancement module, an intra-frame modeling unit and a cross-frame interaction unit are cascaded and matched with channel reforming and residual error correction, and enhanced features are obtained; constructing a four-dimensional cost body on a low resolution, performing probability normalization along a target coordinate dimension, weighting a target coordinate grid according to a probability to obtain a corresponding coordinate, and subtracting the corresponding coordinate from a source coordinate to obtain an initial optical flow; and carrying out attention-guided space fusion on the initial optical flow and context and local correlation, sending the fused optical flow to a differential Mama-based autoregressive refinement module, carrying out iterative updating according to a small number of fixed steps, recovering to a target resolution through convex combination up-sampling, and outputting a final optical flow. According to the method, the optical flow field can be accurately estimated under the conditions of low complexity and low time delay.

The invention relates to a wellbore multiphase flow model numerical solution and gas-liquid distribution state inversion method and system, and belongs to the technical field of petroleum engineering, and the method comprises the steps: 1, constructing and training a physical information neural network for drilling wellbore multiphase flow dynamic simulation and overflow gas distribution state inversion; determining input and output of the physical information neural network; determining a loss function of the physical information neural network; training a physical information neural network; 2, designing an adaptive optimization algorithm, optimizing the final solution precision and convergence speed of the physical information neural network, and obtaining an adaptive physical information neural network; designing an adaptive activation function; designing a self-adaptive sampling mechanism based on residual errors; 3, based on the self-adaptive physical information neural network, numerical solution and gas-liquid distribution state inversion of the shaft multiphase flow model are achieved. According to the method, the problem that a traditional numerical method usually needs high-precision grid division and a large number of computing resources is effectively solved.

The invention relates to the technical field of unmanned aerial vehicle application and urban airspace management, in particular to an intelligent site selection method and system for unmanned aerial vehicle take-off and landing points in an urban building group, and the intelligent site selection system for the unmanned aerial vehicle take-off and landing points in the urban building group specifically comprises the following steps: S1, carrying out the multi-source heterogeneous data fusion and high-precision three-dimensional environment modeling; s2, fluid dynamics simulation and airflow field pre-calculation are calculated; s3, real-time meteorological monitoring and dynamic risk correction; s4, establishing a quantitative safety evaluation model and multi-objective optimization site selection; and S5, visual decision support and feedback learning. According to the scheme, by deeply fusing multi-source heterogeneous geographic information data and constructing a high-precision three-dimensional digital twinborn city environment, accurate simulation and risk assessment of an airflow field around a building group are realized, geometric, material and semantic information is automatically extracted by using oblique photography, laser point cloud and a building information model, and the construction efficiency is improved. A unified three-dimensional grid with physical attributes is formed, and a reliable basis is provided for subsequent fluid calculation.

The invention relates to the technical field of earthwork compaction, and discloses a pipe ditch backfilling and tamping system based on excavator modification. The system comprises an earthwork condition dynamic sensing module which captures a bucket tooth track, a hydraulic oil cylinder pressure pulse and a soil mass vibration spectrum in real time and combines a historical database to construct a model to output a theoretical compaction degree curve; a multi-source compaction difference analysis module performs three-dimensional deviation detection on the theoretical curve and the actual settlement volume data to generate a construction grid-level compaction difference tensor; the defect area association mapping module inputs the tensor into a geological topology analysis network, generates a loose defect propagation path probability cloud chart by combining soil parameters and identifies weak sections; and the tamping strategy self-adaptive configuration module automatically sets operation parameters according to the cloud picture, activates high-precision monitoring on a high-probability defect section, and applies a dynamic excitation force test on adjacent grids, so that intelligent management and control of the backfilling and compacting process are realized.

