235 results about "Boundary data" patented technology

The invention provides a building interior design layout optimization method, and relates to the technical field of indoor modeling and layout optimization, and the method comprises the steps: obtaining building structure boundary data and current situation layout information, constructing an indoor three-dimensional space model, and completing the marking of node passing attributes and a spatial topological structure. On the basis, crowd behavior data of a daily scene and an emergency scene are collected, behavior characteristics such as walking speed, obstacle avoidance response and congestion sensitivity are extracted, and a walking characteristic model used for simulating the individual motion trend is established. And performing multi-scene simulation under a daily event and an emergency evacuation event by using the walking feature model, calculating performance indexes such as passing time, local congestion degree, key node congestion probability and total evacuation time, and identifying a congestion sensitive area. And further constructing a multi-target evaluation model including traffic efficiency, congestion degree and evacuation performance, and performing global optimization on layout adjustable parameters by adopting an algorithm to obtain a candidate layout scheme set.

The invention discloses a regional carbon emission prediction method and system based on deep learning, and belongs to carbon emission prediction. The method comprises the following steps: acquiring historical carbon emission time sequence data and multi-dimensional constraint boundary data of a target area, and mapping the historical carbon emission time sequence data into an input feature vector; outputting an initial future carbon emission evolution trajectory vector; identifying and extracting a constraint violation dimension; constructing an input feature compensation tensor; generating an updated input feature vector; inputting the updated input feature vector into the depth space-time prediction model again for recursive prediction; and outputting a target carbon emission trajectory vector meeting the multi-dimensional constraint boundary data and a corresponding feature adjustment parameter set. According to the method, by automatically analyzing the multi-dimensional management constraint and fusing the multi-dimensional management constraint into the iterative optimization closed loop of the prediction model, the problem that the prediction model in the prior art only optimizes mathematical statistical errors and is seriously disjointed with multi-dimensional targets such as cost control and path feasibility in real management is solved.

The invention relates to the technical field of city cadastral data analysis, and discloses a city update district boundary division method and system based on cadastral data, and the method comprises the steps: collecting the division associated cadastral data of a target city update district, and employing an improved DTW algorithm to obtain a city update district boundary; the method comprises the following steps: screening current situation boundary effective points and newly-added candidate points with history continuity from current situation measured data, extracting spatial features and ownership features for fusion, constructing a feature matrix by using a fusion feature vector, constructing a spatial ownership double-constraint graph neural network, predicting a final boundary point set of a target city update area, and obtaining a target city update area. And generating a final land parcel boundary. Therefore, by introducing the improved DTW algorithm and the spatial ownership double-constraint graph neural network, while accurate association of historical and current boundary data is established, joint optimization of spatial rationality and ownership rationality is realized by utilizing double-constraint feature fusion, and the division precision and division efficiency of the urban update district boundary boundary are improved.

The invention relates to a crop plot identification method and system based on time sequence vegetation characteristics, and the method comprises the steps: constructing a normalized difference vegetation index time sequence according to a multi-temporal satellite remote sensing image, and generating a crop probability distribution diagram through a crop classification model; performing connected domain analysis on the crop probability distribution map, extracting the center of gravity of an effective connected domain as a forward attention point, scanning the crop probability distribution map by using a sliding window, and generating a reverse attention point; based on the forward attention point and the reverse attention point, segmenting the high-resolution remote sensing base map through a visual segmentation model, generating a candidate mask set, and screening to reserve a mask with the maximum area as a land parcel segmentation mask of the forward attention point; and combining all the plot segmentation masks to generate a crop plot identification graph, and converting the boundary of each plot segmentation mask into a geodetic coordinate sequence to obtain plot vector boundary data. The method improves the recognition accuracy, and achieves the automatic and precise segmentation of the boundary of the land parcel.

The invention relates to the technical field of intelligent water conservancy and automatic control, in particular to a polder area multi-station water conservancy data real-time collection and intelligent fusion processing method and system, and the method comprises the steps: a multi-dimensional collection system construction step: collecting time sequence state, fluid field and environment boundary data, and executing time base unified cleaning; an ideal model construction step: constructing an ideal water tank model based on the law of conservation of mass and generating an ideal water level change curve; a parameter injection simulation step: generating a simulation fault water level curve according to injection efficiency attenuation and medium leakage parameters; a double-track difference calculation step: respectively carrying out difference on actual measurement and simulation data and an ideal curve to generate real and theoretical residual vectors; a similarity judgment and control step: calculating sequence similarity to judge a real physical fault or sensor data noise, and generating a fusion control instruction; according to the invention, the technical problem of distinguishing the noise of the sensor from the real physical fault is effectively solved, and false alarm or missing alarm is avoided.

