35 results about "Urban region" patented technology

The invention provides an ecological environment dynamic monitoring method based on big data, and relates to the technical field of environmental pollution detection, and the method comprises the steps: collecting multi-source sensor data of a fixed monitoring station in an urban region, and carrying out the time alignment and space registration of the multi-source sensor data, thereby generating a standardized environmental monitoring data set. And on the basis of the data set, constructing a pollutant transmission network between the monitoring points to obtain a regional pollutant distribution characteristic graph, calculating a diffusion trend coefficient of pollutants in combination with regional wind direction data, constructing a pollutant migration path network, and generating a key supervision region map. According to the method, the pollutant concentration distribution can be dynamically partitioned, and the mobile monitoring equipment is scheduled to carry out gradient type point distribution monitoring, so that the accurate positioning of the pollution source is realized; the accuracy of pollutant diffusion trend analysis and the precision of pollution source positioning are improved, dynamic supervision of key areas is facilitated, the efficiency of environment monitoring and the fine management level are improved, and therefore the risk of environmental pollution is effectively reduced.

The invention provides an unmanned aerial vehicle live-action three-dimensional model construction optimization method and system for urban planning, and relates to the technical field of live-action modeling, and the method comprises the steps: preliminarily constructing a three-dimensional model of an urban region; determining a geometric deviation value of the spatial structure units in the same scene semantic unit according to the geometric boundary features and the image projection errors of the different spatial structure units in the same scene semantic unit; determining semantic conflict loss of the three-dimensional model in a scene semantic extraction process based on a spatial constraint relationship between adjacent spatial structure units and color gradients and transition characteristics of category boundaries; and determining a feature constraint value of the spatial structure unit in the three-dimensional model optimization process through the geometric deviation value and the semantic conflict loss, and carrying out geometric and semantic optimization on the three-dimensional model based on the feature constraint value to obtain a real scene three-dimensional model for urban planning application. By adopting the scheme of the invention, collaborative optimization of the urban area live-action three-dimensional model on geometric accuracy and semantic consistency can be realized.

The invention provides a flexible interconnection device site selection method and system based on distributed resource clustering, and the method comprises the steps: constructing a photovoltaic output feature map Laplacian matrix and a load feature map Laplacian matrix according to the photovoltaic output and load data of a planning region, decomposing the constructed matrixes through DGRNMF, and obtaining a distributed resource cluster; solving a photovoltaic clustering center curve and a load clustering center curve according to a decomposition result through a k-means clustering algorithm, and dividing the photovoltaic clustering center curve and the load clustering center curve into an urban region and a rural region; constructing constraint conditions of the power supply grid segmentation model to obtain the power supply grid segmentation model; and solving the power supply grid segmentation model to obtain an optimal power grid partitioning scheme, and determining a candidate installation position of the flexible interconnection device according to the optimal power grid partitioning scheme. According to the invention, the precision and reliability of the flexible interconnection device site selection planning decision are improved.

The embodiment of the invention discloses an urban agglomeration hot area prediction method based on a large model data driven graph convolutional network. The method comprises the following steps: acquiring historical travel data corresponding to a city, and determining a historical popularity tensor corresponding to each region of the city based on the historical travel data; based on the historical heat tensor corresponding to each region, determining a comprehensive cost matrix between any two regions among the regions; acquiring public opinion information corresponding to the city, and determining a time aggregation feature tensor of the city based on the public opinion information; and obtaining a space-time tensor of each region based on the time aggregation feature tensor and the comprehensive cost matrix, and determining a predicted popularity tensor of each region based on the space-time tensor. According to the embodiment of the invention, the prediction popularity tensor can more accurately and comprehensively reflect the popularity level which can be reached by each region of the city in the future, and a very valuable decision basis is provided for the fields of city planning, resource allocation, tourism promotion and the like.

The invention provides an urban human-water system complex mutual feedback relation identification method based on a system evolution model, and the method comprehensively considers the factors of population change, water resource utilization, water pollution control, urban economic development and the like of a research area. Comprising the following steps: S1, analyzing the evolution characteristics of three subsystems of people, water and city in a research area, and evaluating the coupling coordination degree of the three subsystems; s2, gathering related data, carding causal relationships among the interiors of the three subsystems, constructing a quantification equation, and constructing a mutual feedback evolution model of the urban human-water system by adopting a system dynamics method; and S3, verifying the simulation effect of the model through visual inspection and historical inspection. According to the method, the complex mutual feedback relation among human, water and city multi-elements can be clarified, the human, water and city multi-element mutual feedback evolution process is simulated, finally, a universal model framework is established, the framework can be applied to human, water and city coupling systems in different urban regions, and technical support is provided for achieving coordinated development of the urban economic society and the water resource environment.

