27 results about "Environmental model" patented technology

The invention provides a water environment model coupling data processing method and system, and relates to the technical field of hydrology and water quality monitoring. The method comprises the following steps: determining a soil permeability characteristic descending trend and estimating an uncertainty range of a runoff coefficient; obtaining source model data according to the uncertainty range of the runoff coefficient by using a regional pollution production and convergence model; using the one-dimensional river network model to obtain error information according to the source model data, and outputting prediction data; and determining a prediction deviation mode by comparing the prediction data with the real-time monitoring data, and correcting parameters of all related models in the whole model chain. The method aims at solving the technical problem that the permissible discharge amount set based on a three-model coupling system does not conform to the actual absorption capacity of a water body due to continuous nonlinear deviation of river network model prediction and actually measured water quality data in the three-model coupling system, and accurate analysis of the urban pollution load and water environment quality response relation is achieved. And real-time and self-adaptive adjustment of the permissible emission amount is carried out.

The invention relates to the technical field of environment model construction, in particular to a data and knowledge fusion driven mine integrated modeling method and system. The method comprises the following steps: firstly, preprocessing multi-source heterogeneous data to establish a unified data set, and constructing an object-attribute-environment three-domain associated mine knowledge graph based on physical space information; then, initial geometric models of the earth surface, the ore body, the roadway and the like are constructed respectively, and mapping is established between the models and the atlas; performing forced geometric constraint and logic optimization on the initial model by emphatically utilizing semantic rules in the atlas, and automatically correcting space conflicts; and finally, realizing multi-element space integration under a unified coordinate system. According to the method, deep fusion of geometric reconstruction and geological semantics is realized, the problem of model logic deficiency is effectively solved, a high-precision three-dimensional model with dynamic evolution ability and logic self-consistency is constructed, and reliable support is provided for mine intelligent management.

The application provides an indoor space environment control method based on an optimization algorithm and related equipment, and the method comprises the following steps: constructing an indoor comprehensive environment model by combining historical equipment control parameters and historical space environment data; constructing a comprehensive target function; creating a state space of an ant colony optimization algorithm and generating constraint conditions of the ant colony optimization algorithm; taking the comprehensive target function as an algorithm optimization target, generating an initial equipment control strategy of an environment control device based on the indoor comprehensive environment model and using the ant colony optimization algorithm; taking an optimal parameter interval as a strategy initial solution of a model predictive control strategy, generating a strategy prediction result by the model predictive control strategy based on the indoor comprehensive environment model; and updating algorithm parameters of the ant colony optimization algorithm according to the strategy prediction result and generating an optimal equipment control strategy of the environment control device. The application has the effect of meeting the environmental experience comfort of users on the basis of the lowest energy consumption.

The application provides a water environment model coupling data processing method and system, and relates to the technical field of hydrology and water quality monitoring. The method comprises the following steps: determining the downward trend of soil permeability characteristics and estimating the uncertainty range of runoff coefficient; using a regional source-sink pollution model, obtaining source model data according to the uncertainty range of runoff coefficient; using a one-dimensional river network model, obtaining error information and outputting prediction data according to the source model data; and determining the prediction deviation mode by comparing the prediction data and real-time monitoring data and correcting the parameters of all related models in the whole model chain. The method aims to solve the technical problem that the prediction of the river network model deviates from the actual measurement data in a nonlinear manner in a three-model coupling system, which ultimately leads to the inconsistency between the permitted discharge amount set based on the system and the actual water body absorption capacity, and to realize the accurate analysis of the response relationship between the urban pollution load and the water environment quality and the real-time and self-adaptive adjustment of the permitted discharge amount.

Environment sensing system, comprising at least one sensor (10) for providing location data (12) about objects (18), wherein the location data (12) includes velocity data, and comprising a computational means (14) for converting the location data (12) into an environment model (16) that represents kinematic object data of the objects (18) and assigns an object (18) to a respective object class (K), wherein the computational means (14) is conditioned to preferentially output environment models (16) in which, for an object (18) corresponding to at least one predefined object class (K), at least one predefined physical relationship of the object data to location data (12) assigned to the object (18) is better satisfied for those location data (12) assigned to the object (18) that correspond to a predefined association criterion than for the totality of the location data (12) assigned to the object (18).

