72 results about "Spatial query" patented technology

The invention discloses a 3DTiles data storage method and a map data query method.The 3DTiles data storage method comprises the following steps that (1) an LOD hierarchy pyramid type hierarchy table is established, and an LOD range index is created; 2) generating a three-dimensional object into an agent point, and segmenting a tile according to a KD-tree structure to construct a three-dimensional KD-tree index tree; and 3) storing the data of the KD-tree leaf node into a GridFS of MongoDB multi-mode storage, mapping a file path into a unique hash value, writing the unique hash value into a corresponding node according to a KD-tree node storage structure, and creating a geographic spatial index. The method creatively solves the problems that file system management is difficult due to the fact that the number of files is large, a hierarchical structure based on a file directory is difficult to support efficient spatial range retrieval, and the spatial query response time is reduced to the millisecond level in combination with a three-dimensional KD-tree index and a MongoDB geographic spatial index.

The invention discloses a distributed storage and retrieval method for black soil cultivated land quality space vector big data, and relates to the technical field of data storage and retrieval. The method comprises the steps that firstly, according to space information and attribute information of black soil cultivated land quality space vector data, partition coding design is conducted on row keys, column families and Region partitions of a bottom storage system of a distributed non-relational database HBase, and a storage model used for storing the space vector data is obtained; then obtaining a Geohash coding grid of the space vector data in the storage model through a self-adaptive hierarchical division coding method; performing dimension raising conversion on the Geohash coding grid into a Geohash space grid, and constructing a distributed hierarchical spatial index model according to the Geohash space grid and an index unit of the R * tree; and finally, executing the spatial query request in the distributed hierarchical spatial index model through a spatial parallel retrieval method to obtain a spatial retrieval result. According to the method, the mass space vector data of the large-scale black soil cultivated land can be efficiently stored and retrieved.

The invention provides an after-batch stock land data management method and system. The method comprises the steps of designing an after-batch stock land management database structure, and constructing a land supply data graph layer, a batch land data graph layer, a batch land data graph layer, a batch unsupplied land data graph layer, an overdue working land data graph layer and an idle land data graph layer; collecting multi-source data, performing preprocessing, problem treatment and quality inspection, and generating standardized land supply data and land batch data; constructing a land supply and approval database, and comparing and updating the land supply and approval database with data of a natural resource department system; generating a batch of unsupplied land, an overdue working land and an idle land data graph layer through overlay analysis, and constructing a batch stock land database; automatically updating graph and attribute data based on data such as territorial change investigation and the like; the functions of automatic reminding, land use unit interaction and space query are executed; and carrying out visual rendering and display on the database data, and superposing and displaying the batch stock land and planning and remote sensing image data. According to the invention, the intensive land utilization supervision efficiency can be improved.

The invention relates to a three-dimensional structure displacement stress field prediction method based on a point cloud neural operator, a medium, equipment and application. The method comprises the following steps: constructing a neural operator model for predicting a structure physical field; collecting geometric feature data of the three-dimensional structure and corresponding working condition data; training the neural operator model by using the acquired data and the query position of the internal space of the three-dimensional structure; inputting geometric feature data and working condition data corresponding to the three-dimensional structure into the trained neural operator model, and querying any spatial position in the three-dimensional structure to obtain a displacement predicted value and a stress predicted value at the corresponding position; media and equipment are realized based on the method and are applied to jet engine support displacement stress field prediction. The method can be directly used for a non-parametric complex three-dimensional structure, continuous prediction of a displacement field and a stress field of any spatial query position in the structure is achieved, the structure response prediction efficiency is remarkably improved, the calculation cost is reduced, and the method has good engineering application value.

The invention relates to a remote sensing image data processing method and system based on a Spark architecture, and belongs to the technical field of remote sensing image data processing. The method comprises the following steps: converting a collected original file into a COG format, constructing a hybrid index through a spatial dimension reduction technology, extracting metadata and establishing a metadatabase; based on the hybrid index, quickly positioning a target tile through spatial query, reading a data block, and constructing a TileLayerRDD of a spatial partition in a Spark cluster; and dynamically assembling and calculating the directed acyclic graph according to the algorithm warehouse template, and submitting the directed acyclic graph to a Spark cluster for distributed memory calculation. According to the method, rapid retrieval is achieved through the COG format and the mixed index, pre-slicing is replaced with Spark distributed computing, the storage pressure is greatly reduced, and on-demand real-time analysis and high-concurrency online service of mass remote sensing data are finally achieved through micro-service and elastic resource scheduling.

