54 results about "Spatial optimization" patented technology

The invention discloses a territorial space planning optimization method and system based on three-dimensional modeling, and relates to the technical field of three-dimensional modeling, and the method comprises the steps: obtaining multi-source territorial space data, constructing a three-dimensional space data set, carrying out the three-dimensional geometric modeling, and generating a territorial space three-dimensional model; carrying out multi-dimensional space analysis on the land space three-dimensional model, obtaining a space conflict feature set, carrying out planning constraint, and formulating a space optimization suggestion; executing the space optimization suggestion to perform three-dimensional dynamic modeling, generating a multi-time sequence planning simulation result to perform space planning evaluation, generating a land space planning score, performing planning compensation based on the backtracking space optimization suggestion, updating the space optimization suggestion, and obtaining a space planning optimization scheme. The technical problem that in the prior art, land space planning depends on two-dimensional data, the space conflict and the dynamic evolution process are difficult to comprehensively recognize, and the planning scheme is insufficient in scientificity is solved, and the technical effect of improving the space conflict recognition precision and the planning decision scientificity is achieved.

The invention discloses a vegetation carbon sink space optimization method and system based on interpretable machine learning. The method comprises the steps that firstly, multi-source environment data such as administrative division, environment factors and target variables of a target area are acquired, and a space table data set is formed; training an XGBoost regression model based on the data set, predicting the vegetation carbon sink amount and evaluating the performance of the model; quantifying the contribution of each environmental factor to the carbon sink by combining an SHAP interpreter, generating a feature importance and interpretability map, fitting through a LOWESS algorithm to obtain an environmental factor and carbon sink response relation curve, and extracting an optimal threshold interval; further predicting a carbon sink gain according to an optimization threshold value, delimiting optimization partitions, and forming a space optimization scheme; and finally outputting a vegetation carbon sink optimization suggestion report. According to the method, scientific quantification of carbon sink space optimization can be realized, and the interpretability and decision support value of a carbon sink improvement strategy are improved.

The invention discloses a farmland soil sampling space optimization method based on local heterogeneity, and belongs to the field of soil sampling space optimizing.The method comprises the steps that the heterogeneity level of soil in a research area is calculated through a variable coefficient; according to the soil heterogeneity level of the research area, dividing the research area into spatial continuous sub-areas with similar soil heterogeneity level by using a heterogeneity change algorithm; and on the basis of the environment covariables, a method of combining a fuzzy c-mean classifier and a heterogeneity change algorithm is adopted, geographic and feature spaces are optimized, key sampling positions in continuous sub-regions of each space are identified, and farmland soil sampling space optimization is completed. According to the method, the problem that the influence of the soil local heterogeneity level on sample size distribution and spatial layout optimization is not considered in an existing method is solved.

The invention relates to a multi-scale urban garden carbon sink improvement and ecological collaborative regulation and control system, in particular to the field of urban gardens, and aims to construct a computable and evolvable knowledge graph, deeply fuse multi-source data and domain rules and dynamically drive a space optimization decision. Static planning is upgraded into a'prediction-simulation-learning 'closed-loop process; an optimization algorithm uses a knowledge graph to perform efficient optimization, and a multi-target equalization scheme is generated; carrying out high-fidelity and uncertainty-containing long-term dynamic deduction and risk assessment on the scheme by the digital twinborn body; a simulation result feeds back a calibration knowledge rule through meta reinforcement learning, a success mode feedback knowledge base is extracted from the calibration knowledge rule, and the process realizes collaborative self-evolution of planning knowledge, an optimization model and a simulation environment, so that the accuracy, robustness and foresight of decision making are continuously improved, and the decision making efficiency is improved. And finally, multi-scale collaborative optimization of carbon sink, ecological and social services and economic cost is achieved.