The invention provides a robot sampling planning method and system based on environment extreme value position estimation, and relates to the technical field of robot control, and the method comprises the steps: building a model for a to-be-monitored environment through a Gaussian Markov random field, and mapping sampling points in the environment into random variables in an environment model; calculating mutual information values of each non-sampling point and other non-sampling points based on the environment model; according to the observation value of the sampled point, obtaining an environment extreme value position estimation result through Gaussian process fitting and a Kriging estimation method; according to the mutual information value of the non-sampling point and an extreme value position estimation result, a next active sampling point is obtained through a probability decision-making method fusing mutual information and a spatial distance; based on the Gaussian Markov random field and the sampling information gain, the accuracy and rapidity of robot sampling planning are improved.

The invention discloses a raft culture-based marine product typhoon disaster risk assessment method and a storage medium, and the method comprises the steps: assimilating multi-source actual measurement data to an environment model through a data assimilation algorithm, and simulating an environment field of a target culture sea area according to the assimilated and corrected environment model; applying the environmental load corresponding to the environmental field to a structure model of the raft culture structure for dynamic response analysis, and calculating a structural strength index according to an analysis result; calculating a vitality index of the marine product according to a preset environment factor; and according to the structural strength index, the vitality index of the marine product and the disaster-inducing factor, determining the risk level of the valve type culture structure through a random forest model. According to the invention, comprehensive and objective risk assessment can be realized, and the assessment accuracy can be improved.

The invention relates to a coastal area composite network stability and carbon neutralization capability cooperative improvement method, and belongs to the field of ecological informatics and environment modeling. According to the method, firstly, metabolism subjects are divided based on multi-stage land utilization data, artificial carbon emission and natural carbon sink of each metabolism subject are evaluated, a carbon metabolism path is determined according to the area difference of land types before and after land utilization change and the carbon income and expenditure level difference of unit area, a carbon metabolism network is constructed, and key regulation and control nodes are identified; and by simulating different development scenes, dynamically evaluating the change rule of the stability and the carbon neutralization capability of the composite network, and finally forming a space planning and policy intervention scheme for synergistically improving the stability and the carbon neutralization capability of the composite network. According to the method, the crossing from static evaluation to dynamic optimization regulation is realized, the perspectiveness and scientificity of management decision are effectively improved, and the method is of great significance to guarantee the sustainable development of the coastal area.

This invention relates to the field of robotics technology and discloses a large-model-driven method and system for navigation and autonomous path planning of a composite robot. The method includes: collecting environmental data through multimodal sensors; inputting the data into a visual-language large model (VLM) to construct a holistic environmental model containing geometric, semantic, and dynamic object information; parsing high-level natural language navigation instructions using the VLM and generating navigation target points based on the holistic environmental model; and finally, coordinating the robot's body movement trajectory and end effector action sequence based on the model and target points, and driving their execution. This invention, by introducing a large model for holistic environmental modeling and task parsing, solves the problems of weak environmental understanding and unnatural human-computer interaction in traditional robot navigation technologies. It achieves deep perception of complex dynamic environments and autonomous planning of high-level instructions, significantly improving the intelligence level and operational efficiency of composite robots in real-world scenarios.

In some implementations, a method includes obtaining environmental data corresponding to an environment. The method includes determining that the environmental data corresponding to the environment includes environmental data that corresponds to a first portion of an object that represents a sub-portion of the object and not an entirety of the object. The method includes generating a plurality of candidate point clouds for a second portion of the object based on the environmental data corresponding to the first portion of the object. The plurality of candidate point clouds are associated with corresponding confidence scores. The method includes synthesizing a model of the environment that includes a point cloud representing the first portion of the object, at least a subset of the plurality of candidate point clouds for the second portion of the object and the corresponding confidence scores associated with the subset of the plurality of candidate point clouds.

This invention provides a fully automated pretreatment method, system, and storage medium for soil samples. The method involves acquiring a three-dimensional environmental model of the soil sample pretreatment process, determining a task sequence consisting of a starting point, task points, and target points based on the process flow, and planning a segmented, collision-free path using adjacent point pairs as start and end points. A Gaussian mixture probability model is constructed based on the endpoints, generating sampling points in the probability space to guide random tree growth. The node closest to the sampling point is selected as an expansion node, and multiple alternative directions are generated around the expansion direction. The direction with the lowest energy consumption is selected using a joint energy consumption model. New nodes are generated with a preset step size, and these nodes are added only when the weighted sum of the angular acceleration and angular jerk of the path segment is below a disturbance threshold. When a new node enters the endpoint's attraction domain, an initial path is generated and locally optimized to obtain a segmented path. All segmented paths are then concatenated into a global path, and a robotic arm is controlled to perform the soil pretreatment operation.