The invention relates to a two-dimensional and three-dimensional boundary point association method based on improved boundary point coding and a medium, and the method comprises the steps: carrying out the preprocessing of original land parcel red line data, sequentially numbering land parcels, converting all the land parcels into plane boundary point elements, determining a first boundary point in each plane boundary point element, processing each land parcel into a clockwise land parcel, and carrying out the coding of the clockwise land parcels. Performing two-dimensional boundary point continuous numbering on all vertexes of the land parcel, taking the land parcel after encoding the two-dimensional boundary points as a two-dimensional surface element, and converting the land parcel into a land parcel three-dimensional stereoscopic model comprising three-dimensional boundary points, boundary lines and boundary surfaces; and continuously numbering all the three-dimensional boundary points in sequence by using a cross section analysis method to obtain a land block after coding the three-dimensional boundary points, and establishing an association relationship between the three-dimensional boundary points with successfully matched coordinates and the corresponding two-dimensional boundary points. Therefore, automatic coding of the three-dimensional boundary points of the land parcel red line data and automatic association between the two-dimensional boundary points and the three-dimensional boundary points are realized, and the three-dimensional boundary point management efficiency in land parcel management is improved.

The invention relates to the technical field of terrain information processing, in particular to an intelligent decision-making system and method for excavation and filling parameters of a reservoir area of a pumped storage power station. The method comprises the following steps: acquiring topographic data of a reservoir area; determining elevation distribution characteristics according to the topographic data of the reservoir area; performing excavation and filling boundary analysis based on the elevation distribution characteristics to obtain excavation and filling boundary data; performing earth-rock volume calculation according to the excavation and filling boundary data to obtain earth-rock balance data; identifying the section excavation and filling unbalance degree based on the earth-rock balance data to obtain excavation and filling deviation data; performing slope stability analysis according to the excavation and filling deviation data to obtain slope stability data; performing leakage risk prediction according to the slope stability data to obtain leakage risk data; and identifying a seepage path according to the seepage risk data. According to the method, excavation and filling parameter optimization is realized based on a topographic information processing technology, and the reservoir area construction decision efficiency is improved.

The invention provides an automatic driving operation method and system of a crawler harvester and a storage medium, and relates to the technical field of agricultural machinery automation, and the method comprises the following steps: obtaining boundary data of a harvesting area in a target land parcel; generating a spiral global operation path of the harvesting area from outside to inside based on the boundary data, wherein the path comprises a plurality of operation line segments which are connected in sequence; controlling the crawler harvester to perform straight running operation along the current operation line segment of the spiral global operation path through a preview tracking control strategy; monitoring pose data of the crawler harvester; when it is recognized that the crawler harvester arrives at a field end point of the current operation line segment based on the pose data and harvesting operation of the field end point is completed, the crawler harvester is controlled to turn and feed lines, and the crawler harvester is made to turn to the next operation line segment; and repeating the straight driving operation and the turning line feed until the harvesting operation of the target plot is completed. According to the method, the operation continuity and the operation efficiency are improved on the premise that full coverage and field edge boundary constraints are met.

The invention provides a nuclear power plant thermal discharge dynamic change prediction analysis method, and relates to the technical field of data processing, and the method comprises the steps: collecting a temperature observation data set, extracting a temperature maximum value sequence and a temperature minimum value sequence in an equal-tide period, calculating a wave amplitude stable factor, extracting a plurality of trend inflection points of a temperature change first-order derivative curve, and calculating the temperature change first-order derivative curve. The method comprises the following steps: determining thermal expansion boundary candidate areas caused by thermal drainage, evaluating a time interval and amplitude difference between a lag response inflection point in each thermal expansion boundary candidate area and a previous dominant temperature rise point to obtain a thermal lag offset value, extracting a boundary sensitive area, performing multipoint communication fitting, determining a maximum space extrapolation boundary influenced by the thermal drainage effect, and performing thermal expansion on the maximum space extrapolation boundary. And carrying out trajectory tracking and change direction regression on the extrapolation boundaries at multiple different time points, and identifying a heat disturbance movement trend to obtain dynamic evolution data. The method can identify the diffusion trend of the warm discharged water and predict the temperature change.