The invention discloses a human settlement environment quality evaluation method based on urban public service and ecological system service, and relates to the field of ecological environment evaluation, and the method comprises the steps: determining an evaluation region, and obtaining the natural, economic and remote sensing data of a year to be evaluated in the evaluation region; performing quantitative evaluation on the ecosystem service of the evaluation area from rainfall flood adjustment, heat island effect relief, air purification and park recreation in the ecosystem service; performing quantitative evaluation on the urban public service of the evaluation area from medical security, basic education and public culture in the urban public service; and carrying out weight superposition calculation on the score of each evaluation factor in the ecological system service and the urban public service to obtain a human settlement environment quality comprehensive score of the evaluation area. According to the method, human settlement environment quality evaluation can be carried out scientifically and comprehensively with resident demands as the core, and a direction is pointed out for city space optimization.

The invention discloses an urban comprehensive park space-time network construction method and system based on crowd trajectory data. The method comprises the following steps: firstly, collecting, cleaning and dividing crowd trajectory data in a comprehensive park range; secondly, scenic spots in the comprehensive park are clustered, the number of optimal clusters is determined through clustering analysis, and all the clusters serve as all functional activity districts; then building a trajectory model through space projection and a shortest path algorithm, recovering a user moving trajectory path according to the crowd trajectory data, generating path node sequence data according to the timestamp of each trajectory point, and finally, taking the centroid of each functional activity area as each node of the space-time network, and combining each time period to obtain the user moving trajectory path. And constructing an undirected space-time network and a directed transfer network. The method has the advantages of efficient data processing, high modeling precision and perfect privacy protection, dynamic monitoring and space optimization analysis of the park people flow can be realized, and reliable data support and decision basis are provided for urban comprehensive park planning management.

The invention discloses an active city cooling method based on a three-dimensional city form and a circuit theory, and belongs to the technical field of city environment regulation and heat island effect governance, and the method comprises the steps: S1, recognizing long-term stable cold and heat source patches through obtaining multi-temporal surface temperature (LST) data and combining mathematical form spatial pattern analysis (MSPA) and a landscape connectivity index; s2, adopting a spatial principal component analysis (SPCA) method to construct a comprehensive resistance surface fused with the three-dimensional urban form factors; s3, connecting a cold and heat source to simulate an airflow conduction path based on a circuit theory, extracting a cooling gallery and identifying key nodes; and S4, finally, through a stable surface-connecting line-key point mode active cooling network, space optimization is carried out. According to the method, accurate identification and efficient communication of cold and heat sources can be realized, the heat island effect relieving efficiency is improved, the long-term adaptability of a cooling network is ensured, and a popularized urban thermal environment governance path is provided.

The invention discloses a cloud-side cooperation-based power consumer power consumption data abnormity monitoring method and system, and relates to the technical field of cloud-side cooperation, and the method comprises the steps: obtaining the position of equipment through a GPS, constructing a basic portrait of a power consumer, optimizing the deployment of edge equipment, and achieving the real-time collection of basic power consumption data and environment data. And then de-noising the data and extracting features, identifying an equipment type by using a prediction model, constructing an interference model in combination with a timestamp, environmental data and the equipment type, correcting a basic power utilization function matrix to obtain a standard matrix, and further realizing anomaly monitoring and early warning through deviation comparison. The system iteratively optimizes an interference model through regional convergence data to form an acquisition-analysis-correction-monitoring closed loop. According to the method, the monitoring real-time performance is improved through a cloud edge collaborative architecture, the cost is reduced by utilizing a lightweight model and space optimization deployment, and the problems of high delay, poor adaptability and the like of traditional centralized monitoring are solved.

The present invention relates to the field of information sharing and management technology. It provides an agricultural information sharing and management method based on multi-source data fusion, spatially calibrates multi-source data, and constructs an agricultural health spatial dataset. It mines the correlation between microbial communities and soil health through spatial correlation network analysis and constructs a spatial correlation model. It optimizes the allocation of agricultural resources. It also generates a personalized agricultural resource allocation plan for each region through a spatial optimization algorithm. After the agricultural resource allocation plan is implemented, a correction plan is automatically generated based on spatial feedback from microbial communities and soil health, and an agricultural health assessment report is generated. The present invention establishes a closed-loop feedback system through an adaptive optimization mechanism, dynamically adjusts management measures based on real-time monitoring data, and ensures that the management strategy is always in an optimal state.