The invention discloses a multi-source heterogeneous data integration analysis treatment method, system and device and a medium, and the method comprises the steps: obtaining multi-source heterogeneous original data, carrying out the semantic mapping through a power grid business ontology library, and carrying out the coordinate dynamic normalization through a self-adaptive conversion matrix, and obtaining standardized spatial data; carrying out spatial query, dynamic buffer area calculation and protection area grading fusion through a spatial superposition optimization algorithm, and carrying out topological relation identification and regularization processing on the power line and an external linear ground feature to obtain a spatial conflict analysis result; through a three-level conflict resolution mechanism, recognition and cooperative resolution operation of geometry, attribute and temporal conflicts are carried out, and a resolved compliance space data set is obtained; and performing governance flow driving and rule adaptation through a dynamic business rule engine to obtain a spatial data governance report. According to the method, efficient integration and intelligent treatment of spatial data in the power transmission line project are realized, the data processing timeliness is remarkably improved, and spatial conflicts are eliminated.

Techniques are disclosed relating to determining a minimum search region with a threshold number of entities within the minimum search region. In some embodiments, a system selects, based on a location of a user device, a first region, where the location of the device is at a center of the first region. The system executes, based on the first region, a query on a database storing entity locations. The system increases the first region by a specified amount to generate a second search region, where the increasing is based on determining that entities returned by the first query does not satisfy an entity threshold requirement. The system executes, based on the second region, a second query on the database. In response to the second query returning a number of entities that satisfy the threshold requirement, the system causes display, at the device, of the entities returned by the second query.

The invention discloses a space query optimization method based on a Salted Key. The method comprises the following steps: step 1, data cleaning and format conversion; step 2, converting geographic coordinates of the converted data obtained in the step 1 into Geohash codes; 3, completing data storage by adopting multiple dimensions of time and space; and 4, querying the data stored in the distributed database HBase, and obtaining a query result through two query modes. The invention belongs to the technical field of geographic information systems and data storage, solves the problems of low geographic data storage efficiency and poor query performance of large-scale geographic information in the prior art, is particularly suitable for large-scale geographic data storage and real-time query, can process a large amount of data without sacrificing performance, and is high in practicability. And application requirements of traffic flow, weather forecast and the like which need to consider space and time factors at the same time can be met.

This invention discloses a dual-stream point cloud compression method and system based on semantic scene graphs, relating to the field of point cloud compression. It constructs a point cloud compression network comprising an encoder network and a decoder network: In the encoder network, semantic labels are mapped onto the input point cloud, and scene graphs and octree representations are constructed respectively. Semantic modulation parameters are generated based on the scene graph and encoded to obtain a semantic bitstream. The octree representation, under the influence of semantic modulation parameters, undergoes feature enhancement and attention probability prediction to obtain node occupancy probabilities, and a geometric bitstream is generated through arithmetic encoding. These two bitstreams serve as compressed data. In the decoder network, the bitstreams are decoded, and the octree structure and scene graph information are reconstructed. Node feature representations are recovered by combining the semantic modulation parameters. The reconstructed octree structure is mapped back to the point cloud space through spatial querying and indexing to reconstruct the point cloud. This invention solves the problem of local geometric distortion in low-bitrate octree point cloud compression, ensuring reconstruction quality while reducing the transmission bitrate.

Computer-implemented systems and methods monitor financial risk monitoring using geospatial data. The system includes a data ingestion pipeline that processes heterogeneous geospatial data, normalizes the data into a common spatial reference framework, and applies hierarchical spatial indexing. The indexed data is stored in a geospatial database configured to maintain metadata and alert rules. A financial system stores information linking financial instruments and portfolios to geospatial regions. An application programming interface (API) layer enables spatial querying, rule-based alert evaluation, and notification delivery. A user interface subsystem deployed on client devices facilitates interaction with the system through graphical dashboards, programmatic tools, or natural language inputs. The system supports real-time monitoring and automated alerting based on spatial triggers and financial exposure thresholds, enabling decision-making for risk-sensitive financial domains. The architecture supports high-throughput processing, flexible deployment, and integration with external financial systems and workflows.

