145 results about "Geographic entity" patented technology

The invention belongs to the technical field of natural language processing and geographic information systems, and particularly relates to a region address standardization method based on knowledge graph enhanced retrieval. Cleaning and preprocessing the original address text input by the user; utilizing a fine-tuned large language model to identify a geographic entity and performing standardized expansion on variant expression to generate a query candidate set; entity linking and context retrieval are carried out based on the knowledge graph, and attributes, hierarchy and spatial topology information of associated entities are obtained; in combination with the original input and the map context, an enhanced retrieval query text is generated through large language model reconstruction; vectorized semantic retrieval is carried out through the fine-tuned embedding model, and a preliminary candidate address set is obtained; carrying out multi-dimensional refined sorting by adopting a resorting model; and generating a structured standard address by using a large language model, and outputting the structured standard address after multi-level verification. According to the method, the problems of ambiguity resolution, alias recognition and context understanding in address processing are solved, and the accuracy and robustness of address standardization are improved.

The invention belongs to the technical field of surveying and mapping and geographic information processing, and discloses a geographic entity intelligent identification and reconstruction system based on multi-source surveying and mapping data. The system is composed of a multi-source data acquisition and preprocessing module, a cross-modal feature coding and fusion module, a structural atlas construction and spatial logical reasoning module, a deformable neural modeling module and a physical prior guided collaborative prediction and closed-loop optimization module. According to the method, a cross-modal feature coding and fusion module is arranged, and a modal attention mechanism is introduced to dynamically weight multi-source data, so that heterogeneous information such as a laser point cloud, an inclined image and a multispectral image is fused into a unified coding vector in a high-dimensional space; compared with feature extraction performed by using a static deep network in a comparison file, the method of the invention adopts a minimum residual function to perform modal weight training, has an adaptive feature integration capability, and effectively improves the accuracy of geographic entity recognition and the robustness of boundary segmentation in different scenes.

The invention relates to the technical field of image processing, and discloses a house quality detection method and system based on a live-action three-dimensional model. The method comprises the following steps: converting an OSGB format live-action three-dimensional building model into a body coordinate system and carrying out quality evaluation, carrying out semantic segmentation on a standardized model to obtain a component geographic entity set, establishing an independent local coordinate system of each component to form a single three-dimensional model set, generating a multi-view projection feature image set based on a normal vector distribution planning view angle, and carrying out multi-view projection on the single three-dimensional model set. And detecting defects by adopting a 3D-YOLO-BuildingDefect algorithm, and carrying out inverse transformation to obtain three-dimensional space defect distribution and a quality grade evaluation result. The technical problems that a traditional two-dimensional detection method is insufficient in spatial positioning precision, incomplete in detection coverage rate and insufficient in geometric information utilization are solved, and the spatial positioning accuracy of house quality detection and the comprehensiveness of defect recognition are improved.

The invention discloses a three-dimensional semantic knowledge graph construction method for geographic entity space-time relationship, and relates to the technical field of knowledge graph construction, comprising: acquiring a unified reference geographic entity stream, selecting a mutually covered geographic entity pair set based on XY axis projection overlapping detection, and reading a sensor precision file; determining an up-and-down orientation relation based on a bounding box vertical extreme value; querying a preset layer thickness mapping table to determine a coarse-grained sectioning layer thickness, calculating coarse-grained vertical coverage in the Z-axis direction, defining a crossing depth interval as a coarse-grained vertical index, and comparing the coarse-grained vertical index with a first threshold library to generate a preliminary up-down relationship state tag; and for the ambiguous or envelope state entity pair, determining a local depth range based on a coarse-grained vertical index, performing heavy new sampling by using a fixed fine-grained sectioning layer, generating a second threshold library for rejudgment by revising a threshold, and forming a revised map version. The vertical semantic ambiguity can be eliminated, and the accuracy of judging the upper and lower relationships of the geographic entities is improved.