This invention provides a Bayesian-based method and apparatus for spatial trade-off and synergistic optimization of ecosystem services, relating to the fields of ecology and statistics. The invention acquires an ecological spatial database of a target area, uses ArcGIS software's netting and clipping tools to generate a grid layer of a specified size for the target area, obtaining a pixel set. Based on the ecological spatial database and pixel set, the blue carbon storage, biodiversity maintenance capacity, and coastal protection capacity of the target area are calculated, representing three ecosystem services. Furthermore, the coupling coordination degree is obtained to analyze the overall coordination level among ecosystem services. A Bayesian-based ecosystem service synergy prediction model is constructed using Netica software to identify key driving factors and output the probability distribution of corresponding nodes, simulating and analyzing potential synergistic impacts under different scenarios. This invention can accurately identify and clarify the trade-off and synergistic relationships of key ecosystem services such as coastal wetlands, achieving synergistic spatial optimization of ecosystem services.

This invention discloses a method and system for spatial optimization of vegetation carbon sinks based on interpretable machine learning. The method first acquires multi-source environmental data, including administrative divisions, environmental factors, and target variables for the target area, forming a spatial tabular dataset. Based on this dataset, an XGBoost regression model is trained to predict vegetation carbon sink capacity and evaluate model performance. A SHAP interpreter is then used to quantify the contribution of each environmental factor to carbon sink, generating feature importance and interpretability maps. The Lowes algorithm is used to fit the relationship curve between environmental factors and carbon sink response, extracting the optimal threshold interval. Further, based on the optimization threshold, carbon sink gain is predicted, optimization zones are delineated, and a spatial optimization scheme is formed. Finally, a vegetation carbon sink optimization recommendation report is output. This method enables the scientific quantification of carbon sink spatial optimization, improving the interpretability and decision support value of carbon sink enhancement strategies.

The present invention relates to the technical field of new energy vehicles, and particularly to a load balancing and scheduling method for new energy vehicle charging piles based on intelligent algorithms, comprising the following steps: S1, data acquisition: real-time acquisition of the operating data of the charging piles; S2, charging demand prediction: prediction of the charging demands of each charging pile within a predetermined future time through a graph convolutional network model; S3, spatial scheduling optimization of the charging piles: according to the geographical distribution of the charging piles, the surrounding vehicle flow, and the results of the charging demand prediction, spatial optimization of the scheduling of the charging piles is carried out; S4, load scheduling and resource allocation: based on the results of the charging demand prediction and the spatial scheduling optimization of the charging piles, combined with the grid load situation, resource allocation is carried out. The present invention improves the utilization efficiency of the charging pile resources, optimizes the layout of the overall charging network, and ensures the fairness of the charging service and the balance of the grid load.

The application discloses a cultivated land spatial layout optimization management system and method based on multi-source data fusion, relates to the cultivated land spatial optimization technical field, and acquires cultivated land patch data, irrigation water source data and ecological protection elements in an evaluation area; analyzes basic characteristics of each cultivated land patch; collects cultivated land change data in a historical period, and constructs a training data set containing stable cultivated land and changed cultivated land; analyzes the weight of each basic characteristic based on a stable fitting model; based on each real-time basic characteristic after processing and the weight of each basic characteristic, weighted summation is carried out, and the optimization comprehensive score of each cultivated land patch is calculated; the classification threshold of the optimization comprehensive score is determined according to an administrator-selected threshold analysis method; the cultivated land patch is divided according to the classification threshold, and an optimization attribute list is generated and sent to the administrator. The subjectivity of the uncertainty of weighting is avoided, and the accuracy of system analysis is improved.