The present application relates to a data query method, device, computer equipment, computer-readable storage medium and computer program product. The method comprises: querying the product introduction from the first-level storage space based on the target customer identification and target product identification of the product introduction query request; the first-level storage space includes the transaction information of the product that generated transactions within the target time period and the customer during the last transaction within the target time period; when the query fails, querying the product introduction from the second-level storage space based on the target customer identification and the target product identification; the second-level storage space includes the transaction information of each product during the last transaction with the customer; when the query fails again, querying the product introduction from the third-level storage space based on the target customer identification and the target product identification; the third-level storage space includes the transaction information of each product during each transaction with the customer; and returning the product introduction to the terminal. The use of this method can improve the efficiency of data query.

The invention relates to the field of data query, and discloses a space grid data query method based on AABB and KDTree composite index, comprising the following steps: step 1, acquiring simulation data of a part, establishing a space mapping relationship between the simulation data and a geometry of a die casting, and performing AABB space division on the geometry, the AABB space including primary AABB space division and secondary AABB space division; the primary AABB space division divides the geometry of the die casting into a plurality of topologically associated sub-regions; the sub-region is divided into a plurality of tetrahedron units by the secondary AABB space division; performing binary tree structure recombination on the tetrahedron units in the sub-regions by adopting KDTree; and 2, judging whether the target coordinate point is in the sub-region or not, traversing the tetrahedron unit of the sub-region, and remarkably reducing the calculation complexity and improving the spatial query efficiency of the large-scale grid model by introducing a spatial index structure and an algorithm optimization strategy.

The invention provides a multi-scale block spatial indexing method based on WH-MSDM, and relates to the field of spatial data management and indexing.The method comprises the steps that a WH-MSDM model is constructed; obtaining a query space range; determining the total number of all scale blocks in the query space range through the query space range and a WH-MSDM model; initializing an array; calculating a code of each block in a coordinate range in all hierarchies of the WH-MSDM model and adding the code into an array; sorting the elements in the array; and traversing and processing each code of the array to obtain an effective identifier of each current code in the WH-MSDM model, reading attribute data of the effective identifier, and completing spatial query of the WH-MSDM model. According to the technical scheme, the block coordinates in the query space range are coded, so that all blocks which do not meet the query conditions are directly removed, and the space screening efficiency is high.

The application relates to an efficient spatial keyword query method based on association rule mining, and belongs to the field of spatial keyword query. The application comprises a data preprocessing stage, an association rule mining stage, an index construction stage and a spatial keyword query stage. The association rule mining stage selects corresponding frequent item sets based on a depth control materialization strategy. The index construction stage constructs a quadtree index for the spatial part of a data set, and creates a trie and an inverted list for the text part of the data set. The query stage adopts a coarse-grained spatial query, and combines the inverted list and the corresponding materialized inverted list of the frequent item sets to perform retrieval. The application combines association rule mining, materialized inverted lists and spatial keyword query, and can greatly improve the query efficiency of spatial keywords.

The invention provides an Internet of Things security protection method and system for Internet of Vehicles intrusion detection, and the method comprises the steps: preliminarily discriminating vehicle internal network data and vehicle-to-outside information exchange data through a built-in detection system of a vehicle, and generating a local abnormal event with confidence; then, the preliminary detection result is confirmed through an Internet of Vehicles regional cooperation mechanism, and a fine-grained space query and verification mechanism taking a vehicle captured image as a reference is introduced, so that accurate discovery and association of abnormal network events and physical world perception inconsistency are realized; and therefore, complex threats such as false information injection and man-in-the-middle attack can be efficiently identified and relieved.