The application provides a point cloud filtering method and device for removing background point clouds, and a vehicle. A plurality of point cloud columns and an initial index are obtained. A plurality of shallow feature maps, a plurality of point cloud column features corresponding to the plurality of shallow feature maps, and a first index are determined according to the plurality of point cloud columns and the initial index. The plurality of shallow feature maps and the first index are input into a preset convolutional backbone network to obtain a plurality of splicing features corresponding to the plurality of point cloud columns, wherein the shallow feature maps and the splicing features correspond one by one. The plurality of splicing features are input into a full connection layer to obtain a plurality of classification labels corresponding to the plurality of point cloud columns, wherein the full connection layer is contained in the preset convolutional backbone network, and the classification label is used to represent an object corresponding to a point cloud in the point cloud column. A target point cloud is determined according to the plurality of classification labels, thereby solving the technical problem that the precision of a 3D target detection small model on a laser radar for detecting a target object is not high in a complex urban scene in the prior art.

The invention relates to the technical field of data evaluation, and discloses an urban vegetation cooling effect evaluation method and system based on multi-source remote sensing data, a terminal and a storage medium, and the method comprises the steps: obtaining urban region data of a city, and carrying out the preprocessing and feature extraction to obtain a feature extraction result; inputting the feature extraction result into a vegetation cooling effect evaluation training model, outputting a feature sorting result, a feature analysis result and an ecological threshold recognition result, obtaining a vegetation cooling effect evaluation prediction result, and adjusting the vegetation cooling effect evaluation training model to obtain a vegetation cooling effect evaluation model; and acquiring to-be-evaluated city data of a target city, performing preprocessing and feature extraction to obtain a target feature extraction result, and inputting the target feature extraction result into the vegetation cooling effect evaluation model to obtain a vegetation cooling effect evaluation result. According to the method, through multi-source remote sensing data fusion, the urban vegetation cooling effect is accurately depicted, so that the accuracy of a vegetation cooling effect evaluation result is improved.

The invention provides an urban railway precast beam lifting and transporting frame construction device and method, and relates to the technical field of precast beam construction.The urban railway precast beam lifting and transporting frame construction device comprises a bottom frame, the bottom frame is used for bearing the bottom of a precast beam, abutting frames are hinged to the two sides of the bottom frame correspondingly, and each abutting frame can rotate around a hinge point so as to abut against the side wall, close to the bottom, of the precast beam in the width direction; each abutting frame is fixedly connected with a steel wire rope; the two sets of top frames correspond to the abutting frames on the two sides respectively, each set of top frame comprises a clamping frame and a swing frame, the clamping frame is of a U-shaped structure and used for being clamped to the top side edge in the width direction of the precast beam, the swing frame is installed on the clamping frame in a hinged mode, an abutting plate used for abutting against the top of the precast beam is arranged at one end of the swing frame, and a lifting lug is arranged at the other end of the swing frame. Safe and stable construction of the whole lifting, transporting and erecting process of the precast beam can be achieved, and the safety and construction efficiency of urban railway precast beam operation are effectively improved.

The application provides a SCR downstream NOx sensor failure diagnosis method, comprising the following steps: 1) confirming that the SCR downstream NOx sensor, the ammonia sensor and the ECU are in normal communication; installing a PEMS device and confirming that the PEMS device test data is accurate; 2) starting the vehicle to be tested, and performing PEMS emission tests under three working conditions of urban area, suburb and highway; 3) performing data elimination on the PEMS device, aligning the remaining data by working condition, then comparing and obtaining errors under different working conditions, and obtaining a total error; 4) if the total error is greater than the set threshold, the SCR downstream NOx sensor installed on the vehicle to be tested has failed; or if the total error is less than or equal to the set threshold, the SCR downstream NOx sensor installed on the vehicle to be tested is normal. The application can accurately judge the failure of the SCR downstream NOx sensor, has the advantages of scientific rationality, high reliability and wide application range, and can provide a theoretical basis for the normal operation of the vehicle.