The invention relates to the technical field of cloth dyeing uniformity detection, in particular to a cloth dyeing uniformity detection method and system based on image analysis, and the method comprises the steps: building a three-dimensional optical response model according to the optical characteristics of a fluff cloth fiber material; calculating to obtain a villus shadow intensity distribution diagram according to the linear polarization degree image data, and calculating to obtain a theoretical artifact reflectivity distribution diagram through a three-dimensional optical response model according to the villus shadow intensity distribution diagram and the surface normal vector mapping data; extracting an actual measurement reflectivity distribution diagram from the hyperspectral image data, and performing differential operation on the actual measurement reflectivity distribution diagram and the theoretical artifact reflectivity distribution diagram to obtain a real dyeing component diagram; dividing villus unit grids on the real dyeing component graph, and calculating a spectral fingerprint variance value of pixels in each villus unit grid; and when the spectral fingerprint variance value exceeds a preset process tolerance threshold value, judging that the corresponding fluff unit grid has a real dyeing defect. And the identification precision of the dyeing defects of the fluff cloth is effectively improved.

The invention discloses a text and image bidirectional alignment method and system based on multi-hop parallel reasoning, and the method comprises the steps: analyzing and marking a text, and obtaining a multi-granularity text feature group; image generation is processed, grids and target output are combined into a multi-scale visual feature group, an alignment index table is established, a sub-target chain is constructed based on visual features, the position and the dependency relationship are recorded, and explicit constraints are injected into five elements; recalling the candidate area, generating an anchor point through verification and fusion, writing the anchor point into a cross-modal index, locally completing three-layer decoupling scoring based on anchor point geometry and the cross-modal index, and outputting a three-state evidence in combination with a threshold value; the method comprises the steps of generating an evidence set through geometric and semantic consistency calibration, generating cross-hop evidence according to a rule, weighting and pooling the evidence set, generating a shared vector and traceable meta-information, inputting a task head output result and generating an evidence list and an auditing path, and according to the method, local alignment, constraint verification and evidence accumulation are completed hop by hop. And high-precision, traceable and interpretable cross-modal correspondence is realized.

The invention relates to the technical field of 3D printing error compensation and precision control, and particularly discloses a printing comprehensive precision measurement method for 3D printing equipment, which comprises the following steps: designing a standard test piece containing various typical geometrical characteristics, and combining non-contact three-dimensional optical scanning and contact probe measurement means to measure the printing comprehensive precision of the 3D printing equipment. Spatial distribution data of printing errors are obtained in a controlled environment, a three-dimensional error field model with direction and amplitude information is constructed through point cloud registration and feature comparison, and based on error distribution features, the local resolution is dynamically adjusted by adopting a multi-level self-adaptive grid division strategy, so that a three-dimensional error field model with direction and amplitude information is constructed. A local error compensation model is established by combining tightly-supported radial basis function interpolation and a linear fitting method, a boundary consistency matching algorithm is introduced to realize multi-level model fusion, a unified global error compensation field is formed, an error offset vector field is embedded into a slicing process, point-by-point dynamic correction of a nozzle path is realized by using a trilinear interpolation algorithm, and the nozzle path is dynamically corrected. And the forming precision and the surface quality of the key structure are improved.

The present application relates to the technical field of mold structure design. Disclosed are a mold structure design optimization method and apparatus. The method comprises: performing parametric modeling on a three-dimensional model of a laser cutting die to obtain an adjustable parameter set; performing cutting die geometric feature extraction and feature classification to obtain a feature classification result; performing adaptive multi-scale mesh division to obtain a multi-scale finite element analysis model; performing multi-physics coupling analysis to obtain stress distribution data, deformation data and temperature field distribution data; performing variance analysis to obtain target impact parameters, and, on the basis of the target impact parameters, constructing a multi-objective optimization model; by means of a non-dominated sorting genetic algorithm, solving the multi-objective optimization model to obtain a Pareto optimal solution set; and determining, from the Pareto optimal solution set, target optimization structural parameters of the laser cutting die, thereby improving the optimization efficiency while ensuring the calculation accuracy, and achieving the overall performance improvement of the laser cutting die.