This invention discloses a method for analyzing the self-attractiveness of public spaces based on the behavioral characteristics of urban residents, including the following steps: (1) Data preprocessing: Collect objective data on the scale, function, and population size of urban public spaces within a fixed statistical period, classify public spaces in urban residential areas by type, and perform data preprocessing; (2) Spatial vitality analysis: Analyze the vitality of public spaces from two aspects, namely, analyze the degree of residents' gathering in designated public spaces and the stability of their stay in public spaces; (3) Spatial optimization and adjustment: Optimize and adjust urban residential public spaces based on residents' usage needs, the scope of space optimization, and the existing resource allocation of various public spaces. This invention improves the utilization rate of urban public spaces and accurately positions the future development direction of new urban construction, enabling effective planning of various public space resources and avoiding resource waste.

The invention discloses an intelligent anchor position detection algorithm based on multilevel spatial constraints. The intelligent anchor position detection algorithm comprises the following steps: establishing a ship safety distance model based on a Monte Carlo stochastic simulation technology; establishing an anchoring safe water depth detection model based on KD-Tree; and screening anchor location points which simultaneously meet safety spacing and water depth constraints. According to the method, the advantages of global fast search and local fine detection are effectively integrated by constructing a layered progressive space optimization framework. The method comprises the following steps: firstly, establishing a multi-level spatial constraint model for ship anchor position detection on a theoretical level, and defining a collaborative optimization mechanism between different levels; and secondly, organic fusion of spatial index and dynamic filtering is realized in algorithm design, an anchoring position point meeting the safe distance between ships is obtained through an anchoring safety detection model based on plane distance constraint, an anchoring position point meeting the water depth constraint is obtained through water depth detection based on KD-Tree, and compared with an existing method, the calculation efficiency is remarkably improved.

This invention discloses an intelligent recommendation method and system for group meeting locations based on a large language model. The method includes: outputting individual and location profiles from the large language model and inputting them into a spatial optimization model to obtain a group center; setting a search radius from the group center to generate a candidate location set, along with the individual movement cost and average movement cost corresponding to each candidate location; classifying and semantically annotating the candidate locations with tags to obtain a structured ranking result, and further generating a structured recommendation result. Thus, individual and location profiles are generated based on natural language analysis, and the movement cost of individual users to various locations is introduced for reverse weighted iteration to filter and obtain a candidate set with high accessibility. Then, multi-round chain reasoning is performed using full-process data to select highly feasible recommendation options from the candidate set that align with the interests of the user group, ensuring that group meetings can be successfully arranged without strong resistance from individual users.

The invention discloses an intelligent AI full-automatic package storing and taking system, particularly relates to the field of intelligent logistics and automatic storing and taking, and comprises a multi-mode sensing acquisition module, a dynamic feature recognition module, a real-time space construction module, an intelligent decision module, an automatic scheduling execution module and a data management monitoring module. According to the intelligent AI full-automatic packet access system, through the multi-mode perception acquisition module, the fine perception capability of physical attributes of a packet is improved, and the problem of insufficient space optimization caused by lack of fine perception of the physical attributes of the packet is directly relieved; a dynamic feature recognition module is used for modeling a sensor space relation and image semantic association, deep space optimization storage based on package features is directly supported, and the space utilization rate is increased; the intelligent decision-making module adopts a reinforcement learning and autonomous learning optimal decision-making strategy, so that the storage efficiency and the energy consumption can be dynamically balanced when concurrent requests are processed, and the path planning efficiency and the system throughput in a high-concurrency scene are remarkably improved.