The invention relates to the technical field of geographic information systems, in particular to a GIS buffer zone parameter inference method based on deep learning, and the method comprises the following steps: obtaining a natural language instruction input by a user; analyzing the natural language instruction to extract a geographic entity keyword and a fuzzy description word; based on the fuzzy description word, determining an initial distance parameter through a pre-trained language-space mapping model; querying a spatial database based on the geographic entity keyword to obtain geographic entity attributes; according to the geographic entity attribute, correcting the initial distance parameter to obtain a corrected distance parameter; a field programmable gate array (FPGA) is used for carrying out parallel calculation on the spatial relation matrix to generate an optimized buffer area; and outputting the optimized buffer area. According to the method, the FPGA is introduced to carry out parallel calculation of the spatial relation matrix, so that the data processing speed and the energy efficiency ratio are remarkably improved, and the real-time generation of the buffer area is realized.

The invention discloses a real-scene three-dimensional system geographic entity space-time coding method. According to the method, the dynamic sensing capability of the geographic entity state is remarkably improved through an evolution prediction mechanism. Traditional coding mostly focuses on current state records, but the method depends on a state transition probability model of time decay weighting, can accurately capture recent change trends of entities, generate evolution prediction codes and dynamically bind the evolution prediction codes with space codes and time codes, so that the coding can not only reflect current positions, time and attributes of the entities, but also can reflect current state records of the entities. And the state trend of 1-3 months in the future can be pre-expressed. According to the method, the subsequent stage of a construction road can be pre-judged in advance, an emergency department can quickly recognize potential risk entities, the problem that geographic information lags behind actual change is effectively solved, more prospective data support is provided for collaborative decision making of multiple departments, the suitability and long-term reliability of coding in multiple scenes are enhanced through full-process closed-loop design, and the method is suitable for popularization and application. And a stable basic support is provided for efficient application of live-action three-dimensional geographic information.

The invention provides a three-dimensional geographic entity space-time identification coding method based on a Beidou grid code, and belongs to the field of live-action three-dimensional, and the method employs a classification identification + space identification + time identification structure, and rapidly calculates an outsourcing 3D convex hull of a three-dimensional geographic entity through KD tree pruning and principal component analysis. The method comprises the following steps of: determining a subdivision hierarchy of a maximum inner packet grid by using neighborhood seed growth, calculating an entity space identifier which takes a Beidou three-dimensional grid position code as description by using a six-point method, further calculating an entity time identifier in a form of geographic entity ID + timestamp, realizing accurate identification of a geographic entity three-dimensional space position and time information, and realizing accurate identification of the geographic entity three-dimensional space position and time information. The problems that traditional geographic entity coding is insufficient in identification precision in three-dimensional space and time dimension, data integration is difficult and the like are solved, and the method has extremely high application value in the fields of live-action three dimensions, smart cities, low-altitude economy and the like.

The invention discloses a multi-task learning method and system based on knowledge enhancement, and the system comprises a basic coding module which is used for coding traffic event text information into text coding representation; the knowledge graph construction module is used for constructing a traffic field knowledge graph; the knowledge enhancement module is used for identifying the geographic entities in the text coding representation, linking the geographic entities to the traffic domain knowledge graph, and deeply fusing the geographic knowledge of the screened knowledge base entities in the traffic domain knowledge graph with the text coding representation; the event extraction module is used for extracting related elements in the text coding representation according to the text coding representation after deep fusion, and preliminarily constructing an event framework; and the multi-task learning module is used for coordinating combined learning and reasoning of entity identification, relation extraction, event type classification and knowledge fusion related tasks, identifying and extracting traffic event text information to be processed, and outputting a final prediction result. According to the method, the geographic entity in the text and the geographic knowledge in the knowledge graph are effectively linked and fused, information sharing and complementary enhancement can be realized, and the recognition accuracy and robustness of the model are improved.

The invention provides a multi-level geographic entity data consistency determination method and device, equipment and a storage medium, and relates to the technical field of surveying and mapping geographic information. The method comprises the steps of performing fusion processing on geographic entity data of different spatial scale hierarchies to form a unified database; based on geometric, semantic and attribute features, a differentiation matching model is adopted to carry out automatic identity determination on point-shaped, linear and planar entities of different hierarchies, and comprehensive judgment is carried out by utilizing multiple geometric quantities such as distance, buffer area overlapping proportion, area overlapping degree, curvature, trend and the like; and performing unified coding and association relationship construction on the entities according to an affirmation result. According to the method, the problems that the same entity in the multi-level geographic entity data is inconsistent in affirmation and non-uniform in coding are solved, automatic and high-efficiency consistency affirmation and integrated management are realized, and the data processing accuracy and efficiency are remarkably improved.