The invention provides a multi-pipeline layout method based on a niche coevolution algorithm, and relates to the technical field of pipeline layout methods. Comprising the following steps: A1, establishing an environment model of a pipeline layout space; a2, solving a multi-pipeline layout problem by applying an ecological niche coevolution algorithm; and A3, when the ecological niche coevolution algorithm meets a termination condition, outputting an optimal global solution as a final multi-pipeline layout scheme. On the basis, a niche layout mode, an elite partner selection strategy, a multi-dimensional information sharing mechanism and a self-adaptive evolution mechanism are introduced, the defects that in an existing co-evolution algorithm, information interaction is insufficient, and prematurity is prone to occurring are overcome, the global search ability and the quality of solution of the complex combination optimization problem are remarkably improved, and the method is suitable for large-scale popularization and application. Therefore, the problems that when an existing co-evolution algorithm is applied to multi-pipeline layout, a co-author selection mechanism is simple, shared information dimensions are single and lagged, and combined explosion is prone to being generated are solved.

The invention provides a data processing method and system for floating installation path planning, and the method comprises the steps: obtaining multi-source heterogeneous data which comprises three-dimensional submarine topography data, installation equipment three-dimensional data, hydrological parameter data and weather forecast data; performing gridding processing on the weather forecast data, the three-dimensional submarine topography data and the hydrological parameter data, and constructing a marine environment digital twinborn model based on a gridding processing result; performing dynamic prediction on the hydrological parameter data and the weather forecast data to obtain space-time evolution of the flow velocity field; performing multi-objective optimization based on the marine environment digital twinborn model and the space-time evolution of the flow velocity field to obtain a path optimization strategy; and constructing a digital twinborn simulation environment model based on the marine environment digital twinborn model and the path optimization strategy, and performing path verification updating on the digital twinborn simulation environment model based on the three-dimensional data of the installation equipment to obtain target path parameters. According to the invention, the quality and effect of path planning are significantly improved.

The invention relates to the field of photoelectric detection and computer vision, and discloses an intelligent identification method and system for a thermal imaging telescope, and the method comprises the following steps: 1, constructing a rigid thermal reference and a pneumatic noise sequence, and quantifying an environment situation index according to the rigid thermal reference and the pneumatic noise sequence; 2, locking a region of interest, and extracting an average radiation temperature sequence and an edge gray level fluctuation sequence; 3, calculating a thermal response correlation coefficient, and generating a thermal confidence coefficient; 4, performing frequency domain spectral subtraction and periodic verification on the edge fluctuation by using the pneumatic noise sequence, and generating a micro-motion confidence coefficient representing the mechanical attribute; and step 5, dynamically distributing weights according to the environment situation indexes, and fusing multi-dimensional features to calculate the biological existence probability. According to the method, the double-reference environment model is constructed, and passive temperature rise and pneumatic interference are distinguished by using thermal response and motion frequency difference, so that the problem of low recognition accuracy of traditional temperature or shape feature recognition is solved.

The invention belongs to the technical field of surveying and mapping task path planning, and particularly discloses a surveying and mapping task path planning method and system based on big data, and the method comprises the steps: firstly obtaining the current and historical surveying and mapping data of a target region, and recognizing an abnormal change pattern spot through calculating the change confidence; judging whether the pattern spots have geographic information changes or not based on a preset rule, generating variable surveying and mapping priorities, performing surveying and mapping zoning by utilizing a spatial clustering algorithm, generating a preliminary surveying and mapping task path in combination with a sequence optimization algorithm, and importing the path into a geographic environment model to perform safety conflict detection and multi-target efficiency analysis; and finally, correcting the path according to a detection analysis result and outputting a final surveying and mapping task path. Through quick discovery and efficient response to geographic information change, the generated surveying and mapping task path has high safety and high efficiency, and the input-output ratio and the operation intelligence level of surveying and mapping resources are remarkably improved.