This invention relates to the field of electromagnetic compatibility technology in power systems, and more particularly to a rail position control and suppression system based on multi-objective optimization. The invention generates a target potential distribution prediction scheme through a potential distribution prediction generation module, which then corrects the scheme using a spatial calibration unit based on real-time train position offset to generate spatial dynamic correction coefficients. The spatial optimization unit then optimizes the scheme based on historical soil resistivity drift data. Simultaneously, a target drainage action timing scheme is generated through a timing scheme generation module, corrected by a timing calibration unit based on real-time rail potential deviation to generate timing dynamic correction coefficients, and then optimized by a timing optimization unit based on historical equipment performance data. Finally, a comprehensive point-based control module achieves coordinated spatial and temporal control.

The present invention provides a base station site selection method based on a spatial optimization algorithm and measured signal model calibration, including: step 1, determining the center point and radius of the area with weak signal coverage to be improved, and calculating the distance between the target base station planning point and the weak coverage center point according to the signal propagation model; step 2, setting the search radius with the center of the area with weak signal coverage to be improved as the center of the circle, determining the circular search circle with the search radius, and obtaining the total number of base stations in the search circle and the initial unordered base station list; step 3, when the total number of base stations in the search circle is 1, obtaining the coordinates of the target base station planning point; step 4, when the total number of base stations in the search circle is greater than 1, optimizing the spatial sorting of the base stations, and calculating the coordinates of the target base station planning point. The method of the present invention improves the site selection accuracy by combining the measured signal data, accurately targeting the area with weak signal coverage to be improved, ensuring that the base station deployment can effectively cover the target area, improving the site selection accuracy, and ensuring the consistency of the results.

The invention relates to the technical field of metadata processing, and provides a spatial optimization method, system and device based on multi-level tree organization metadata, and the method comprises the steps: creating a multi-level tree organization, and setting a compression mark in the multi-level tree organization; when a record is inserted into the multi-level tree organization, the compression mark on the corresponding business type tree is removed; when the records in the multi-level tree organization are deleted, the compression marks are set for the corresponding service type trees again; when the data of the multi-layer tree organization is serialized, performing combined serialization or independent serialization on the associated service type trees according to whether the service type trees in the association paths have compression marks or not; when the data of the multi-layer tree organization is read, reading the data of the associated service type tree according to the compression mark; when the service type trees of the multi-layer tree organization are eliminated, the associated service type trees are eliminated according to the compression marks. According to the method, the occupation of the metadata space can be reduced under the scene that the metadata is organized by the multi-layer tree.

The invention provides a hyper-parameter space boundary analysis method and device, electronic equipment and a storage medium. The method comprises the steps that first hyper-parameter data of the precision system is obtained, the first hyper-parameter data has a plurality of dimensions, each dimension represents a hyper-parameter, and the hyper-parameters are parameters influencing the operation effect of the precision system; performing dimension reduction processing on the first hyper-parameter data to obtain second hyper-parameter data, wherein the dimension number of the second hyper-parameter data is smaller than that of the first hyper-parameter data; performing continuous function modeling for every m different dimensions in the second hyper-parameter data to obtain a plurality of continuous function relationships; performing spatial optimization for each continuous function relationship to obtain a feature value of the second hyper-parameter data, wherein the feature value indicates the position of a point with the maximum gradient descent step length in the second hyper-parameter space; and carrying out boundary solving and dimension raising processing by utilizing the characteristic value of the second hyper-parameter data to obtain first hyper-parameter space boundary information. According to the invention, the efficiency and accuracy of hyper-parameter space boundary analysis can be improved.

This invention discloses a three-dimensional nearest neighbor search method for multi-objective composite requirements based on GIS and Python, belonging to the field of geographic information systems and spatial data analysis technology. The method includes the following steps: extracting the geographic three-dimensional coordinates of the center points of multiple objectives; digitally processing the multi-objective composite requirements; delineating the analysis area and defining analysis units; constructing a regional analysis index system based on GIS; and implementing three-dimensional nearest neighbor search analysis based on Python to capture nearest points that meet the target requirements. Starting from digitized multi-objective composite requirements, this invention establishes a large-scale regional requirement analysis index system using GIS tools, and then performs efficient collaborative screening of multi-objective composite requirement conditions based on Python. This solves the technical problem that traditional methods cannot simultaneously handle attribute constraints and geometric distances, and is applicable to scenarios requiring spatial optimization decisions such as building site selection, path planning, and resource allocation.

