117 results about "Geoweb" patented technology

The invention discloses a flood detention area emergency evacuation early warning method based on environmental perception and intelligent analysis, and relates to the technical field of flood control and disaster mitigation, and the method comprises the steps: collecting the original data of a flood detention area site, and forming a monitoring array; a monitoring array is divided into a plurality of monitoring units according to geographic grids, a rainfall permeation model is established according to rainfall data and soil humidity data, a surface runoff field is constructed in combination with terrain elevation data, and the confluence direction of the runoff field is calibrated through water level data; based on a rainfall penetration model and a surface runoff field, generating a flood detention area inundation evolution sequence, segmenting into an inundation grade map according to a time step length, planning a flood detention area emergency evacuation path, matching with a road network in a geographic information system, generating an optimal evacuation path, and issuing graded early warning information to an early warning area. And sending a withdrawal instruction to residents in the flood detention area through the emergency broadcasting system. According to the invention, by establishing a partition early warning mechanism and a differential early warning strategy, accurate delivery and efficient transmission of early warning information are realized.

The invention discloses a high-precision three-dimensional point cloud visualization method, electronic equipment and a storage medium, and belongs to the technical field of geographic space information systems.The high-precision three-dimensional point cloud visualization method comprises the steps that S1, a point cloud file is input, and meta-information of the point cloud file is obtained; s2, performing scalable data geographic gridding processing on the point cloud file meta-information to obtain a basic grid object; s3, adopting a data stratified sampling method to obtain a multi-level grid object; s4, constructing a multi-level index file based on the multi-level grid, and outputting the multi-level index file; s5, performing high-availability, high-concurrency and compression processing on the output multi-level index file; and S6, performing real-time hierarchical scheduling rendering on the point cloud based on the processed multi-level index file. A point cloud is quickly split into small blocks by using a gridding technology, then parallel processing is performed, a hierarchical rendering level is generated by performing sub-sampling on a whole data set from bottom to top by using a plurality of sampling strategies, and meanwhile, a quick layering strategy is introduced, so that the throughput is remarkably improved.

The invention relates to the technical field of urban geological survey, in particular to an urban geological survey method based on a big data cloud computing technology, which comprises the following steps: based on urban geological drilling detection data, land subsidence monitoring data and underground pipe network distribution data, grouping the data according to geographic grid units and time points, performing statistical analysis to obtain a geological parameter statistical set; and based on the geological parameter statistical set, setting multiple levels of storage partitions according to a data updating frequency, and establishing a geological data partition storage table. According to the method, urban geological data are grouped according to geographic grid units and time points, a multi-level storage partition mechanism is established, hierarchical storage and compression of the data are realized, the occupied storage space is reduced, and the data access speed is increased; key monitoring areas are screened based on a geological parameter change rate threshold, differential compression storage strategies are adopted for different areas, and the overall storage efficiency is optimized on the basis of guaranteeing important data integrity.

The invention provides a small watershed non-point source pollution key source area determination method which can be applied to the technical field of pollutant analysis and the field of environmental science. The small watershed non-point source pollution key source area determination method comprises the following steps: acquiring multiple groups of rainfall runoff process information corresponding to a to-be-investigated geographic area; generating N groups of pollutant output quantity theoretical values based on the multiple groups of rainfall runoff process information and the N groups of land information; generating N groups of pollutant transmission resistance values based on pre-collected N groups of geographic information in one-to-one correspondence with the N geographic grid units; based on the N pollutant output quantity theoretical values and the N pollutant transmission resistance values, generating N pollutant output quantity actual values in one-to-one correspondence with the N geographic grid units; and on the basis of the N pollutant output quantity actual values, screening out at least one target geographic grid unit from the N geographic grid units to serve as a small watershed non-point source pollution key source area.