The application provides a spatial query performance optimization method in a geographic information system, and belongs to the technical field of geographic information systems.The application adopts three-dimensional Hilbert space-time filling curve coding and memory level columnar storage format to maintain the locality of space-time data and reduce invalid memory loading, introduces a consistent hash and adaptive space grid dynamic partitioning load balancing strategy to migrate hotspot tiles to idle nodes, adaptively distributes query requests based on a deep Q network artificial intelligence space-time load routing decision model, and dynamically adjusts the strategy update mode through an adaptive exploration rate adjustment function, triggers a repartitioning process when the query response delay exceeds a threshold, and performs garbage collection on a low-frequency version chain, thereby solving the technical problem that the spatial query performance of the geographic information system rapidly decreases with the increase of the data scale in a high-concurrency streaming spatial data input scene.

The invention provides a high-performance geographic layer management method, system and device and a medium, and belongs to the technical field of geographic information systems. According to the method, a unified spatial query interface is established by constructing a dynamic and static combined hybrid spatial index system; on-demand data scheduling is realized by adopting a dynamic loading mechanism associated with a view; optimizing rendering resources through group-level state management and data batch processing; a GPU instantiation rendering technology is utilized to realize efficient drawing of massive elements; and visual processing of the spatial data is completed based on real-time aggregation analysis. According to the method, the problem of lagging of a traditional GIS system during massive element rendering and the problem of delay of dynamic data updating are effectively solved, smooth rendering and real-time interaction of million-level geographic elements are achieved, and the rendering performance and the resource utilization efficiency of the system are remarkably improved.

The invention discloses a compressed XML database type, system and method supporting efficient query, and relates to the technical field of XML databases, and the database type adopts a hierarchical compression storage architecture and a reverse search query architecture; in the storage stage, XML non-keyword information is coded through Huffman coding, recoverable ordered arrangement is carried out on the coded information through a tree structure, then transcoding is carried out, the information is stored in a disk in a binary form, and compared with a traditional XML database storage mode, at least 50% of storage space is saved. In the query stage, a reverse search mode is adopted, a corresponding Huffman code initial position is positioned through a keyword, then under the optimization effect of a reverse index, reverse search is performed to recover a complete XML structure, and the query complexity is reduced from traditional O (n) to O (1). According to the method, the storage efficiency and the query performance of the XML data are greatly improved, and the method is suitable for large-scale XML data management and application scenes.

The invention provides a point cloud three-dimensional implicit reconstruction method and device, equipment and a medium, and relates to the technical field of computers, and the method comprises the steps: carrying out the multi-scale feature extraction of an original point cloud, obtaining and carrying out the cross-scale dynamic fusion processing of a micro-scale feature, a mesoscale feature and a global feature, and obtaining a fusion feature field; a multi-scale symbolic distance function value of the spatial query point is predicted based on the fusion feature field, compensation processing is carried out in combination with a shape correction term, a final implicit field value is obtained, and the shape correction term is obtained by carrying out shape prior processing on the original point cloud; and performing gradient optimization and surface reconstruction processing according to the final implicit field value to obtain a three-dimensional grid model. According to the method, through multi-scale feature extraction, feature fusion and shape correction compensation processing, the precision and robustness of three-dimensional implicit reconstruction are improved, so that the reconstructed three-dimensional grid model can more accurately reflect the geometric and topological characteristics of the original point cloud.

The invention provides a reverse k nearest neighbor query method and device based on a Sketch graph, equipment and a medium, and the method comprises the steps: constructing a road network model based on a large-scale road network, and obtaining nodes in the road network model to construct a data point set; on the basis of the data point set, a multi-source Dijstra is adopted to construct a Sketch graph; connecting a query point to the Sketch graph; and searching all reverse k nearest neighbor data points of the query points in the Sketch graph to solve the problem of huge calculation waste caused by verification operation on a large number of redundant nodes when query parameters are relatively large or data points are sparse in spatial query.