The invention discloses a historical block courtyard boundary intelligent extraction and semantic analysis method based on space-air-ground multi-dimensional sensing fusion, and the method comprises the steps: data fusion, the analysis of existing data, and the fusion of multivariate heterogeneous data, and the multivariate heterogeneous data comprises satellite remote sensing, unmanned plane oblique photography and ground mobile laser point cloud. Constructing a cross-scale courtyard enclosure data cube through the fused data, cutting the data cubes of different scales into a plurality of regions, constructing a three-dimensional space cube through the cut regions, and collecting cultural feature information related to historical courtyards through the three-dimensional space cube; according to the method, satellite remote sensing, unmanned aerial vehicle oblique photography and ground mobile laser point cloud are fused through a multi-source heterogeneous data adaptive fusion mechanism, a cross-scale courtyard enclosure data cube is constructed, and a data weighted registration algorithm based on feature significance is proposed. The problems of data missing and registration deviation caused by high building density and serious shielding in historical blocks are solved.

The invention provides a vehicle turning path planning method and device for irregular land parcels, and is applied to the technical field of path planning, and the method comprises the steps: carrying out the initialization of a pheromone field based on the boundary data of a geographic information system and internal obstacle data, and constructing a rasterized map for representing a passable region; based on the current state of the vehicle, determining the minimum distance of obstacles in the surrounding environment of the target vehicle; based on the real-time movement speed, the minimum turning radius of the target vehicle is determined; determining a dynamic corridor parameter of the target vehicle based on the minimum distance and the minimum turning radius of the surrounding obstacle; based on the dynamic corridor parameters and the pheromone field of the rasterized map, generating a turning point probability density field of the target vehicle, and sampling the turning point probability density field to obtain a turning point set; and constructing a turning path of the target vehicle based on the turning point set, and determining the turning cost of the turning path. According to the invention, Pareto optimization of energy consumption and efficiency in a complex scene can be realized.

Methods and systems are configured for accessing a three-dimensional (3D) facies model including a set of layers, each layer including boundaries data representing initial facies boundaries for a set of facies represented in that layer; accessing geological constraints data representing facies trends for the set of facies represented in the facies model; for each layer: for each facies type in the layer, determining, for a portion of the layer, a distance from the portion of the layer to a facies boundary for that facies type in the layer; and based on the distance for each facies type and the facies trends represented in the geological constraints data, determining a facies probability value; stacking the layers each including facies probability values for each facies type represented in that layer; simulating facies trends for each facies type; and generating a 3D facies trend model including the simulated facies trends.

The invention discloses an urban village identification method based on a graph neural network and multi-source geographic big data, and relates to the technical field of geographic images, and the method comprises the steps: obtaining remote sensing data, social perception data and building footprint data of an urban village; based on road network trajectory data, cutting built-up area boundary data through a hierarchical buffer area strategy to obtain a basic evaluation unit; the streetscape image data, the satellite image data, the interest point data, the building attribute data and the building form data are preprocessed respectively, and visual features, social economic features and building form features are constructed; constructing a graph network structure of the graph neural network model; and according to the instance sample group, in combination with a graph network structure of the graph neural network model, constructing and training a GraphSAGE model so as to improve the recognition probability of the villages in the city. According to the method, the spatial interaction and regional relation between the network spatial structure and the multi-dimensional attributes are effectively understood through the GNN.

The invention belongs to the technical field of space geodetic survey observation data inversion regional land water reserve change, and provides a method and related equipment for inversion of land water reserves based on a Slepian basis function combined with GNSS three-dimensional deformation, and the method comprises the steps: obtaining vertical and horizontal deformation observation values of GNSS through simulation; determining a Slepian primary function of the target area according to the boundary data and a preset maximum expansion order, and further determining a function relationship between a Slepian coefficient of GNSS three-dimensional deformation and a Slepian coefficient driven by mass load change; determining an observation equation according to the function relationship, and resolving the observation equation by adopting least square joint adjustment; and according to the Slepian coefficient driven by the mass load change, carrying out inversion on the regional land water reserves of the target region to obtain a regional land water reserve change result. The method has the beneficial effect that the precision and efficiency of regional land water reserve inversion are improved.