The invention relates to the field of mobile robot motion planning, and discloses a quadruped robot motion planning method and system based on height self-adaption. The method comprises the following steps: constructing 3D and 2D local obstacle maps according to coordinate transformation, and calculating a grid vertical distance through ray casting to generate a 2.5 D local obstacle map; determining an initial control sampling space by combining speed, acceleration and height constraints; discretizing a sampling space and simulation time, deducing a control value sequence and recursively calculating a local trajectory; then calculating a shaft alignment bounding box in a directed bounding box of the robot, screening grid units in the shaft alignment bounding box, comparing the height of a machine body with the allowable height of grids, and rejecting collision trajectories to obtain a feasible trajectory set; and finally selecting an optimal track by the evaluation function, extracting a control value and sending the control value to hardware for execution. According to the method, the 2.5 D local obstacle map containing height information is constructed, the four-dimensional control sampling space is designed, and the robot height self-adaptive adjustment is realized in combination with the collision detection and evaluation function.

The invention relates to the technical field of goods shelf detection, in particular to a self-detection method and device for goods shelf settlement, and provides the following scheme: obtaining a top view image through an image sensor arranged right above the top of a goods shelf, dividing the image into a plurality of grid units, and positioning a rectangular geometric shape by utilizing Hough transform; and screening a plurality of to-be-detected areas in combination with the edge features. For an area to be measured, homographic registration and ortho-rectification are carried out based on a reference image, a displacement field is obtained by adopting sub-pixel-level dense registration, and a geometric parallax component field corresponding to imaging parameters is obtained through robust estimation. And under the hypothesis of small deformation, inverting the parallax into a pixel normal distance, and carrying out weighted aggregation on the local region to obtain a local distance measurement result. And by iteratively combining adjacent grids, determining a settlement area boundary, and finally outputting a settlement detection result. Millimeter-level settlement quantification can be realized under a single-frame image, hardware transformation is avoided, and the method is suitable for automatic detection and long-term monitoring of multi-specification goods shelves.

The invention relates to the technical field of road engineering safety monitoring, in particular to an expressway slope crack identification method based on unmanned aerial vehicle laser point cloud visualization, which comprises the following steps: multi-source data collaborative acquisition: an unmanned aerial vehicle carrying a laser radar scanner and a high-resolution optical camera flies along a multi-angle combined route, and the unmanned aerial vehicle carries a laser radar scanner and a high-resolution optical camera; synchronously acquiring side slope three-dimensional laser point cloud data and an orthoimage sequence; data fusion preprocessing: denoising and filtering the data to generate an exposed slope triangular mesh curved surface model, and mapping textures to generate a high-precision live-action three-dimensional model; performing multi-dimensional feature fusion recognition, extracting curvature and texture features, inputting the curvature and texture features into a pre-training classification model, judging and outputting a crack pixel-level position; and carrying out visual output, superposing crack information rendering and generating a quantitative report containing the length and width of the spatial position. The method is high in coverage precision and identification accuracy, and provides a reliable basis for slope safety assessment.

Computer-implemented methods and systems for processing geometry replacements are disclosed. The methods include decoding / encoding a syntax element associated with a coding mode from / into a bitstream associated with geometry displacements; and reconstructing / converting, based on a coefficient configuration associated with the coding mode, a plurality of quantized transform coefficients from / to a plurality of zero-run length codes.

The present invention relates to a contour accuracy compensation method and system for a precision hot-press forming mold. The method comprises: delineating grids on a three-dimensional model of a hot-press forming mold to obtain mold surface grid data; performing curvature analysis to obtain a high-curvature region and a low-curvature region; performing high-density sampling on the high-curvature region, and performing low-density sampling on the low-curvature region, so as to obtain a sampling point set; using a coordinate measuring machine to perform three-dimensional coordinate measurement on the sampling point set to obtain surface contour data; performing comparative analysis on the surface contour data and a theoretical model to obtain a contour error distribution; on the basis of the contour error distribution, using an inverse distance weighted interpolation algorithm to perform interpolation operation on an entire mold surface to obtain a mold surface compensation amount distribution; and on the basis of the mold surface compensation amount distribution, correcting the three-dimensional model of the hot-press forming mold to generate a compensated mold processing model. The implementation of the present invention realizes intelligent and automated contour accuracy compensation.