The application discloses an intelligent division method for police case high-occurrence areas based on density clustering and k-means clustering, and the method comprises the following steps: obtaining police case data of a city; preprocessing original police case data to obtain data after unification and standardization; clustering the data after preprocessing by using a density algorithm to obtain all categories and corresponding data of each category; clustering the police case data of all categories by using a k-means algorithm; then clustering all police cases of each police case data by using the density algorithm to obtain all categories and corresponding data of each category; extracting boundary points of each category data to obtain corresponding boundary contours, that is, to obtain police case high-occurrence areas. The application can accurately identify police case high-occurrence areas, and can effectively balance the uneven distribution of police case high-occurrence areas in urban areas and suburban areas, thereby providing effective data support for subsequent police deployment, unified dispatching and command.

The invention provides a snow sweeping and deicing path control method based on vehicle track dynamic feedback, and belongs to the technical field of smart city traffic management.The snow sweeping and deicing path control method comprises the steps that a kafka technical component and a websocket communication technology are combined, GPS data of a snow removing vehicle are accessed in real time, the vehicle driving track is dynamically displayed, and urban area operation progress is visited; a Q-learning reinforcement learning algorithm is introduced, parameters such as road priority and operation vehicle energy consumption are combined, dynamic allocation of the optimal operation path strategy of the snow removal truck is achieved by constructing a reward function and a continuous iteration state-action value function (Q value function), and the effect of dynamic balance of snow removal operation efficiency and operation vehicle energy consumption is achieved.

This invention relates to the field of spatiotemporal data processing technology, and discloses a method, system, terminal, and storage medium for predicting multi-dimensional urban indicators based on semi-supervised learning with small samples. The method includes: extracting visual, textual, and structural features of urban space using a three-branch encoder, and generating a unified urban region representation vector using a multimodal fusion mechanism; subsequently, constructing a semi-supervised collaborative computing framework that integrates a heterogeneous neural network model and an ensemble tree model as a regressor; and, under conditions of a small number of labeled samples, using an alternating pseudo-label generation and four-fold pseudo-label selection mechanism, performing semi-supervised augmentation training on the model with massive amounts of unlabeled data to improve the accuracy of spatiotemporal data labeling. This invention significantly reduces the dependence on labeled data and achieves high-precision labeling prediction across multiple dimensions of urban indicator calculation.

The invention discloses a traffic planning method based on big data, and belongs to the technical field of traffic planning, and the method comprises the following steps: S1, collecting the passenger volume and passenger transportation turnover data of the whole society, railways, roads, water transportation and civil aviation of a preset region; s2, using a big data analysis technology to predict traffic demands in the target urban area and from the target city to other cities based on the collected passenger traffic volume and passenger traffic turnover data; and S3, according to a traffic demand prediction result, constructing a three-layer rail transit network comprising an intercity line, an urban line and a local line, and endowing a fast and slow line composite function to a newly added line in the rail transit network. According to the method, the rail transit network with clear layers and highly-compounded functions is constructed, and the operation efficiency of a traffic system is comprehensively improved.

The application relates to the technical field of urban waterlogging treatment, in particular to an urban waterlogging emergency management system based on the Internet of Things. The system comprises the following: a data acquisition module that acquires first data of drainage hydraulic states and water accumulation distribution and second data of waterlogging drainage construction conditions and drainage surplus; a region division module that divides the urban region into a plurality of waterlogging island units based on the calculation of connectivity of the first data and the calculation of conflict degree of the second data; a key node identification module that identifies key nodes in the units, calculates the overlapping degree and the coordination coefficient between the nodes, and determines the node emptying sequence; a cross-unit scheduling module that calculates the unit lever density according to the sum of the node emptying lever rate and the average overlapping degree, and determines the unit processing sequence; and a processing module that sequentially carries out waterlogging drainage. The application can significantly improve the utilization efficiency of waterlogging drainage resources by means of two-dimensional region division, key node identification and lever density sorting, and preferentially processing high-lever nodes and units.

The invention relates to the technical field of urban inland inundation early warning, and provides an urban inland inundation waterlogging evaluation method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining low-resolution DEM data and geographic vector data of a target urban region; the geographic vector data comprises road vector data and river vector data; performing resampling on the low-resolution DEM data to obtain high-resolution DEM data; performing correction processing on the road vector data based on the high-resolution DEM data so as to perform elevation sampling on a starting point and an end point of a main road and perform elevation sampling on a starting point and an end point of a non-main road to obtain road elevation data; performing elevation correction on the river vector data to obtain river elevation data; performing flooding depth calculation according to the road elevation data and the river elevation data; and performing flooding risk assessment based on the calculated flooding depth. According to the method, the accuracy of calculating the waterlogging depth of the urban inland inundation can be improved, so that the accuracy of risk early warning evaluation is improved.