The steam generator state real-time monitoring method based on artificial intelligence belongs to the field of artificial intelligence and comprises the following steps: S1, data acquisition and labeling; S2, sample generation is performed by using a quantum generative adversarial network based on random projection embedding to realize data expansion; S3, the expanded data is input into a feature extraction model to perform training of the feature extraction model, and a five-layer fully connected neural network is used for feature extraction; S4, the feature-extracted data is input into a feature dimension reduction model to perform training of the feature dimension reduction model, and a self-encoding neural network algorithm based on local preserving projection is used to realize feature dimension reduction; S5, the dimension-reduced data is input into a classifier to perform training of the classifier model; and S6, steam generator state recognition and monitoring are performed.The steam generator state real-time monitoring method based on artificial intelligence can solve the problems of insufficient sample quantity and lack of data diversity and enhances the robustness of the model when the model has noise or fuzzy classification boundary data.

The invention provides a nuclear fuel assembly grabbing positioning and deviation correction method and system based on industrial vision. The method comprises the steps of obtaining multi-view image data of a target nuclear fuel assembly and structured light deformation image data under a corresponding view; extracting an outer contour boundary of the target nuclear fuel assembly in a three-dimensional space based on the multi-view image data and the structured light deformation image data to obtain initial outer contour boundary data; performing pose positioning based on the initial outer contour boundary data in combination with original design data of the target nuclear fuel assembly to obtain a current pose parameter of the target nuclear fuel assembly in a three-dimensional space; performing deviation analysis based on the current pose parameter in combination with a preset standard pose parameter to obtain current deviation data and a corresponding deviation analysis result; and if the deviation analysis result is correctable deviation, performing instruction generation based on the current deviation data to obtain a pose correction instruction. The problem that the correction effect is poor in an existing method is solved.

The invention belongs to the technical field of image processing, and particularly relates to a geological disaster risk area dynamic updating method based on slope unit automatic segmentation. Comprising the following steps: 1, acquiring digital elevation model raster data covering a target area and remote sensing image raster data spatially aligned with the digital elevation model raster data, and outputting slope unit vector data; 2, acquiring disaster-bearing body vector data, performing spatial superposition on the disaster-bearing body vector data and the slope unit vector data, and combining outer boundaries of slope units of all geological disaster risk areas to generate risk area vector boundary data; 3, generating new year risk area vector boundary data based on the new year data; and updating the risk area vector boundary data of the last year based on the risk area newly-added area and the risk area reduced area. According to the method, the slope unit division precision, the disaster-bearing body exposure description capability and the timeliness of risk area range updating are remarkably improved.

The invention discloses an intelligent control method for collaborative operation of a concrete leveling robot, and the method comprises the steps: obtaining the position state updating data of multiple devices according to an initial operation region division result, carrying out the dynamic distribution of tasks in combination with the workload and mobility of each device, and determining the responsible region and operation sequence of each device; according to the operation rhythm control parameters, operation area boundary data between adjacent devices are obtained, the elevation deviation between adjacent areas is analyzed according to the boundary elevation connection requirement, and the boundary processing priority and the adjustment scheme are determined; according to the boundary processing priority, obtaining operation progress difference data between the devices, and if the progress of a certain device is lagged, dynamically updating a task allocation strategy through data interaction frequency adjustment to obtain an optimized device operation path; and according to the updated region boundary data, obtaining the latest state information of multi-device cooperation, aiming at a region seamless connection target, adjusting the operation rhythm between the devices, and determining a final elevation consistency control parameter.

The invention discloses a pump set model selection method based on actual working condition delay simulation and a storage medium, and the model selection method takes actual operation historical boundary data of a pump room to be transformed as a basis of pump set design, and breaks away from a traditional single working condition design situation, so that the selected pump set is closer to an actual operation working condition. And the optimal frequency combination meeting the working conditions and the corresponding operation power serve as the calculation basis of future operation of the pump set, the expected saving cost is calculated through long-time-period simulation, and the appropriate water pump model number combination is selected. Compared with the existing technical scheme, the model selection method provided by the scheme not only can meet the standard design requirement, but also ensures that the pump set operates as efficiently as possible under the daily condition.