The invention provides an operation situation analysis method and device, equipment and a storage medium, and relates to the technical field of data processing, in particular to the technical field of intelligent transportation, automatic driving, large models and data analysis. The specific implementation scheme is as follows: according to a plurality of geographic grid units formed by dividing a target operation area, carrying out gridding aggregation on operation data in a space-time knowledge graph to obtain aggregation operation indexes of the plurality of geographic grid units; generating an operation thermodynamic diagram representing demand distribution according to the current order data of the plurality of geographic grid units; determining the scheduling efficiency of the plurality of geographic grid units according to the aggregation operation index; and for a target grid unit in the operation thermodynamic diagram, predicting an expected operation index of the target grid unit at a future target moment according to the current operation index, the historical operation index and the scheduling efficiency of the target grid unit. According to the scheme provided by the embodiment of the invention, the real-time diagnosis and future prediction of the operation situation are realized by aggregating, presenting and analyzing the data in the space-time knowledge graph.

The invention relates to the technical field of knowledge maps, in particular to an intelligent networked automobile data processing system based on data elements and knowledge maps, and the system comprises a data element definition module which analyzes original intelligent networked automobile data elements, distinguishes the original intelligent networked automobile data elements into a vehicle static parameter set and a vehicle dynamic parameter set, and forms a structured map blueprint. According to the method, element analysis is carried out on the intelligent network connection automobile data, and the intelligent network connection automobile data is divided into the static parameter set and the dynamic parameter set, so that the data has hierarchical structural characteristics, and the controllability and definition of subsequent data processing are improved. And in combination with differentiated structure construction of the static storage layer and the dynamic storage layer, a hierarchical data configuration model with clear logic is formed, and the data scheduling efficiency and the system load stability are improved. A geographic grid coding mode is introduced, space division is carried out on entity data with position attributes, spatial dimension information is made to have high-density indexability, and positioning and regionalization operation can be achieved easily.

Systems, methods and devices for location-based services are disclosed in the present invention. A multiplicity of network devices, a database, and a server platform in network-based communication. The database stores a space-network model binding IP addresses and physical locations. The server platform is operable to generate at least one geofence in the space-network model and specify entitlements for the location-based services within the at least one geofence. The at least one geofence and specific entitlement are stored to the database. The multiplicity of network devices is configured to learn the space-network model and the at least one geofence and perform tasks based on the entitlements specified for the location-based services within the at least one geofence.

The invention provides a distributed quotation data collaborative pushing method and system. The method comprises the following steps: establishing a dynamic association model with a network congestion trend by collecting transmission path environment fluctuation data, and generating environment network association parameters; real-time quotation data is cut by adopting double dimensions of a geographic grid boundary and a commodity classification hierarchy, and dynamic binding of data blocks and storage nodes is realized through a scalable hash ring; generating a dynamic routing strategy based on the environmental parameter energy integral, the geographic grid coverage density and the commodity level update rate, and calculating a transmission path priority by combining a geographic extension direction and a data volume growth trend; and constructing a path state evolution model, evaluating a node failure probability and spectrum energy attenuation, and when a path correction factor exceeds a threshold value, triggering a multi-channel push mechanism. According to the technical scheme provided by the invention, distributed quotation data pushing has a network state self-adaptive multi-path cooperation capability.

The invention discloses a geographic network analysis method based on feature and structure distribution offset. The method comprises the following steps: S1, obtaining a traffic flow data set; s2, acquiring a causal attention sampling weight; s3, acquiring a target node; s4, performing sample reweighting; and S5, outputting a predicted traffic flow data set. According to the method disclosed by the invention, the attention mechanism and the causal-guided sampling technology are fused, the node sampling process is optimized, and the dependence of the model on background characterization is reduced. According to the method, an attention mechanism and a causal theory are combined, the sampling weights of target node neighbors of the same type and the sampling weights of target node neighbors of the different types are obtained respectively, and the purpose is that a model recognizes nodes having a strong causal relationship with labels or recognizes nodes more similar to the target nodes. In this way, the invariant characterization is significantly improved, and the dependence on the background characterization in accidental or specific modes is reduced.