The present application belongs to the technical field of urban public facilities equipment, and relates to a method for collecting and recycling urban rainwater, which comprises the following steps: (1) collecting water through a four-stage source water collecting channel; (2) collecting rainwater of the urban trunk road and the four-stage source water collecting channel into a three-stage trunk road water collecting channel; (3) collecting rainwater of the urban trunk road and the three-stage trunk road water collecting channel into a two-stage regional water collecting channel; (4) filtering and depositing rainwater collected by the two-stage regional water collecting channel in a filter and depositing pool; (5) flowing rainwater of the two-stage regional water collecting channel into an urban river or a first-stage urban water conveying pipeline, and finally flowing the rainwater into a suburban reservoir; (6) conveying water of the suburban reservoir to an upstream river through a return pipeline, and opening a water intake station at each section of the return pipeline; (7) configuring a solar power supply system for the urban river to supply power; and (8) cleaning the surface water collecting channel. The method can collect and utilize rainwater, avoid flooding of urban roads by rainwater, and improve the utilization rate of rainwater.

The application discloses a kind of electric drive axle speed limiting fixed block and containing its modular electric drive axle, wherein electric drive axle speed limiting fixed block includes assembly plate, the side of the assembly plate is swingly provided with bending frame, the end of the bending frame is fixedly connected with pedal, the side of the assembly plate is fixedly connected with arc frame.The application realizes a kind of electric drive axle speed limiting fixed block by the mutual cooperation of assembly plate, bending frame, pedal, arc frame, clamping groove, clamping strip, fixing frame, rotating shaft, torsion spring, recessed groove, movement port, movement rod, baffle, external block, return spring, sliding slot, sliding block, connecting plate, through port and bearing, in the process of use, it is by the distance of mechanical limit pedal stepped down, to the whole electric drive axle is speed limited, without using electric signal transmission, driver needs foot to step on pedal to control speed, so in urban area, especially some buses or engineering vehicles, the highest speed can be well limited.

The present application relates to the field of rail transit, and specifically provides a regional multi-mode rail transit network passenger flow distribution prediction method, medium and computer device, wherein the regional multi-mode rail transit network passenger flow distribution prediction method comprises the following steps: improving the K-shortest path search algorithm according to the hierarchical characteristics of the pre-constructed regional multi-mode rail transit network; constructing a set of feasible paths between any OD based on the pre-generated passenger flow OD matrix of the "region + urban area" and the improved K-shortest path search algorithm; and integrating the set of feasible paths between any OD into a travel path probability selection model to realize the passenger flow distribution of the regional multi-mode rail transit network. Through such a structure, more scientific integrated analysis of the passenger flow demand of the regional rail transit network can be provided, so as to meet the diversified travel demands of passengers in different regions, with different functions and different speeds.

The application discloses a shared support for steel beam assembly and box girder cast-in-situ and a construction method, the shared support comprises an expanded foundation group, a steel pipe column group and a protection platform, the expanded foundation group is arrayed, the steel pipe column group comprises a standard section and an adjusting section, the bottom end of the standard section is connected with the corresponding expanded foundation group, the top end of the standard section is connected with the adjusting section, the top end of the adjusting section is provided with a transverse distribution beam, a connecting system is arranged between adjacent standard sections, the connecting system comprises a transverse connecting system and a longitudinal connecting system, the protection platform is arranged on the connecting system and is not higher than the top end of the standard section. According to the shared support for steel beam assembly and box girder cast-in-situ and the construction method, the shared support is installed once, the lower part is used for normal vehicle passing, the upper part is used for steel beam assembly firstly and then is used for box girder cast-in-situ operation, and the bridge construction under the narrow operation condition in the urban area is met.

The invention discloses a low-altitude medical rescue aircraft site selection and scheduling optimization method based on adaptive large neighborhood search, and the method comprises the steps: obtaining a weight evaluation result of each medical rescue demand point according to the multi-dimensional basic data of an urban region; according to the demand point weight evaluation result, constructing a site selection-demand allocation mixed integer programming model; according to the mixed integer programming model, obtaining an initial feasible solution through K-means clustering and a greedy heuristic algorithm; according to the initial feasible solution, obtaining an optimal solution through iterative operation of a destruction operator and a repair operator and local search of a variable neighborhood descent method; and according to the optimal solution, obtaining a temporary take-off and landing point layout scheme and an emergency rescue scheduling scheme. According to the method, the purposes of minimizing global rescue response time and realizing fair and efficient coverage of medical rescue resources are achieved through scientific site selection and reasonable configuration of rescue resources of temporary take-off and landing points.

