23 results about "R-tree" patented technology

The invention discloses a surveying and mapping geographic information data management method and system based on cloud computing, and relates to the field of geographic information, and the method comprises the steps: constructing a semantic segmentation model based on a convolutional neural network Deep Lab, and carrying out the feature extraction and semantic annotation of a surveying and mapping geographic data set through the semantic segmentation model, and obtaining a geographic element set; performing spatial division and indexing on the geographic element set by adopting an R tree spatial indexing method to obtain a hierarchically organized geographic element tree; constructing a graph neural network model based on a graph convolutional network GCN, and performing topological relation modeling on the geographic element tree by using the graph neural network model to obtain a time-space attribute graph containing geographic semantics and topological relations; and constructing a space-time prediction sequence model based on the space-time diagram neural network STGCN, and performing evolution trend prediction on the space-time attribute diagram by adopting the space-time prediction sequence model. Aiming at the problem that dynamic prediction of geographic elements is difficult to realize in the prior art, the spatial-temporal evolution trend of the geographic elements is predicted, and dynamic prediction is realized.

The invention relates to the technical field of digital fusion, in particular to an electronic chart drawing method and system based on a data fusion technology, and the method comprises the steps: S10, building and dynamically updating a mixed index structure based on a preset electronic chart database and an incremental data packet collected in real time; s20, matching the same-name elements, fusing the identified space overlapping regions, and outputting a de-duplicated global sea chart data set; s30, dividing a plurality of sub-regions, constructing a quadtree-R tree index, and outputting a quadtree-R tree double-layer mixed index structure; s40, converting the screen coordinates into geographic coordinates, screening visible elements, and outputting a visible region element set; and S50, based on the visible area element set and a preset style rule, allocating a rendering task, optimizing and matching a GPU instruction set, and outputting a real-time sea chart picture with a preset frame rate. According to the method, the real-time processing efficiency and the visualization fluency of the electronic chart are remarkably improved, and the user interaction experience is optimized.

The invention provides a layout file geometric data processing method, a computer device and a storage medium. The method comprises the steps that a layout file of a three-dimensional chip is obtained, polygonal entities and layer information are extracted, the polygonal entities are distributed to corresponding layer containers, and an independent R tree index is created for each layer; performing connectivity analysis on the polygonal entity, and returning a connected component set and performance analysis statistical information; when an independent R-tree index is created for each layer, data of all polygonal entities of a single layer is obtained, a minimum boundary rectangle is generated for each polygonal entity, R-tree indexes are constructed for different layers in parallel by adopting a plurality of threads, whether the number of node entries of the R-tree indexes exceeds a splitting threshold value or not is judged, and if yes, splitting processing is carried out on nodes; and verifying the consistency of the created R tree index and the original data. The computer device and the storage medium can realize the method. The geometric data processing efficiency of the layout file can be improved.

The invention relates to the technical field of data processing, and discloses a geographic space object indexing method and device, a storage medium and a computer device.The method comprises the steps that a geographic space object corresponding to a minimum enclosing rectangle located in a single initial regional grid is stored in a regional exclusive R tree corresponding to the initial regional grid, and the geographic space object corresponding to the minimum enclosing rectangle located in the single initial regional grid is obtained; storing the geographic space object crossing the initial region grid in a region sharing R tree; when any one of the initial regional grids is in a dense state, re-dividing the initial regional grids until the divided regional grids are in a sparse state; and in the current latest geographic space grid chart, determining a target area grid according to an index box selection area corresponding to the geographic space object index instruction, and querying and returning a target geographic space object corresponding to the index box selection area by using the area sharing R tree and the current latest area exclusive R tree corresponding to the target area grid in parallel. By reducing the density of the grid and then storing the object by using the R tree, the subsequent indexing efficiency can be improved.

The invention discloses a curved surface deviation detection method based on virtual-real superposition and multi-user cooperation, and relates to the technical field of deviation detection. Comprising the steps of calculating point cloud data to obtain a curvature feature matrix; the reverse model data and the real object point cloud data are aligned, curved surface deviation detection operation is executed, a deviation field is coded, and preliminary visual display is carried out in a VR / AR environment; a plurality of users carry out collaborative recheck based on the deviation field, dynamic visual projection is carried out on annotation space coordinates according to curved surface curvature features, meanwhile, the annotation space coordinates, user gesture tracks and text keywords are jointly coded, a two-dimensional R tree annotation index is established, and annotation data and a deviation field result are spatially correlated; and dynamically updating the visual content and correcting the deviation according to the spatial association. According to the method, the problems of inaccurate alignment, low rechecking efficiency, difficulty in coverage of a blind area and the like in curved surface deviation detection are effectively solved, and the accuracy, interpretability and team cooperation efficiency of a detection result are improved.