The invention relates to the technical field of logistics transportation monitoring, in particular to a method, a device, equipment and a medium for judging deviation of a vehicle driving route, and the method comprises the steps: converting a first track point set on a target driving route into a first geographic grid code set; acquiring a second track point formed on the actual driving route of the target vehicle, and converting the second track point into a second geographic grid code; and comparing the second geographic grid code with the geographic grid codes in the first geographic grid code set, and judging whether the target vehicle deviates from the target driving route or not according to a comparison result. Analysis and judgment of deviation between the actual driving route of the vehicle and the pre-specified route are realized under the condition of not using map service or professional GIS (Geographic Information System) software.

The invention relates to an electric vehicle track synthesis method based on differential privacy, and the method is characterized in that the method comprises the steps: obtaining a real electric vehicle track data set of an urban geographic space, carrying out the meshing of the urban geographic space according to regions, and obtaining a divided geographic grid; according to a geographic grid and a road network of an urban geographic space, track movement mode extraction is carried out on a real electric vehicle track to obtain a geographic grid transfer matrix and a region transfer matrix which meet differential privacy constraints; according to the charging pile set in the urban geographic space, modeling is carried out on the consumption of the vehicle driving electric quantity, and an electric quantity state updating rule and a charging guiding strategy of the vehicle are obtained; based on Markov sampling, combined with the region transfer matrix, the grid cell transfer matrix, the electric quantity state updating rule and the charging guide strategy, a synthetic track is generated, the legality of the synthetic track is verified, and an electric vehicle synthetic track data set is obtained; according to the method, the privacy leakage risk is effectively avoided, electric vehicle trajectory data with high behavior fidelity can be generated, and the method is suitable for various privacy protection data analysis and intelligent travel decision-making scenes and has good engineering practicability and popularization prospects.

The invention discloses a bank customer grid management method based on a geographic space relationship, and belongs to the technical field of geographic information processing. A bank customer grid management method based on a geographic space relationship comprises the following steps: S1, creating a geographic grid by selecting a single or multiple polygons or administrative divisions on a map, and storing the created geographic grid in a database in a WKT text form; s2, obtaining accurate longitude and latitude coordinate points of the customer through an on-site visiting or address decoding function, storing the accurate longitude and latitude coordinate points into a database, and binding the accurate longitude and latitude coordinate points with customer information; s3, reading the WKT text and the longitude and latitude coordinate points of the customer in the database, and establishing a binding relationship between the customer and the geographic grid through a point-surface relationship between the longitude and latitude coordinate points of the customer and the corresponding region of the geographic grid; and S4, one or more customer managers are set up for each geographic grid to establish a customer-grid-customer manager association relationship, and the association relationship is applied to various field scenes.

The invention provides a satellite-borne SAR constellation task planning method and device for maritime ship rescue, and belongs to the field of satellite-borne SAR, and the method comprises the steps: building a target ship movement range prediction model under physical constraints according to the maximum navigation speed and the maximum movement radius of a target ship in combination with the calculation of a geographic grid; constructing an adaptive priority strategy, analyzing geographic grids which a target ship may pass through, designing a trajectory prediction method based on Gaussian probability distribution according to the course and speed of the ship, and adaptively adjusting the priority of the geographic grids according to the probability; if the coverage rate of the geographic grids exceeds a set threshold value, assigning different priorities to each geographic grid according to the predicted track, otherwise, adopting equal priorities; and designing an MSDDEE algorithm, and respectively executing a multi-cross individual generation strategy, a feasibility-based individual selection strategy, a local left shift strategy and a population restart strategy to optimize task planning of search and rescue ships. The search efficiency is improved.

The present invention provides a method for evaluating the vulnerability of marine hazard-bearing bodies based on SETR and geographic grids, which belongs to the field of intelligent ocean data processing technology. The method comprises the following steps: establishing a sample library, constructing a semantic segmentation model of remote sensing images of marine hazard-bearing bodies based on a SETR network, constructing a grid spatiotemporal data set using geographic gridding technology, establishing a grid and spatial value density hazard-bearing body vulnerability assessment method, calculating a marine hazard-bearing body vulnerability index, and realizing the vulnerability assessment of marine hazard-bearing bodies in a region. In view of the difficulties in investigating and extracting massive marine hazard-bearing bodies and the lack of intelligent early warning and monitoring technical means, a marine hazard-bearing body vulnerability assessment model based on SETR and geographic grids is constructed using deep learning, geographic gridding, spatial value density, disaster science and other technologies, so as to realize intelligent and rapid evaluation of marine hazard-bearing bodies in a large range of scenarios, which is of great significance to the intelligent monitoring and early warning of disasters of marine hazard-bearing bodies under typhoon disasters and the refined management of disaster prevention and mitigation.