The application discloses a city traffic network evaluation and optimization method and system based on different interests, and relates to the technical field of traffic network analysis. Firstly, based on road network information, traffic flow and passenger flow data, three directed and weighted complex networks representing different interests are constructed: high-speed traffic and convenience network, urban motor vehicle road traffic and convenience network, and public transportation network. Then, the weighted edge community detection algorithm is used to divide each network into communities, and the traffic flow, passenger flow, vehicle speed and average travel time of each community area are evaluated. Through network connectivity analysis, the traffic accessibility of each area is evaluated. Combined with population density, enterprise distribution and other data, the weighted vertex importance algorithm is used to identify important nodes and evaluate their rationality and role. Finally, according to the evaluation results, optimization schemes such as road repair, widening, new road construction and additional public transportation lines are proposed.

This invention concerns an innovative method and device for recording and analyzing road surface smoothness, implemented via a telematics device-main unit (1) installed on a transport vehicle [e.g., truck, bus, etc.] (7) performing independent tasks, such as waste collection, goods transportation, passenger transport, or surveillance. The telematics device - main unit (1) records acceleration [vertical - longitudinal - lateral] (8) and angular velocity through the integrated three-axis accelerometer (2), gyroscope (3), and GPS receiver. Subsequently, the processor-controller (6) correlates the data with geographic coordinates and transmits them via the cellular communication module (5) to the cloud-based computing platform (9), where data is visualized on a GIS map with color-coded smoothness indicators, alert algorithm output, and administrative classification [Municipality, Region, Highway] (10). The device automatically calculates the vertical axis when the vehicle is stationary, regardless of the mounting orientation. It further applies corrections in cases of high longitudinal or lateral acceleration by filtering out vibrations unrelated to road surface degradation. The platform displays the latest measurements for each point, maintains historical records, and activates alerts only when new wear or damage is detected. The data is categorized into geographic units (municipalities, regions, highways), enabling the production of statistical and comparative reports per area, thereby supporting evidence-based planning and prioritization of maintenance interventions.

The utility model relates to an all-in-one snow sweeper chassis power system and a snow sweeper, which comprise a cab, an engine, an operating device, a driving device, a first transfer case and a second transfer case which are arranged on a chassis, and the engine is arranged at the lower end of the cab and connected with the first transfer case through a transmission shaft. The first transfer case is connected with the second transfer case through a transmission shaft, and the first transfer case and the second transfer case are connected with the operation device and the driving device respectively. All-wheel drive is achieved through the first transfer case and the second transfer case, and the all-wheel-drive snow remover adapts to wet and slippery road conditions of snow removal operation, has good drive capacity on the wet and slippery road conditions, can be applied to road conditions such as high-speed road conditions, airports and urban areas and is high in vehicle practicability.

The application provides a method for calculating multi-scale land cover change contribution degree and its correlation, wherein the method for calculating the contribution degree comprises the following steps: taking a national region, a natural regionalization region, a province and a typical urban area as multi-scale division regions; obtaining multiple land cover changes according to land cover categories; calculating population contribution degrees in multiple comparison modes according to population data in the multi-scale division regions; and calculating land cover change contribution degrees in multiple comparison modes according to the area of each land cover change in the multi-scale division regions. The land cover change in the multi-scale division regions and the population factor can be used to calculate the contribution degrees in multiple comparison modes. The multi-scale and quantitative method for calculating the contribution degrees is not easily affected by a few data deviations, the conclusion is closer to the actual situation, and thus the reference demand of the current land cover change on land policy tendency can be met.

The invention discloses an urban river-crossing large-span bridge side span incremental launching construction method, and relates to the technical field of bridge incremental launching construction.The method comprises the following steps that a steel beam is divided into an incremental launching main beam and a suspended splicing main beam, the incremental launching main beam is manufactured in a partitioned mode, and the suspended splicing main beam is integrally manufactured; after being manufactured, the pushing main beam and the suspended splicing main beam are spliced and accepted respectively; assembling platforms, pushing temporary piers and guide beams are arranged on the two sides of the river channel, and pushing equipment is installed on the pushing temporary piers; different requirements of land road and water road transportation in urban river-crossing construction are met through differentiated steel beam manufacturing and transportation schemes, river channel navigation interference is avoided in combination with a circulating pushing mode, safety risks caused by interference of synchronous construction of a main tower and a steel beam are reduced, and the construction efficiency and environmental adaptability are greatly improved; and the construction quality and the bridge structure safety can be guaranteed in an all-around manner through the operation of stably pushing the temporary pier structure and synchronously tensioning the stay cable in the suspended splicing stage by a multi-link acceptance flow.