The invention discloses a pipeline geographic entity conversion production method, system, equipment and medium, and the method comprises the steps: S1, designing a pipeline geographic entity model which is used for stipulating a unified format of a converted pipeline geographic entity; s2, the comprehensive pipeline data are expressed as primitives, the comprehensive pipeline primitives comprise pipe point primitives and pipeline primitives, and the pipe point primitives are divided into entity primitives and drawing primitives; primitives of the integrated pipeline data are coded into primitive codes for associating the integrated pipeline primitives with pipeline geographic entities; s3, traversing the pipe point primitives, judging whether the pipe point primitives are entity primitives or not, if yes, generating pipe point entities based on the entity primitives, and if not, not processing in the step and waiting for participating in pipeline entity conversion in the step S4; and S4, traversing the pipeline primitives, and performing pipeline entity conversion. According to the invention, automatic upgrade conversion from the integrated pipeline data to the pipeline geographic entity data is realized.

The embodiment of the invention discloses a virtual area model processing method and a related device, which can be applied to scenes such as the map field, the cloud technology, artificial intelligence, intelligent traffic, auxiliary driving, digital human, virtual human, games, virtual reality, augmented reality and the like. According to the method, the virtual region is constructed by the region image used for describing the geographic entity region, so that the problem of data misalignment is avoided, the accuracy of subsequently constructing the virtual region model is improved, the complexity of the construction process is reduced, the method is not limited by map vector data, and the application range is expanded. In addition, regional images are identified through multiple image identification models, and semantic features describing all the sub-regions are obtained. And performing three-dimensional reconstruction according to the multiple semantic features to obtain a virtual region model for the geographic entity region. Therefore, three-dimensional reconstruction is carried out based on multiple rich semantic features, and the accuracy of the obtained virtual region model is higher.

The application discloses a low-efficiency land dynamic monitoring management method based on real three-dimensional geographical entities, relates to the technical field of natural resource informatization management, and comprises the following steps: constructing a terrain mutation sensitivity atlas and a vertical risk guide grid, generating a weighted initial value field under the joint driving of an elevation gradient, a reflection intensity and an echo confidence, and forming vertical prior information of geographical entities; based on the vertical prior information of the geographical entities, performing spatiotemporal consistency forced registration, performing local elastic calibration on oblique photography images and laser point cloud data through a multi-scale rigid-flexible mixed constraint mechanism, and generating a vertical error field. Through the construction of the sensitivity atlas, the execution of rigid-flexible registration, the introduction of semantic reconstruction, the implementation of uncertainty propagation and dynamic resampling regulation and control, the vertical error closed-loop correction of the three-dimensional model under complex topography is realized, the accuracy and stability of low-efficiency land identification are improved, and high-credibility technical support is provided for urban space analysis and land decision-making.

The invention belongs to the technical field of natural language processing, and particularly discloses a method for constructing a geographic knowledge graph alignment model, which comprises the following steps of: constructing a geographic knowledge graph structure containing multi-dimensional spatial information; creating a corresponding reverse link for the relation link between each geographic entity by using a reverse link generation strategy; distributing corresponding weights to different neighbor entities of each geographic entity by using a spatial perception attention mechanism, and calculating an output feature of each geographic entity by combining an orthogonal transformation matrix of the relationship and the spatial distance; and generating a negative sample through the adversarial network, training a pre-constructed deep learning network by using the negative sample, performing error calculation by using a combination of vector loss and geographic loss as total loss in the training process, and updating a corresponding weight parameter according to an error result until network convergence reaches an expected target, thereby completing training. According to the method and the device, the accuracy of geographic entity alignment in the geographic knowledge graph can be improved.