The invention discloses a gain control parameter management method and device for a high-orbit SAR, and relates to the technical field of synthetic aperture radars, and the method comprises the steps: dividing a preset geographic space region into a plurality of geographic grids; collecting scene data of a corresponding scene in each geographic grid, wherein the scene data comprises geometric model data and physical parameters of each ground feature; collecting a high-orbit SAR satellite track and a satellite-ground relative position; acquiring radar position parameters of each ground feature; calculating scattering characteristics of each ground feature according to the scene data; establishing a corresponding relation between a load manual gain control parameter of the radar and the scattering characteristic of each ground object to obtain manual gain control data; a relational database is used for storing ground feature geometric module data, ground feature physical parameters, ground feature scattering characteristics, high-orbit SAR satellite tracks, satellite-ground relative motion and manual gain control data. The effectiveness of gain control parameter management of the SAR is improved.

A system comprising one or more processors and one or more non-transitory computer-readable media storing computing instructions that cause the one or more processors to perform operations: receiving first real-world geolocation data, generating one or more first virtual encounters based at least in part upon the first real-world telematics data and the first real-world geolocation data; generating one or more second virtual encounters based at least in part upon the first real-world environmental data and the first real-world geolocation data; providing a first virtual map; providing a first virtual character associated with the first real-world user; and simulating the first virtual map and the first virtual character in a virtual game, simulating at least one of (i) the one or more first virtual encounters or (ii) the one or more second virtual encounters for the first virtual map and for the first virtual character. Other embodiments are described.

The invention discloses a building identification method, device and system, and a storage medium. The building identification method comprises the following steps: S1, obtaining geographic space information of buildings in a plurality of data sources; s2, coding the building according to the geographic space information to obtain a building grid coding set table; wherein the building grid code set table comprises a building ID of each data source and a grid code corresponding to the building ID; s3, according to the building grid coding set table, obtaining a spatial relation data table oriented to a geographic grid; wherein the spatial relation data table comprises all data source building ID sets and the number of corresponding overlapped grids; and S4, according to the spatial relationship data table oriented to the geographic grid, calculating the coincidence condition and degree of the corresponding buildings in the plurality of data sources so as to realize building matching. By adopting the technical scheme of the invention, the contradiction between the accuracy of code identification and the high efficiency of code matching is balanced to the greatest extent.

The invention discloses a path planning method based on a city engine and an unreal engine. The method comprises the following steps: completing basic data preparation, rule definition, model generation and visual presentation and analysis, and establishing a city model; secondly, constructing a vehicle motion model in an unreal engine, and simulating weather; the three-dimensional static model and a dynamic model in an unreal engine are fused to generate an urban environment; carrying out geographical gridding on the urban area; introducing a trafficability map and physical restrictions of the vehicle, and setting the trafficability map of the vehicle; an improved A * algorithm based on geographic gridding is introduced, path planning is conducted, the improved A * algorithm is used, and path optimization is achieved through a heuristic function and a penalty function; and outputting the generated path plan.

This invention discloses a method for earthquake landslide hazard zoning based on subtractive clustering ANFIS, belonging to the field of earthquake landslide hazard zoning technology. The method includes the following steps: collecting earthquake landslide monitoring data including seismic data, topographic data, meteorological and hydrological data, and image data; extracting features from the image data to obtain feature-extracted data; based on the earthquake landslide monitoring data, using a subtractive clustering algorithm to determine the initial cluster centers of the earthquake landslide area, thereby obtaining initial clustering information for the earthquake landslide; and combining the earthquake landslide hazard levels and their monitoring data within each geographic grid unit to draw an earthquake landslide hazard zoning map. The data acquisition technology, subtractive clustering algorithm application technology, ANFIS model construction technology, and data calibration technology in this method are closely integrated with modern information technology. The hazard calibration coefficient is used to calibrate the hazard index, improving the accuracy of earthquake landslide hazard assessment.