The application relates to the field of privacy protection query schemes, in particular to an indoor multi-user personalized spatial keyword privacy query method based on a GIS enhanced index tree. In view of the demand of multi-user spatial keyword privacy query in an indoor environment, a GISEnhancedIndexTree index structure is constructed by fusing Hilbert coding, an R tree, an encrypted Bloom filter and an EASPE encrypted vector, and spatial and text information of indoor objects are encrypted and indexed. During query, a user request is encrypted and processed into a trapdoor, a server performs spatial, floor and keyword pre-filtering in the index tree according to the trapdoor, calculates the similarity of encrypted vectors by means of EASPE, and returns the encrypted result to the user after threshold filtering, score aggregation and sorting. Meanwhile, a comprehensive position vector construction method and a privacy protection coordinate conversion method based on a local coordinate system are designed to guarantee the privacy safety of the whole data flow. The method can effectively protect the privacy of users and improve the efficiency and accuracy of indoor multi-user personalized spatial keyword query.

The invention provides a sub-graph matching method based on decomposition query, which relates to the technical field of data processing, and comprises the following steps: decomposing a query graph and a data graph into a plurality of query sub-graphs and data sub-graphs; establishing a filtering strategy based on the feature vectors, filtering the data sub-graphs based on the filtering strategy, and obtaining a first candidate data sub-graph set which comprises a plurality of candidate data sub-graphs; generating an R tree based on the candidate data sub-graphs, and excluding unmatched candidate data sub-graphs in the first candidate data sub-graph set to obtain a candidate result set; and calculating a matching sequence based on the candidate result set, obtaining a preliminary matching result of the query sub-graph, combining the preliminary matching result into a candidate sub-graph, and taking the verified matching sub-graph as a final sub-graph matching result through refinement and verification. A data graph and a query graph are decomposed into a plurality of sub-graphs for efficient query of vertexes in the graphs. The generated candidate vertex set can provide more accurate information for the sorting method.

The application discloses a kind of based on GiST spatial index multi-resolution fragmentation DEM database construction method, comprising: S1, with the resolution of fragmentation DEM image tile as hierarchical division standard;S2, existing DEM image tile is hierarchically divided according to S1 hierarchical division standard, to minimum outer rectangle as unit independent storage;S3, based on DEM image tile, the hierarchical structure rule of R tree is used to establish parent-child node relationship, and the initial R tree multi-resolution skeleton is constructed;S4, on the basis of initial R tree multi-resolution skeleton, uniform different hierarchical spatial relationship description rule is formulated, and according to the rule, the spatial correlation between DEM image tile is described, and the preliminary establishment of multi-resolution DEM database based on GiST spatial index is completed;S5, the DEM image tile to be stored is stored into database, and the database is improved.The application improves the performance of DEM data storage.

The invention discloses an encrypted data query method, and relates to the technical field of data encryption. Comprising the steps that a data owner generates a secret key containing a pseudo-random seed and sends the secret key to a data user; the data owner constructs a common R-tree index, converts the common R-tree index into a safe R-tree index by using an index construction algorithm, and sends the safe R-tree index to the cloud platform; the data user obtains a search token according to the received secret key and the data query range needing to be queried, and sends the search token to the cloud platform; the cloud platform searches on the security R tree index according to the search token, and sends a search result to the data user; and the data user decrypts the search result to obtain plaintext data. According to the method, privacy protection and security of multi-dimensional data in the cloud computing environment are improved, so that a data owner and a user can safely store, retrieve and process sensitive data on a cloud platform, and data privacy and security challenges in the cloud computing environment can be solved.

The application relates to the technical field of property management and discloses a data task coordination management method based on a multistage organization framework, which comprises the following steps: S1, synchronizing an organization framework through an enterprise WeChat API to generate cross-system identity mapping; an interval nesting model is constructed, and interval information of all nodes is stored by using an R tree space index; S2, receiving an index abnormal event, automatically generating a task object, and associating all contents of the event with the task object as a context snapshot; S3, acquiring all subordinate departments which are completely contained in an interval and meet a depth condition by querying the R tree to generate a permission matrix of a current user; S4, managing a task life cycle by using a finite state machine, and synchronizing to a PC terminal board in real time through a WebSocket; and S5, after the task is completed, automatically acquiring the latest index value from the board, comparing the latest index value with a snapshot, and generating an effect improvement report. According to the application, offline communication cost is reduced, task transmission time is greatly shortened, system docking cost is reduced, the whole life cycle of a task is covered, and coordination efficiency is improved.