The application belongs to the technical field of data processing, and discloses a geographic information text intelligent extraction method based on knowledge perception; comprising: constructing a geographic knowledge ontology library, and constructing a corresponding semantic relationship network based on the same; obtaining text geographic entities and text semantic relationships corresponding to input geographic information text; constructing a corresponding initial tree based on the obtained text geographic entities and text semantic relationships, and combining a semantic relationship network; performing knowledge perception and semantic understanding on the corresponding initial tree based on the geographic knowledge ontology library, and obtaining a corresponding semantic tree; performing information extraction based on the obtained semantic tree, and obtaining required geographic information; the application realizes in-depth understanding and intelligent extraction of geographic information text by constructing a geographic knowledge ontology library and a semantic relationship network, and improves the accuracy and efficiency of geographic information extraction.

The present application relates to the technical field of geographic information display, in particular to a geographic entity information display method based on real scene three-dimensional modeling, comprising: acquiring multi-angle remote sensing images of the geographic entity region, performing target detection on the multi-angle remote sensing images to obtain each geographic entity type in the multi-angle remote sensing images; matching the geographic entity type with a preset geographic knowledge graph to obtain geographic information corresponding to the geographic entity type. Through processing of the multi-angle remote sensing images, the present application can effectively identify geographic entities, and extract more accurate geographic information according to different perspectives. Through the process, the accuracy of geographic entity classification and identification can be improved, and the geographic entity type is matched with the geographic knowledge graph, so that each geographic entity not only has a description of the physical space position, but also can be combined with rich semantic information.

This invention relates to a method and system for improving the quality and efficiency of map element production, comprising the following steps: Step 1: Providing a configuration management database, which is used to manage and maintain a geographic entity document library. Existing paper or electronic map element production standard documents are disassembled, index rules are established, and stored in the configuration management database; Step 2: Establishing basic files for data production personnel, connecting to the personnel system database, and automatically matching the work experience of production personnel. This invention, through the interaction between data production personnel and the system, integrates rich map data production cases with traditional production standard documents, effectively improving the skill proficiency of production personnel. Furthermore, by combining big data analysis, it accurately targets production bottlenecks and problematic production personnel, forming bottleneck solutions and pushing them to relevant data production personnel, effectively improving the quality and production efficiency of map data products.

The invention discloses a geographic entity derived land use sea classification method and system. The method comprises the following steps: obtaining geographic entity data and POI data; according to a preset grading standard, performing multi-level classification on the geographic entity data and the POI data to obtain multi-level geographic entity attributes and multi-level POI attributes; obtaining a pre-trained cascade derivation model; the cascade derivation model is based on the multi-level geographic entity attributes and the multi-level POI attributes of the training samples, and land use sea attributes of all levels are obtained step by step according to the grading standard; inputting the multi-level geographic entity attributes and the multi-level POI attributes into a cascade derivation model to obtain multi-level land and sea use attributes; and according to the multi-level land use sea attributes, obtaining land use sea classification corresponding to the geographic entity. By adopting the embodiment of the invention, the geographic entity can be automatically derived into the land-use-sea classification in combination with the interest point data, and the automation degree of land class conversion is improved.

The invention relates to the technical field of green logistics and traffic management, and discloses a material green transportation path optimization method considering a carbon emission factor, and the method comprises the steps: dividing a geographic region into a plurality of environment influence subregions according to a geographic entity layer and environment sensitivity information, establishing a dynamic environment influence factor model for each partition by combining real-time meteorological data; constructing an instantaneous carbon emission model combined with the driving behavior portrait for the vehicle; distributing a partition carbon budget for the vehicle, and establishing a carbon budget dynamic exchange rate based on the environmental impact factor; constructing a multi-objective optimization model taking the transportation cost, the transportation time and the total environmental influence calculated by weighting the instantaneous carbon emission and the environmental influence factors as objectives to generate an initial transportation path; according to the path scheme, triggering inter-regional carbon budget transaction or cross-regional carbon budget transaction based on a dynamic exchange rate so as to adjust budget held by the vehicle; and based on the adjusted budget, iteratively updating the transportation path until the system state converges.