The invention discloses an urban area division and retrieval method and system based on GPS error homogeneity, which are applied to the technical field of information, and the method comprises the following steps: constructing an urban area into a rectangular area of a square grid, and based on a first GPS matching sequence and matching points in the GPS matching sequence, obtaining a second GPS matching sequence; calculating the earth great circle distance between the matching point and the corresponding positioning point in the grid, namely taking the earth great circle distance as the positioning error of the matching point; calculating to obtain a GPS error distribution vector of the grid according to the positioning error of the matching point in the grid; constructing a similarity matrix based on the GPS error distribution vector and the rectangular region, and extracting a feature vector; performing clustering and region division on the feature vectors to obtain sub-regions; and by establishing an index from the grid number to the sub-region number, completing the region retrieval of the GPS coordinate point.

This invention belongs to the field of smart city and urban computing technology, and specifically provides a method for urban region representation based on multi-view joint learning and structure-aware contrastive analysis. It includes the following steps: S1: Acquisition of multi-source urban data and initial multi-view construction; S2: Enhanced feature encoding based on multi-view joint learning; S3: Consensus representation generation based on global cross-view feature aggregation; S4: Structure-aware contrastive learning and multi-task joint optimization; S5: Outputting the final dense urban region representation vector. This invention, through a multi-view joint learning module, utilizes a self-attention mechanism and an adaptive fusion strategy to achieve effective interaction of complementary information between different views, significantly enhancing the quality and robustness of single-view features. This enables MVJC to perform excellently in downstream tasks such as crime prediction and land use classification, significantly improving prediction accuracy and clustering effects.

The application relates to a position calculation method of a material sorting site based on a clustering analysis and an area method Floyd algorithm, and the application comprises the following steps: 1, K-means clustering analysis is carried out on cell coordinates in a city area; 2, intersections in each area are screened out by using an area method; 3, a suitable delivery point position is found by using a Floyd algorithm to traverse the intersections in the cell; 4, K-means clustering analysis is carried out on the delivery point positions of the whole city, and steps 2 and 3 are repeated to find the position of a large-scale sorting material center. The application can reduce the traversal objects of the Floyd algorithm by screening the intersection coordinates through clustering and the area method, thereby reducing the calculation amount, screening the most suitable intersection position as the material delivery point position, and scientifically screening the material delivery points to obtain the position of a suitable large-scale sorting station.

This invention belongs to the field of urban computing and data mining technology, and specifically to a multi-view urban region embedding method based on spatial functional consistency. It includes the following steps: S1: multi-view data collection and processing; S2: spatial functional consistency in-view representation learning; S3: cross-view interaction within the region; S4: cross-view interaction between regions; S5: dual-feature attention fusion; S6: downstream task application. This invention effectively suppresses information interference caused by noisy edges and weakly correlated connections, improving the accuracy and stability of local structure modeling. Simultaneously, it enhances the global semantic connectivity and cross-view information propagation capabilities of the region representation. Furthermore, through a dual-layer attention fusion mechanism, it achieves adaptive integration of multi-view features and inter-regional correlation features, further improving the discriminativeness, robustness, and generalization ability of the final region embedding representation.

The invention discloses an intelligent decision-making method and system for urban industrial layout suitability evaluation, and relates to the field of urban planning regional development, and the method comprises the steps: collecting multi-source heterogeneous data of a target urban region, building a standardized space-time database, and building an initial evaluation factor system based on the standardized space-time database; loading the standardized space-time database to a three-dimensional geographic information unit, and constructing a city multi-agent simulation environment; utilizing a causal inference engine to calculate a causal net effect of the candidate industrial layout scheme on a preset urban index based on historical data in the standardized space-time database, and generating a causal net effect evaluation report; and fusing the real-time data of the initial evaluation factor system, the current state of the urban multi-agent simulation environment and the causal net effect evaluation report to generate a dynamic decision state vector. The crossing from static point location evaluation to dynamic path planning is realized, and the perspectiveness of industrial layout decision making is improved.