The invention provides a take-out order scheduling method and system, a storage medium and a program product, and relates to the field of personnel or project management, and the method comprises the steps: generating a path network according to the coordinates of a pickup point and a delivery point of a new order; determining a group of geographic grid indexes covering the path network based on a preset grid cell size to obtain a new order path index set; calculating an intersection index set of the new order path index set and the future path index total set of the candidate rider; and when the number of the unique identifiers of the geographic grid indexes in the intersection index set exceeds a preset path matching threshold value, adding the new order into the order sequence of the target candidate rider with the highest comprehensive score, and adjusting the planned path corresponding to the target candidate rider to complete the scheduling of the new order. By implementing the method, the problem of misjudgment of the smoothness caused by path simplification can be relieved, and the matching accuracy of the order and the rider is improved, so that the overall delivery efficiency is improved.

The invention discloses an energy supply side optimization management system and an implementation method, and relates to the technical field of energy management. The method comprises the following steps: acquiring source end data of an energy supply side, analyzing the source end data through a multi-level protocol adaptation engine and a dynamic rule matching engine, and extracting various energy features and energy supply side GIS (Geographic Information System) information; constructing a multi-energy flow topology constraint matrix based on energy features, performing fine-grained geographic grid division based on energy supply side GIS information, and determining grid-level energy dynamic parameters; performing dynamic trend adjustment on the grid-level energy dynamic parameters in combination with the multi-energy-flow topology constraint matrix, and determining a grid-level energy dynamic prediction map; searching an optimal tradeoff solution set through a population aggregation and dispersion search algorithm; and carrying out constraint solution on the optimal tradeoff solution set in combination with the safe operation boundary, and determining an energy scheduling optimal solution. According to the invention, the accuracy and foresight of energy management are improved, the loss link is accurately traced, and the system is driven to continuously evolve towards the low-carbon and high-efficiency direction.

The present disclosure is related to an electronic device and a method for cluster based object sensing. A method for object sensing comprises: selecting one or more network nodes from a cluster of network nodes associated with a geographic grid; and triggering the one or more network nodes to sense one or more objects in the geographic grid.

Disclosed here are methods, systems, and apparatuses for optimizing in-building network coverage through aggregation of usage data, network data, and other performance metrics and geospatial analysis employed to map network coverage data onto a geographic grid, facilitating spatial visualization of performance. The network coverage data is mapped to the buildings data to create a spatial visualization. A model is then applied to the network coverage data and the spatial visualization to identify buildings with a network coverage score below a threshold, and an appropriate action is performed based on the identification.

To facilitate efficient entity resolution, systems and methods include a first dataset is received from a first database associated with a first entity and a second dataset is received from a second database associated with a second entity. A geo-grid is mapped to a geographical area covering the first entity data records and the second entity data records. A grid matching area in the geo-grid is generated for each first entity data record based on latitude data and longitude data of each first entity data record. Candidate matching records are determined from the second entity data records based on respective grid matching areas. Actual matching records are determined from the candidate matching records based on a threshold for a trigram similarity between each candidate matching record and the respective first entity data record. The actual matching records are associated with the respective first entity data record in the first database.

The present invention discloses a method for evaluating and warning marine disaster-bearing bodies based on unmanned aerial vehicles and geographical grids, belonging to the technical field of marine disaster-bearing body evaluation, and comprising the following steps: Step S1. Determining the evaluation area and establishing a monitoring network: determining the range of the disaster-bearing body area to be evaluated, burying a plurality of first sensors within the disaster-bearing body area, dividing geographical grids based on the positions of the first sensors, connecting the first sensors to a preset data processing system to form a monitoring network, and realizing real-time collection and transmission of data; Step S2. Receiving monitoring data and preprocessing the data: receiving and monitoring marine disaster data, when the marine disaster data reaches a first preset threshold, enabling the first sensors to collect corresponding data of the disaster-bearing body area at a preset frequency, collecting the data of the first sensors, and performing data preprocessing. The invention improves the real-time performance and accuracy of the evaluation, and enhances the monitoring and warning capabilities for marine disasters.