This invention provides a method for configuring soil conditioning measures for drought and flood mitigation, belonging to the field of soil and water conservation technology. This method collects physiographic data and hydrological evolution data for the study area to determine the impact of soil conditioning measures on rainfall-runoff production in different soil units, establishes empirical equations to quantify the regulating capacity of various soil conditioning measures, constructs a drought and flood evaluation index system and verifies its rationality, divides the watershed into suitable areas for the implementation of soil conditioning measures, then quantifies the regulating capacity of individual soil conditioning measures in each sub-basin based on the suitable areas. Using a single-objective spatial optimization method, with the goal of maximizing drought and flood mitigation, the method ultimately determines the spatial layout of soil conditioning measures in the study area. This method achieves an optimal configuration of various soil conditioning measures for the purpose of drought and flood mitigation.

The present invention provides a spatial optimization method and system for a surface water environment monitoring network, and relates to the technical field of data processing. The method comprises: obtaining river information of a to-be-monitored area; establishing a river buffer zone based on the river information; extracting human activity intensity data in the river buffer zone; selecting multiple candidate monitoring sections based on the human activity intensity data, and determining the monitoring coverage of each section; merging all monitoring coverages, removing overlapping areas, and obtaining an accurate monitoring coverage; constructing a surface water environment monitoring network spatial optimization model with the goal of maximizing coverage of human activity intensity based on each candidate monitoring section and the accurate monitoring coverage; optimizing the model through an adaptive global optimization search algorithm, and outputting an optimal monitoring site layout plan; and arranging monitoring sites according to the optimal monitoring site layout plan, so as to perform spatial optimization of the surface water environment monitoring network.

This invention discloses a multi-UAV cooperative search trajectory planning method based on 3D action decoupling, aiming to solve the core problems of low efficiency in 3D action coupling learning, insufficient target uncertainty modeling, imbalance between exploration and utilization, and poor multi-UAV cooperation in multi-UAV cooperative search under 3D unknown environments. This invention models the multi-UAV cooperative search process as a partially observable Markov decision process, designs a 3D action decoupling Actor network to achieve decoupled control of horizontal plane motion and vertical altitude motion, constructs a non-sparse multi-dimensional reward function to provide dense feedback for policy learning, and introduces a dynamic noise attenuation mechanism based on target confidence to achieve spatial optimization allocation of exploration resources and complete iterative optimization of the cooperative search strategy. This method can significantly improve the target detection rate, reduce flight energy consumption and conflict rate, and can efficiently adapt to the needs of multi-UAV cooperative search trajectory planning in complex 3D unknown environments.

The application discloses a kind of silt dam dam system space optimization intelligent simulation method based on high-resolution image, it is related to silt dam system planning technical field, including the geographic registration after the multiple high-resolution remote sensing images of target river basin, extract three-dimensional terrain information, generate surface deformation elevation difference grid through pixel level difference operation, extract the measured sediment discharge of each sub-basin, and combine with the rainfall data corresponding to different time, construct the sediment transport ratio model of each sub-basin, generate the actual sediment yield contribution intensity spatial distribution diagram of target river basin, it is used as input, in the spatial range of target river basin, with dam system overall service life maximization as target intelligent simulation optimization is carried out, at least including dam site coordinates and dam height dam system space layout parameter is solved, provide a kind of can analyze the dynamic process of river basin sediment yield and siltation, realize river basin sediment yield contribution intensity fine mapping, and can carry out system level optimization to dam system.The method.