The invention discloses a double-flow point cloud compression method and system based on a semantic scene graph, and relates to the field of point cloud compression, and the method comprises the steps: constructing a point cloud compression network comprising an encoder network and a decoder network: in a coding end network, carrying out the semantic label mapping of an input point cloud, and respectively constructing a scene graph and octree representation; semantic modulation parameters are generated based on the scene graph and coded to obtain semantic bit streams, octree representation obtains node occupancy probability through feature enhancement and attention probability prediction under the action of the semantic modulation parameters, geometric bit streams are generated through arithmetic coding, and the two bit streams serve as compressed data; in the decoder network, bit streams are decoded, an octree structure and scene graph information are reconstructed, node feature representation is recovered in combination with semantic modulation parameters, and the reconstructed octree structure is mapped back to a point cloud space through spatial query and indexing to reconstruct a point cloud. According to the method, the local geometric distortion problem of low-bit-rate octree point cloud compression is solved, the reconstruction quality is ensured, and the transmission bit rate is reduced.

The invention belongs to the technical field of tunnel engineering, and particularly relates to a tunnel blasting scheme design method and system based on a database technology. According to the scheme, a hybrid architecture historical blasting case database comprising structured data and spatial data is constructed, and a progressive retrieval engine and a scheme generation algorithm are combined; the innovation of tunnel blasting design from experience dependence to data driving is realized; according to the scheme, structural features such as blasting parameters and geologic features are deeply fused with spatial features, a proposed progressive retrieval engine is combined, the spatial query efficiency is effectively improved, meanwhile, the matching degree of a reference case and an actual scene is improved, and meanwhile, the matching efficiency of the reference case and the actual scene is improved. According to the scheme, a tunnel blasting scheme generation normal form integrating benchmark maintenance, parameter optimization and expert verification is provided, so that the accuracy of the generation scheme is guaranteed, and meanwhile, the generation scheme can better adapt to an actual scene.

The invention discloses a frontier landscape database construction method based on feature element recognition. The method comprises the steps of obtaining frontier landscape basic data based on frontier landscape elements; on the basis of research content and a framework construction technology, constructing a border landscape basic information database in combination with border landscape basic data; the border Xinjiang landscape basic information database comprises a border Xinjiang landscape style and feature element thematic database; the method comprises the following steps: obtaining the landscape style and feature elements of the Xinjiang cities and towns, and obtaining database hierarchical division based on the landscape style and feature elements of the Xinjiang cities and towns and landscape carrier types; and constructing a thematic database of the landscape styles and features of the frontier cities and towns based on hierarchical division of the database. The constructed database comprises related contents such as spatial and temporal distribution, historical evolution, ecological environment and social humanity data of all entity elements of the frontier cities and towns, the functions such as frontier cities and towns style and appearance data storage, data editing, map visualization and spatial query analysis are achieved, and theoretical thoughts and technical references are provided for related research and application.

The invention discloses an underground pipe network three-dimensional automatic modeling visualization method and system based on ShapeFile data, and relates to the cross technical field of geographic information systems and three-dimensional visualization, and the system comprises a data import module which is used for importing ShapeFile data including geometric information and attribute parameters of pipelines, inspection wells and ancillary facilities, and supports multi-database storage; the three-dimensional coordinate conversion module is used for performing three-dimensional coordinate conversion on the two-dimensional coordinates; the three-dimensional modeling module is used for generating a parameterized pipe network model, and the pipeline diameter is driven by an attribute field; and the three-dimensional visualization module is used for visualizing the three-dimensional model and realizing split-screen comparison of the two-dimensional map and the three-dimensional scene. According to the system, two-dimensional ShapeFile data can be automatically generated into three-dimensional coordinates through WGS84 coordinate conversion and elevation field analysis, and pipeline connection relation analysis is optimized, so that topology construction and space query efficiency is remarkably improved, and pipe network space situation awareness is more visual.

The invention discloses an inspection defect duplicate removal method based on target detection and space coordinate conversion, and relates to the field of unmanned aerial vehicle inspection and artificial intelligence. The method comprises the following steps: acquiring a detected object image, synchronous POS data and lens attitude data through an unmanned aerial vehicle, outputting defect information through a pre-trained target detection model, and mapping defect pixel coordinates into WGS-84 longitude and latitude as a unique space identifier in combination with camera parameters; a circular buffer area index of a dynamic space threshold R is constructed, duplicate removal is achieved through space query, category judgment and confidence coefficient comparison, and duplicate records are written into a redundant log table for model iterative optimization. The method solves the problems of repeated alarm, insufficient positioning precision and single de-duplication logic in the prior art, has the advantages of accurate de-duplication, high adaptability and high efficiency, realizes closed-loop optimization, and is suitable for unmanned aerial vehicle inspection of large infrastructures such as power lines and bridges.