The application provides a kind of unmanned aerial vehicle map spot investigation route planning method and device, wherein the method comprises: obtaining the vector polygon boundary data of the region to be investigated, and constructing target surface and planning surface with different task semantics and geometric characteristics;According to the ground coverage size of a single photo calculated by camera parameters and ground sampling distance, classify the map spot;According to the determined map spot type, adopt the matching route generation strategy to generate the classified route;Based on the classified route, generate the discrete flight point set of unmanned aerial vehicle, and decouple the action arrangement of spatial position and evidence attitude.Through the application, the flight and photographing time of unmanned aerial vehicle in non-target area is reduced, the coverage efficiency is improved, and the problem of poor efficiency and accuracy of map spot investigation in the prior art is solved.

The invention provides a hydraulic structure health monitoring method fusing physical constraints and a time sequence large model, relates to the field of hydraulic structure monitoring, and solves the technical problems that an output result violates a physical law and a hydraulic monitoring result is inaccurate due to lack of physical consistency in the prior art. The method comprises the following steps: collecting various sensor monitoring data of the hydraulic structure; inputting the monitoring data into a pre-trained prediction model; through a physical constraint module of the prediction model, taking environmental load data, material parameter data and geometric boundary data of the hydraulic structure as input, embedding a mechanical equation describing behaviors of the hydraulic structure into a loss function of the prediction model, and outputting a structure response prediction value and a structure safety threshold value; through a time sequence prediction module of the prediction model, taking monitoring data as input, and outputting a structure state prediction value of a future time period and a confidence interval of the prediction value; and based on an output result of the prediction model, generating a hydraulic health state assessment result and early warning information.

The application discloses a sea area change monitoring method, device and equipment and a storage medium, and relates to the technical field of sea area monitoring. The method comprises the following steps: performing super-resolution reconstruction based on target sea area boundary data at a set monitoring frequency to obtain remote sensing images of the target sea area; extracting scattered planar vector patches of culture facilities from the remote sensing images; determining culture range patches of the culture facilities according to the outer convex surface boundary geometry of the midpoint element patch in the scattered planar vector patch; analyzing NetCDF sea current multidimensional data, generating format grid sets including different direction flow rates and wind speed value vector fields according to the step length of the set monitoring frequency; determining a regression coefficient map according to the spatial relationship between the different direction flow rates and the wind speed, and monitoring the culture facilities by using the regression coefficient map. The application takes into account the influence of flow rates, flow directions and wind speeds on the position distribution of the culture facilities, and can efficiently and accurately monitor the temporal and spatial changes of the culture sea area by combining the analysis of the NetCDF data.

The invention relates to the technical field of electricity market day-ahead prediction, in particular to an electricity market day-ahead price difference prediction method and related equipment, and the method comprises the steps: firstly obtaining electricity market boundary data, meteorological observation data and line maintenance plan data of a target area, and carrying out the preprocessing to form multi-source feature input data; and then, inputting the data into an LASSO regression model for price difference prediction. The model comprises a dynamic penalty factor generator and a near-end gradient solver. The dynamic penalty factor generator dynamically adjusts penalty factors based on multi-source features and predicted price difference in the last time period. And the near-end gradient solver adopts a near-end gradient algorithm, combines a Nesterov acceleration strategy and convergence threshold judgment conditions, iteratively solves optimal parameters, and finally outputs a day-ahead-real-time price difference prediction result. According to the method, through dynamic adjustment and efficient solution, the prediction accuracy is improved.

The invention discloses a flood routing simulation method and device for a multilayer underground building. The flood routing simulation method comprises the following steps: constructing a logical topology network structure of a multilayer underground building, wherein single-layer two-dimensional plane geometric information comprises height distribution of floors of floors; based on the constructed logical topology network structure, aiming at each floor in the multi-floor underground building, executing the following contents: determining configuration data of the floor; associating boundary data with the determined configuration data; calling a two-dimensional hydrodynamic numerical simulation engine based on the determined configuration data, and determining floor submerging process data; judging whether the floor is the last floor of the multi-floor underground building or not; under the condition that the floor is not the last floor of the multi-floor underground building, inflow boundary data of the next floor corresponding to the floor are determined, and the inflow boundary data indicate the change condition of flood flowing into the next floor from the floor along with time. Therefore, the flood routing simulation of the multi-layer underground building is realized.

Example methods and systems are provided for virtual conferencing based on geofences. A video conference provider or a client device establishes an event streaming session associated with an event at a location via a virtual conference application installed on the client device. The video conference provider or the client device detects that the client device has entered one or more geofences associated with the location based on geofence boundary data associated with the one or more geofences and location data associated with the client device during the event streaming session. The video conference provider or the client device executes at least one rule associated with streaming within the one or more geofences to control one or more media components associated with the client device.