A device for processing frame data may be configured to identify one or more semantic characteristics for the frame data, wherein the frame data comprises a plurality of frames, each frame of the plurality of frames being acquired for a same scene and by a different frame source of a plurality of frame sources; extract features from each respective frame of the plurality of frames; determine a non-uniform sampling pattern of the plurality of frames based on the one or more semantic characteristics; and project, using the non-uniform sampling pattern, a portion of the extracted features into a bird's-eye-view (BEV) space having a grid structure to generate a fused set of BEV features.

The invention provides a grouting simulation method and system based on time sequence interaction and self-adaptive grid reconstruction, and relates to the technical field of grouting engineering.The grouting simulation method comprises the steps that monitoring data of the grouting construction process are obtained, the monitoring data are input into a grouting diffusion prediction model, a grouting pressure prediction value is output, and a series of prediction responses are conducted based on the grouting pressure prediction value. Obtaining a grouting pressure predicted value, a boundary point set of the grouting diffusion area, the area and the volume of the grouting diffusion area and a diffusion response result of the pressure distribution diagram; constructing a geometric model of the grouting area based on the diffusion response result, and performing grid unit division and grouting diffusion area mapping on the geometric model; and performing local grid encryption and reconstruction on the grid units according to a density control rule to obtain a structured grid data model, adaptively updating the structured grid data model by using real-time monitoring data, and performing real-time visual grouting optimization control. According to the invention, the high-precision prediction response of grouting is improved.

The invention belongs to the technical field of geometric pretreatment in computer aided engineering (CAE), and particularly relates to a dirty geometry restoration method for a complex three-dimensional geometric model, which comprises a dirty geometry detection and restoration module based on heuristic rules and geometric topology analysis. By means of a multi-model collaborative alignment and bonding mechanism, high-precision assembly between parts is achieved through geometric feature matching and adjacent domain self-adaptive adsorption; acquiring material attributes provided by the simulation platform, and performing accurate cutting and boundary reconstruction on an intersection domain based on an intersection domain intelligent segmentation algorithm of the material attributes to ensure correct mapping of boundary conditions of a physical field; a geometric Boolean processing engine iterative learning mechanism of a general merging algorithm is integrated, and a high-quality model for simulating a grid is generated through multi-round iterative optimization. According to the method, double challenges of internal dirty geometry of a single model and derivative dirty geometry of intersection / adjacent areas among multiple bodies are solved, and key physical attributes and topological continuity of electromagnetic signal links are ensured and are completely reserved during repair.

A method performed by an apparatus for controlling autonomous driving of a vehicle is introduced. The method may comprise generating, based on a segmentation model processing point cloud data, a first semantic grid map, generating, based on an object detection model, a second semantic grid map, adjusting a probability regarding whether occupancy exists for an element included in each grid of the first semantic grid map and the second semantic grid map, and generating a fused grid map by determining, as a representative label, at least one label corresponding to a highest value among final probabilities of the at least one label, wherein the final probabilities are determined based on whether the at least one label matches the element, outputting, based on the fused grid map, a signal, and controlling, based on the signal, autonomous driving of the vehicle.

The invention relates to a territorial space planning data monitoring evaluation method and system, and the method comprises the steps: obtaining multi-modal data, constructing an atmospheric diffusion model based on the multi-modal data, reversely positioning a pollution source, and obtaining a pollutant responsibility matrix; carrying out space grid fusion calculation through the pollutant responsibility matrix and the carbon sink data to generate a carbon source-carbon sink distribution diagram representing a territorial space carbon balance pattern; based on the regional characteristics of the carbon source-carbon sink distribution diagram, generating a territorial space carbon planning scheme through a low-carbon guiding algorithm; constructing a disaster model based on the multi-modal data, and carrying out space coupling analysis on a disaster risk area and a high-carbon sink potential area output by the disaster model to obtain a land space carbon restoration scheme; a digital twinborn platform is constructed according to multi-modal data, an atmospheric diffusion model and a disaster model, an expected carbon sink increment value of a land space carbon planning scheme is deduced and verified through the digital twinborn platform, and iteration of the implementation scheme is carried out.