A computer-implemented method facilitates vegetation management and environmental simulation for a geographic region. The method includes obtaining input data representing tree areas and tree characteristics for one or more species. Tree nodes are created based on identified tree centroids from the tree areas. Spatial data structures are generated to represent vegetation and terrain features based on the tree nodes and terrain data. Selection criteria are applied to partition the tree nodes into management categories. Environmental models representing alternative vegetation configurations, including a baseline and a modified configuration corresponding to tree removal treatments, are generated. Vegetation data in the environmental models is modified to reflect the alternative configurations. Environmental simulations are executed to compute outputs representing ecological responses. Statistical relations are generated between vegetation management actions and the simulated environmental responses, and output data is provided representing predicted outcomes, management planning information, or changes in environmental conditions.

This invention relates to the field of environmental model construction technology, and in particular to a data and knowledge fusion-driven integrated mine modeling method and system. The method first preprocesses multi-source heterogeneous data to establish a unified dataset, and then constructs a mine knowledge graph based on physical spatial information, linking objects, attributes, and the environment. Next, initial geometric models of the surface, ore body, and tunnels are constructed, and a mapping is established between the models and the knowledge graph. The semantic rules in the knowledge graph are used to enforce geometric constraints and logical optimization on the initial models, automatically correcting spatial conflicts. Finally, multi-element spatial integration is achieved under a unified coordinate system. This method achieves deep integration of geometric reconstruction and geological semantics, effectively solving the problem of missing model logic, and constructing a high-precision three-dimensional model with dynamic evolution capabilities and logical self-consistency, providing reliable support for intelligent mine management.

This invention relates to the field of data processing, proposing a method and system for recommending garden vegetation based on ecological and environmental data. First, environmental monitoring signals are acquired using sensor networks. Based on geostatistical variation patterns, spatial reconstruction and spatiotemporal interpolation of the signals are performed to construct a digital environmental model. Second, a global ecological neighborhood benchmark is constructed to standardize the signals, and a resource pressure index is calculated and introduced into a dynamic competition model as a nonlinear gain environmental factor weight. Third, multiple ecological strategy control logics are pre-set, and a Gaussian probability mapping between the resource pressure index and the applicability of each strategy is established. The strategy outputs are weighted and integrated using posterior probability weights to obtain configuration instructions including initial maintenance measures. Finally, feedback signals after the implementation of the instructions are monitored. When deviations exceed limits, physical adjustment mechanisms such as water and fertilizer regulation or microhabitat improvement are activated, and the model parameters are adaptively corrected. This invention achieves precise decision-making and closed-loop dynamic control of garden vegetation configuration.

The embodiment of the invention provides an environment interaction simulation method and device, computing equipment and a storage medium. The environment interaction simulation method comprises the steps that an environment model is acquired; correlating corresponding mass points for the vertexes in the environment model, setting springs for the connection relationship between the mass points, and constructing a mass point spring system of the environment model; based on the physical disturbance factor, carrying out iterative updating on the physical state of the mass point in the mass point spring system to obtain at least one piece of mass point position information of the mass point spring system of an iterative step; based on the mass point position information, mass point displacement information of the mass point spring system is determined; and based on the mass point displacement information, driving vertexes in the environment model corresponding to the mass points. The method can efficiently and truly simulate the morphological change process of a large-scale vegetation object subjected to physical disturbance, considers reality, efficiency and expansibility in the environment interactive simulation process, and can be widely applied to the fields of digital culture product manufacturing software and the like.

The invention relates to the technical field of building design, in particular to an intelligent building design assisting and optimizing system and method driven by multi-dimensional environment data, and the system comprises a multi-dimensional environment data integration and analysis module which obtains and processes multi-source environment data to construct a structured environment data set, and forms a three-dimensional thermo-optical environment model; the historical drawing learning and intelligent optimization module analyzes a historical design drawing through a deep learning model and generates an optimal design recommendation; the real-time feedback and optimization suggestion module is used for inputting the current design scheme and carrying out real-time calculation on the current design scheme to obtain an optimization suggestion; wherein the current design scheme is selected as a scheme generated according to the optimal design recommendation, and adaptive optimization of the current design scheme is realized by combining the structured environment data set and the three-dimensional thermo-optical environment model. Through the digital twinning and AI technology, the precision and efficiency of green building design are improved, the environmental performance and resource utilization are optimized, and sustainable intelligent assistance is achieved.