This invention proposes a method for correcting abnormally high values ​​in remote sensing satellite nighttime light imagery, belonging to the field of remote sensing image processing technology. Addressing the problem of low accuracy in existing nighttime light image correction techniques, this invention acquires remote sensing satellite nighttime light imagery and preprocesses it; acquires target area boundary data and adjusts the preprocessed light imagery; statistically analyzes all light values ​​in the adjusted light imagery to identify abnormal light value intervals; performs isolated analysis on the light values ​​within the abnormal intervals to determine abnormally high values; classifies the abnormally high values ​​into at least one distribution combination based on their distribution pattern; uses a local mean fitting method to calculate correction values ​​based on the normal light values ​​surrounding the abnormally high values; and replaces each abnormally high value with its corresponding correction value to generate a corrected nighttime light image of the target area. This invention achieves high accuracy in nighttime light image correction.

In order to solve the problems of the prior art, the truck safety detection system is provided, which comprises a carrier, a second scanning laser sensor, a cargo safety inspection system and a control system. After the target vehicle to be inspected enters the second scanning field of the second scanning laser sensor to form an effective trigger, the control system obtains the distance data of each scanning point of the surface of the target vehicle to be inspected relative to the second scanning laser sensor, connects the distance data to form a vehicle body data model, and analyzes the vehicle cab based on the vehicle body data model. The cargo safety inspection system is controlled to be opened or closed according to the analysis result of the vehicle cab. The application mainly forms a boundary data model of the target vehicle to be inspected based on the data point cloud of the scanning laser sensor to analyze and judge, has the advantages of high precision, high stability, strong anti-interference ability and high adaptability to vehicle types, and has low requirements for the deployment site.

This pipeline damage prediction system uses a computer to predict pipeline damage due to a natural disaster, the pipeline damage predication system comprising: a basic data storage unit that stores pipeline attribute data indicating an attribute of a pipeline, stores ground characteristic data which indicates a characteristic of the ground in which the pipeline is buried and which includes at least liquefaction data, ground boundary data, or terrain modification data in units of polygons in a map information system GIS, and stores damage data indicating the degree of damage due to a natural disaster occurring in the past; and a damage prediction calculation unit that generates damage prediction information in which damage occurring in the pipeline is predicted on the basis of the pipeline attribute data, the ground characteristic data, and the damage data stored in the basic data storage unit.

The invention discloses a multi-class-group ecological safety operation space determination method and system for a large estuary delta and a storage medium. Relates to the technical field of ecological environment protection and wetland resource management. The method comprises the following steps: acquiring multi-source spatio-temporal data of a target estuary delta, preprocessing, constructing a multi-period inning boundary database, analyzing a distance effect, calculating an inning strength index, determining an optimal hysteresis period through hysteresis analysis, constructing three types of accumulation indexes, fitting a response relation curve of the three types of accumulation indexes and biodiversity, and determining the biodiversity of the target estuary delta. Identifying non-linear inflection points on the curve to determine a threshold position; and constructing a biodiversity response surface according to the analysis result, and further identifying the ecological operation space. According to the method, data of multi-stage remote sensing, multi-class biodiversity monitoring and the like and a multi-model joint calculation framework are combined, the lag response, the cumulative effect and the threshold features of the multi-class biocenosis are quantitatively recognized, an ecological safety operation space recognition system is formed, and support can be provided for ecological planning, management and decision making.

This invention discloses a method, device, and computer-readable storage medium for dynamically adjusting the output value of a joystick. The method includes: acquiring physical boundary data of the joystick, which reflects the physical limit modulus of the joystick at different physical angles; in response to a mapping mode switching command, acquiring target boundary data matching the command, which defines the effective output area of ​​the joystick in the current mode; constructing a target mapping rule for the joystick based on the physical boundary data and the target boundary data; and dynamically stretching or compressing the real-time physical modulus of the joystick using the target mapping parameters in the target mapping rule when the joystick is working, so that the physical output of the joystick accurately matches the target effective output area. This invention enables a single joystick to seamlessly switch between multiple output feel and boundary shape instantly, achieving a high-precision customized control experience across scenarios while shielding underlying physical errors.