This application discloses a method and apparatus for constructing a ciphertext spatial index based on hierarchical order-preserving encryption, relating to the field of ciphertext spatial index construction. The method includes: embedding a security policy into the nodes of an R+ tree index to obtain an AR+ tree index; generating multi-level keys based on the AR+ tree index; using the multi-level keys to perform hierarchical order-preserving encryption on the plaintext index data, mapping the plaintext index data to ciphertext intervals; parsing the query statement to obtain a query rectangle and user access permissions; performing hierarchical order-preserving encryption on the query rectangle based on the AR+ tree index and multi-level keys, and finding the intersection with the minimum bounding rectangle of each layer's nodes; verifying user access permissions and filtering out all data IDs that meet the conditions; determining the original data ciphertext based on the filtered data IDs; and decrypting the original data ciphertext using the encryption algorithm used when encrypting the original data to obtain the plaintext data. This application enables fast retrieval and querying of spatial indexes in ciphertext mode.

The invention relates to the field of privacy protection query schemes, in particular to an indoor multi-user personalized space keyword privacy query method based on a GIS enhanced index tree. According to the requirements of multiple users for space keyword privacy query in an indoor environment, encryption indexing is carried out on space and text information of an indoor object by constructing a GISEnhancedIndexTree index structure fusing a Hilbert code, an R tree, a densely distributed filter and an EASPE encryption vector. In the query process, a user request is encrypted into a trap door, and the server sequentially executes space, floor and keyword pre-filtering, encryption vector similarity calculation by means of EASPE, threshold filtering, score aggregation and sorting in the index tree and then returns an encryption result to the user. And meanwhile, a comprehensive position vector construction and local coordinate system-based privacy protection coordinate conversion method is designed, so that the privacy security of the whole flow of data is ensured. According to the method, the efficiency and accuracy of indoor multi-user personalized spatial keyword query are improved while the user privacy is effectively protected.

The invention discloses an efficient retrieval method for large-scale spatial data of aviation geographic information. The efficient retrieval method comprises the following steps: compressing each element in the aviation geographic spatial data by adopting a vector quantization technology; an R tree is adopted as a spatial data index structure, and an index is established through a minimum boundary rectangle MBR surrounding a spatial object; and carrying out parallel retrieval on the geospatial data. According to the method, the data storage space requirement is reduced, the geographic space data retrieval efficiency is effectively improved, and the data retrieval time of a large-scale geographic scene is greatly saved.

The present invention provides a BIM efficient three-dimensional collision detection method based on a distributed framework, including an index establishment process and a collision query process, wherein the index establishment process includes: S1, reading a BIM original data set and storing it in HBase; S2, dividing a grid index according to grid parameters to obtain multiple grids; S3, placing each BIM entity in a grid; S4, establishing a 3D R-tree index for each grid; the collision query process includes the following steps: A1, obtaining a target query range and a target grid parameter and obtaining a first result set A2, searching for a 3D R-tree of each grid ID in two first result sets and taking out the BIM original data set stored in the 3D R-tree to obtain a second result set; A3, filtering BIM entities that do not match the target query range; A4, extracting a BIM original data set with an intersection between two BIM entities to form a collision pair and adding it to a third result set. The beneficial effect is that the present invention can improve the index query rate, reduce the index construction time, and improve the computing efficiency.

The application discloses a kind of R+tree dynamic publishing and subscribing method based on lazy update strategy, comprising: constructing subscription condition list and R+tree;Receive subscription condition;The unique identification of subscription condition is generated, and the update field, boundary field and pointer field of subscription condition are determined;Judge whether the unique representation is contained in the initialized subscription condition list, if yes, delete subscription condition, and receive next subscription condition;If not, determine the updated subscription list and the updated R+tree, in response to the publishing request of target event, receive the subscription relationship of target event;Based on subscription relationship, search in the updated subscription list and the updated R+tree, determine final target subscription condition, and publish the final event corresponding to final target subscription condition.The application can improve the efficiency of traffic event matching and node subscription management.

The invention relates to the field of information retrieval, in particular to an astronomical data index construction method and device based on an R tree and a program product. The method for constructing the astronomical data index based on the R tree comprises the steps that an astronomical star catalogue is obtained, the astronomical star catalogue comprises a plurality of data lines, and fields of the astronomical star catalogue comprise spatial positions; dividing the celestial coordinate system into a plurality of pixel blocks with different spatial codes based on a predetermined sky area division protocol, mapping the data rows to the corresponding pixel blocks based on the spatial positions of the data rows to obtain the spatial codes corresponding to the data rows, and dividing the data rows with the same spatial codes in the astronomical star catalogue into one data block to obtain a plurality of data blocks; constructing an R tree index for each data block in the plurality of data blocks based on the spatial position of the data row to obtain a block index of the data block; and performing one-to-one correspondence on each spatial code and the block index to obtain an astronomical data index. According to the method, the astronomical data retrieval efficiency is improved.