The invention relates to an ecological protection priority area identification method and system based on multi-source data and space optimization, and the method comprises the steps: collecting and preprocessing multi-source space data in a target area, and generating a theme space data set; quantifying the ecosystem service in the target area, and obtaining a standardized magnitude spatial distribution map; combining the species distribution point location in the target area with the theme space data set, and simulating to generate a suitability space distribution diagram; fusing the standardized magnitude spatial distribution map and the suitability spatial distribution map to form a regional comprehensive protection value curved surface; and carrying out iterative calculation on the regional comprehensive protection value curved surface by adopting a space optimization algorithm to obtain an ecological protection space layout scheme, and delimiting different protection level priority ecological protection regions of the target region. According to the method, the accuracy, scientificity and operability of an ecological protection priority area identification delimiting process are greatly improved, and an efficient technical approach is provided for cooperative protection of biodiversity and ecological system service.

The invention discloses a cultivated land resource optimization configuration method considering drought and flood disaster comprehensive risks, relates to the technical field of geographic data analysis and land resource optimization, and solves the problem that the existing cultivated land resource optimization method does not fully consider the drought and flood disaster risks and thus is insufficient in applicability in areas with frequent drought and flood occurrence. According to the method, drought and flood disaster comprehensive risk and plowing suitability index evaluation systems of land resources are constructed respectively, grading evaluation results of the drought and flood disaster comprehensive risk and plowing suitability index evaluation systems are combined, a spatial conflict judgment matrix is established by utilizing a general matrix method, so that a key optimization configuration area is accurately identified, and finally, a multi-target genetic algorithm NSGA-II is utilized to simulate a cultivated land layout in the key optimization configuration area. According to the method, drought and flood disaster risk factors are systematically fused into a cultivated land resource optimization configuration process, a cultivated land replacement mode under the background of frequent drought and flood disasters can be effectively simulated, meanwhile, the search range of an optimization algorithm is remarkably reduced, and the efficiency of cultivated land resource space optimization simulation is greatly improved on the premise of guaranteeing the quality of an optimization scheme.

According to the integrated monitoring device for the operation connecting rod of the generator outlet circuit breaker, through voiceprint, three-axis multi-dimensional vibration, spatial optimization integration of the angle sensor and a multi-modal data fusion algorithm, the mechanical fault diagnosis precision is remarkably improved, and the integrated monitoring device is suitable for intelligent substation state maintenance scenes and has good application prospects. A three-dimensional modeling technology is adopted to carry out spatial analysis on a circuit breaker operating mechanism, and a sensor layout scheme is optimized through a genetic algorithm, so that a voiceprint microphone, a three-axis multi-dimensional vibration sensor and a high-precision angle encoder can realize coupling interference minimization in a limited installation space, and in the aspect of data fusion, the accuracy of data fusion is greatly improved. A heterogeneous feature extraction model based on a deep belief network is constructed, time-frequency domain signal processing and mechanical motion trail analysis are combined, 12 types of typical mechanical faults such as opening and closing jam and connecting rod deformation can be effectively recognized, an edge computing terminal is integrated in the system, GOOSE message real-time transmission abnormal state quantity is supported, and the fault diagnosis accuracy is improved. And a dynamic compensation module is innovatively introduced to eliminate the influence of electromagnetic interference on sensing data.

The invention provides a nuclear energy development and spatial distribution optimization system based on LEAP framework extension, and relates to the technical field of energy and environment. The data acquisition module is used for acquiring regional factory site suitability data, energy demand data, environmental constraint data and power grid capacity data from a plurality of data sources, preprocessing the data and integrating the data into a spatial database; the dynamic space optimization engine module is used for completing matching of nuclear energy resources and regional demands according to a plant address-demand matching algorithm and a multi-objective optimization model; the policy scene coupling system module is used for supporting a user to customize various policy variables and dynamically adjusting nuclear energy development optimization constraint conditions according to the policy variables input by the user; and the dynamic scene simulation module is used for supporting a user to select a scene type in a customized manner, simulating the influence of the scene type change on the regional nuclear energy development path and the energy structure through iterative computation, and outputting the optimized nuclear energy development path and the regional energy structure.