The present application provides a shortest route planning method and system, based on the AIS data of the target ship, and pre-processing the AIS data, then using a specific judgment method to screen the AIS data, then based on the pre-processed and screened data, using the grid method to construct a low-precision environment model, then using the ant colony algorithm to calculate the shortest path of the route in the low-precision environment model, and determining the shortest path grid range, reducing the unit grid width in the low-precision environment model to construct a high-precision environment model, and determining the shortest path grid range in the high-precision environment model according to the shortest path grid range in the low-precision environment model, finally using the A-star search algorithm to calculate the shortest path of the route in the shortest path grid range of the high-precision environment model, and using the Bezier curve method to optimize the shortest path of the route, obtaining the optimized shortest path of the route and displaying, which can greatly improve the precision of the environment model, and the time cost is low.

This invention relates to the field of soil monitoring technology, and in particular to a method and system for dynamically adjusting soil-groundwater pollution risk thresholds based on an environmental model. The method includes: collecting soil and groundwater monitoring data; constructing an environmental model including soil pollution concentration, groundwater pollution concentration, and pollutant migration rate; obtaining comprehensive pollution characteristic data; extracting key features and determining the contribution of each feature to risk assessment; calculating the initial weights of each feature based on their contribution and obtaining a weight allocation scheme; calculating soil and groundwater pollution risk values ​​by combining pollution load data and weight values, and initially setting risk thresholds; monitoring pollutant concentration fluctuation data in real time; predicting pollutant migration trends using time series analysis algorithms and obtaining risk change prediction results; and optimizing the risk thresholds by combining the risk change prediction results and environmental capacity constraints to obtain dynamically adjusted risk thresholds. This invention achieves accurate extraction of pollution features and dynamic adjustment of weights.

This invention provides a multi-pipeline layout method based on a niche co-evolutionary algorithm, belonging to the technical field of pipeline layout methods. It includes the following steps: A1: Establishing an environmental model of the pipeline layout space; A2: Applying the niche co-evolutionary algorithm to solve the multi-pipeline layout problem; A3: When the niche co-evolutionary algorithm meets the termination condition, outputting the optimal global solution as the final multi-pipeline layout scheme. Based on this, this invention introduces a niche layout pattern, an elite collaborator selection strategy, a multi-dimensional information sharing mechanism, and an adaptive evolutionary mechanism, overcoming the shortcomings of insufficient information interaction and premature convergence in existing co-evolutionary algorithms. It significantly improves the global search capability and solution quality for solving complex combinatorial optimization problems, thereby solving the problems of simple collaborator selection mechanisms, single and delayed shared information dimensions, and combinatorial explosion inherent in existing co-evolutionary algorithms applied to multi-pipeline layout.

Method for reducing environmental models for the simulation of driving functions using a normalized influence measure, with: - Acquisition of input data consisting of an underlying environment model, a driving function to be tested and a simulation target as well as simulation parameters including initial conditions and time intervals, wherein the input data is fed to an input of a system that performs the subsequent steps; - Providing a predictive model in the form of a neural network trained on historical simulation results to predict a simulation output depending on the environment model and the driving function, wherein the predictive model is parameterized so that it predicts the simulation output exclusively from the input data; - Generating a predicted simulation output; - Applying an explainability metric to the predictive model for the specific prediction in order to determine an influence value for each feature of the environmental model and to scale this to a normalized SHAP value between 0 and 1; - Deriving an adaptation of the environment model from the normalized SHAP values ​​by reducing the resolution for features below a first threshold and maintaining full detail for features above a second threshold, and setting a level of detail proportional to the normalized SHAP value in between, thereby providing an adapted environment model; - Generating a justification and influence output that lists the features relevant to the predicted simulation output and their influence, for documentation and traceability of the model fitting.

This invention discloses a method for three-dimensional propagation modeling of 4G and 5G signals based on graph neural networks, comprising the following steps: S1, acquiring three-dimensional environmental data, signal source parameters, and user measurement data to establish a three-dimensional environmental model and generate training and validation sample sets; S2, performing propagation path modeling on the three-dimensional environmental model, calculating direct, reflection, and diffraction features and aligning them with the samples; S3, constructing a joint model of graph neural network and three-dimensional convolution, completing initial training to obtain baseline parameters; S4, establishing an elastic weight consolidation library based on validation results; S5, performing fine-tuning using incremental data to obtain updated parameters; S6, generating signal prediction and three-dimensional distribution maps; S7, iteratively updating and outputting the final model based on error results. This invention achieves high-precision modeling and adaptive optimization of 4G and 5G signals in complex three-dimensional space, improving prediction accuracy and model stability, and possessing the advantages of scalability and rapid convergence.