The invention provides a data processing method and device, equipment, a readable storage medium and a program product, and the method comprises the steps: in the running process of a target program, pausing the running target program in response to an object graph obtaining instruction; querying object graph generation information of the target instance object belonging to the to-be-queried class from the heap storage space in a pause running stage of the target program; the heap storage space is used for storing object information of instance objects generated in the running process of the target program; generating an object graph of the target instance object according to the object graph generation information of the target instance object; the object graph is used for determining whether memory resource abnormal occupation exists in the running process of the target program. According to the method and the device, the memory information of the required instance object can be obtained according to the to-be-queried class, and the object graph of the required instance object is determined online, so that the data processing amount is reduced, the data processing efficiency is effectively improved, and whether memory leakage exists in a program or not can be quickly determined according to the object graph.

The application provides a task name query method and device, electronic equipment and medium, the method comprises the following steps: obtaining a to-be-queried instance ID and a project space corresponding to the to-be-queried instance ID in a MaxCompute computing platform; querying instance detail information corresponding to the to-be-queried instance ID by using the to-be-queried instance ID and the project space, and judging whether the instance detail information contains a scheduling node ID; if the instance detail information contains the scheduling node ID, extracting a task ID from the scheduling node ID, and querying a task name corresponding to the task ID in a DataWorks development platform. The application can use the to-be-queried instance ID and the corresponding project space to effectively locate the corresponding task ID and task name in the DataWorks platform, which can effectively avoid the manual inquiry mode in the related art, and thus can effectively improve the query positioning efficiency of abnormal instance tasks and the work efficiency of operation and maintenance personnel.

The present invention discloses a 3D tile data storage method and a map data query method, wherein the 3D tile data storage method includes the following steps: 1) establishing a LOD hierarchical pyramid-shaped hierarchical table and creating an LOD range index; 2) generating proxy points for three-dimensional objects, segmenting tiles according to a KD-tree structure to construct a three-dimensional KD-tree index tree; 3) storing the data of the KD-tree leaf nodes in GridFS of MongoDB multimodal storage, mapping the file path to a unique hash value, writing the value into the corresponding node according to the KD-tree node storage structure, and creating a geospatial index. The present invention creatively solves the difficulties in file system management caused by a large number of files. The hierarchical structure based on the file directory is difficult to support efficient spatial range retrieval. By combining the three-dimensional KD-tree index with the MongoDB geospatial index, the spatial query response time is reduced to milliseconds.

This invention provides a data spatial query method, apparatus, electronic device, and computer-readable storage medium. The data spatial query method provided by this invention includes: acquiring target business data; constructing a spatial field based on the latitude and longitude data of the target business data; importing the spatial field into a preset index; acquiring the latitude and longitude data of two diagonal vertices within a visualized map area; determining a data query range based on the latitude and longitude data of the two diagonal vertices; acquiring a geographic grid based on the data query range and the shrinkage ratio of the visualized map; and aggregating and statistically analyzing the target business data within the geographic grid area based on the spatial field to obtain query results. The data spatial query method provided by this invention can aggregate points on a large number of maps and respond promptly to the aggregation.

The invention belongs to the technical field of geographic information data query, and provides a cross-network geographic information security query method and device, equipment and a medium, and the method comprises the steps: obtaining a geographic spatial data query request of an extranet user; performing data verification on the geographic spatial data query request to obtain planar geometric data of a query target, the planar geometric data including a first coordinate system; sending the first coordinate system of the planar geometric data to an internal network and converting the first coordinate system to obtain a second coordinate system; executing spatial query on a target layer of the geographic spatial database according to the second coordinate system to obtain a first query result; and processing the first query result according to a preset desensitization rule to obtain a second query result, and returning the second query result to the extranet user. The cross-network geographic information query method has the beneficial effect that the cross-network geographic information query security and accuracy are improved.