The invention discloses a query method and system based on a trajectory index structure, and the method comprises the steps: S1, constructing a probabilistic maneuvering R tree: S11, receiving a to-be-inserted dynamic object, and modeling the motion uncertainty of the to-be-inserted dynamic object into a PMBR which is composed of a plurality of maneuvering unit groups; s12, inserting an object into a leaf node which enables the internal motion confusion degree of the node to be increased to the minimum, if the inserted node overflows, executing a node splitting method based on a future interaction score, and selecting a division scheme which enables the interaction possibility of the two split nodes in a future time window to be minimum; s13, inserting an object at a leaf node; s14, splitting the nodes; and S15, updating the PMBR of the ancestor node upwards. And S2, receiving a query request, and returning a query result. According to the method, the pruning efficiency of predictive query is remarkably improved. A flexible motion model is applied, and a pruning strategy and accurate calculation are combined, so that the query performance is greatly improved while the accuracy is ensured.

A mass storage system for ship historical trajectory data designed by the present invention includes a trajectory storage module, a local index module, and a data maintenance module. According to the characteristics of the ship trajectory data structure, the orderly organization and storage of ship historical trajectory data are completed. Combining B+ trees, R trees, and hash tables according to common query types, a local index structure supporting multiple query types is constructed. At the same time, the local index and the corresponding data storage partition are maintained in the same node, reducing communication overhead. Based on the constructed storage and index structure, a query method is implemented based on a parallel query method to optimize the queries based on time, space, and ship identification. Since the model of storing the same ship data in the same node effectively reduces the communication overhead between nodes, and the row key and index structure ensure the rapid search for these three types of keywords, the query latency can be effectively reduced.

The application discloses a chip layout link tracking method based on a scan line and an R tree, and belongs to the technical field of calculation, estimation or counting. The method comprises the following steps: analyzing an input layout file, constructing an event queue for a read graph, storing events into an R tree and traversing the R tree by using a scan line, and outputting a required graph set. The above method can effectively realize efficient processing of large-scale layout data and rapid extraction of multilayer links.

The invention relates to the technical field of urban service facility site selection, in particular to a multi-target joint site selection method for urban convenience service facilities with a hierarchical structure, which comprises the following steps: acquiring popularity of each candidate address, a target user set, a travel track set corresponding to the target user set, maximum service capacity and construction cost, and generating each leaf node; clustering all leaf nodes in a multi-level manner by adopting an R + tree structure construction and pruning strategy and taking candidate address popularity corresponding to each leaf node as an index to obtain all generated R + trees; marking each level of the aligned R + tree, and generating an index layer Hash mapping set; and selecting # imgabs0 service centers, # imgabs1 # service centers and # imgabs2 # service centers on the basis of the index layer hash mapping set by adopting a heuristic local greedy strategy under the conditions that the total construction cost of all the selected service centers is smaller than or equal to a total cost threshold value and the popularity sum of all the selected service centers is the highest. According to the invention, the multi-target joint site selection efficiency and effect are improved.

The invention discloses a coarse and fine granularity combined three-dimensional building model organization method and device, electronic equipment and a storage medium. According to the method, an R tree is used for organizing data on the aspect of coarse granularity, then an octree is used for organizing the data on the aspect of fine granularity, the depth of the tree is reduced, the overall structure is more biased to a balance tree, the data organization construction speed is increased, and support is provided for data organization of a three-dimensional data model. Experiments show that the method has more superiority than an R tree and an octree in the aspects of creating speed and inserting speed, and is also faster than the octree in the aspect of retrieval speed, especially retrieval biased to a small area. The method can meet efficient organization and management of the three-dimensional building model, especially in applications needing frequent construction and insertion of three-dimensional building model data.

The application discloses a chip layout link tracking method based on a scan line and an R tree, and belongs to the technical field of calculation, estimation or counting. The method comprises the following steps: analyzing an input layout file, constructing an event queue for a read graph, storing events into an R tree and traversing the R tree by using a scan line, and outputting a required graph set. The above method can effectively realize efficient processing of large-scale layout data and rapid extraction of multilayer links.

The invention discloses a GPU spatial query optimization method based on nearest neighbor query, and the method comprises the steps: carrying out the clustering analysis of boundary rectangles of spatial objects based on an improved density clustering algorithm, sorting the central points of all types of sets after clustering and the spatial objects in each type of sets, and finally constructing a clustering sorting R tree, therefore, a large amount of power grid spatial data can be quickly and effectively retrieved, the spatial data processing efficiency is optimized, and support is provided for constructing a heterogeneous cloud platform oriented to non-structural spatial data.