The invention relates to the technical field of computers, in particular to a site selection model construction method based on a knowledge graph, a site selection method based on a site selection model, computer equipment for implementing the methods, a computer readable storage medium and a computer program product. The site selection model construction method comprises the following steps: acquiring a data set for site selection analysis; extracting data from the data set according to the knowledge graph framework and constructing a knowledge graph; extracting knowledge graph characteristics taking the user identifier as a main key from the knowledge graph; dividing the site selection area into geographic grids, and extracting grid features; fusing the knowledge graph features and the grid features to form a fused feature set; and based on the fused feature set, a machine learning algorithm is used to train a site selection model, and the site selection model is used to predict the site selection value of each geographic grid.

This invention discloses a building identification method, apparatus, system, and storage medium, comprising: step S1, acquiring geospatial information of buildings from multiple data sources; step S2, encoding the buildings according to the geospatial information to obtain a building grid code set table; wherein, the building grid code set table includes: the building ID of each data source and its corresponding grid code; step S3, obtaining a spatial relationship data table oriented towards the geographic grid based on the building grid code set table; wherein, the spatial relationship data table includes: the set of building IDs of all data sources and the number of corresponding overlapping grids; step S4, calculating the overlap and degree of corresponding buildings in multiple data sources based on the spatial relationship data table oriented towards the geographic grid, so as to achieve building matching. The technical solution of this invention maximizes the balance between the accuracy of coding identification and the efficiency of coding matching.

This application relates to the field of data analysis technology, and in particular to a method, apparatus, computer device, storage medium, and computer program product for extracting profile lines from oblique photogrammetry data. The method includes: dividing the oblique photogrammetry data into multiple block files according to a geographic grid, with each block file containing a root node corresponding to a specific block file, and hierarchically storing node files corresponding to child nodes derived from the root node; identifying target block files and target node files that intersect with the projection line data; reading specific geometric data from the target node files, with the geometric data associated with profile line extraction; using a preset intersection algorithm to traverse the geometric data in all target node files to obtain profile points, and connecting the profile points to generate target profile lines. This method can improve the efficiency of profile line extraction in large-scale oblique photogrammetry data and reduce the computational load of profile line extraction.

The invention relates to the technical field of fire risk early warning, and particularly provides a power grid facility fire danger early warning method and device, and the method comprises the steps: obtaining fusion perception data of a geographic grid to which a to-be-analyzed power facility belongs; taking the fused sensing data as a pre-trained neural network model to obtain a fire danger early warning degree of the to-be-analyzed electric power facility output by the pre-trained neural network model; performing fire danger early warning on the to-be-analyzed electric power facility based on the fire danger early warning degree of the to-be-analyzed electric power facility; wherein the fusion sensing data comprises at least one of satellite heat source point data, meteorological element data and power grid data. According to the technical scheme provided by the invention, the space-time precision of fire danger prediction and the disaster prevention toughness of a power grid are effectively improved, and accurate technical support is provided for active defense strategies such as activation of a fire barrier of a power transmission corridor, dynamic load scheduling and the like.

The invention relates to the technical field of land value evaluation data processing, and discloses a land value evaluation and circulation transaction system based on multi-source heterogeneous data fusion, which comprises the steps of converting policy texts, environment monitoring and market transaction data into standardized influence vectors, calculating an information unbalance degree through geographic grid projection to represent data conflict intensity, and calculating a data conflict degree; according to the method, internal contradictions of multi-source data are spatially developed, conflicts masked in traditional assessment are quantified into operable risk indexes, meanwhile, dynamic confidence degree modulation is achieved in combination with transient feature analysis, and the reliability of the system is improved. Land value judgment has trend insight and risk early warning capabilities, and a high-credibility decision-making basis is provided for circulation transaction.