This application belongs to the field of digital twin basic data management technology. This application provides an automated method and apparatus for generating spatial identity codes for basic geographic entities. The embodiments of this disclosure acquire the geometric and classification information of basic geographic entities under a unified spatiotemporal reference, automatically calculate the minimum bounding rectangle / minimum outer cube, adaptively select the minimum grid level that can contain the geometric range, and generate two-dimensional or three-dimensional location codes level by level according to the BeiDou grid location code rules. These are combined with classification codes and sequence codes to form a standard field; then, a proprietary identification field is formed by combining this field with root identifier codes and special codes, and extended fields are added as needed to achieve interaction with external codes. This can realize the automated generation, verification, parsing, and traceability of spatial identity codes in scenarios such as provincial, municipal, and county collaborative production updates, two-dimensional / three-dimensional integrated database construction, semantic association, and service publishing, providing unified support for the data organization and management of basic geographic entities and cross-industry interconnection.

A spatial decision-making suggestion generation method and system based on LLM and a geographic knowledge base, relating to the field of data processing technology, is disclosed. This method first establishes a knowledge base containing spatial geometric data of geographic entities. When a user's natural language decision query is received, a large language model is used for semantic parsing to extract the decision objective, spatial entities, and constraints. The system retrieves candidate knowledge from the knowledge base through semantic similarity calculation and evaluates the spatial compliance confidence level of each candidate based on the spatial geometric data and constraints. Subsequently, the candidate knowledge is hierarchically labeled according to confidence level to construct structured text, which is then injected into the large language model through a preset template. Finally, the system generates a spatial decision report based on the injected structured information. Implementing the technical solution provided in this application can improve the accuracy of spatial decision-making suggestions.

The invention provides a data updating method and device for digital twin entities, and relates to the technical field of digital twin geographic information.The method includes the steps that the observation capacity satisfaction degree of a sensing node is calculated, a target node is determined, mapping between the target node and the geographic entity is established, and first entity data of the geographic entity is obtained; second entity data of the digital twin entity corresponding to the geographic entity is then updated based on the first entity data. According to the digital twin entity-oriented data updating method provided by the invention, geographic entity data can be comprehensively, accurately and timely acquired, and meanwhile, aiming at data perception of a specific entity, the traversal quantity of a leading source is greatly reduced, the entity data acquisition efficiency is improved, and accurate and timely updating of the digital twin entity data is realized.

This invention relates to a method and system for constructing geographic entities and generating relationships, specifically including: identifying target vector layers from multiple sources, and extracting layer names, attribute field names, and their corresponding attribute values ​​from the target vector layers; performing multi-level filtering and comprehensive scoring based on layer names to determine the standard layer category for optimal alignment of layer names; mapping the attribute field names of the target vector layers to target standard fields using the standard layer category as a reference, and converting the attribute values ​​corresponding to the attribute field names into standard codes to achieve attribute standardization; acquiring the geometric data of the target vector layers, generating target vector entities based on the geometric data, and binding the corresponding standard attributes to the target vector entities; establishing topological relationships, hierarchical relationships, and cross-source entity referencing relationships between entities based on spatial topology analysis and semantic association analysis, thereby forming a structured geographic relationship network.

The application provides a method and device for modeling a geographical entity conversion relationship, electronic equipment, a storage medium and a computer program product. According to an embodiment of the application, a plurality of form nodes of a geographical entity and attribute values of each form node are established, including two-dimensional data expression and three-dimensional data expression corresponding to each form node, a mapping relationship between a geographical information element and the geographical entity is configured, spatial entity relationships of one or more geographical entities in converted target data are calculated, unique entity codes of the one or more geographical entities are obtained based on the spatial entity relationships, and the unique entity codes of the one or more geographical entities are stored in preset fields of a two-dimensional data expression set and a three-dimensional data expression set, so as to link and associate a three-dimensional model and a two-dimensional vector. The above scheme can enhance the flexibility of database structure adjustment and data conversion, realize the association of a three-dimensional model and an entity vector graph, reduce intermediate processing steps, and improve conversion efficiency.

The application discloses a kind of three-dimensional expression form basic geographic entity construction method considering morphological constraint, it is related to electronic information technical field, including the following steps: the vertex of the ground plot in land class map is based on elevation data acquisition elevation information, and according to the set elevation difference and slope threshold reservation geographic entity two-dimensional graph element within the point that shows topographic feature, the present application fully integrates land class map and elevation data, uses triangulation method to obtain the triangle net information of the basic geographic entity body graph element, is stored in three-dimensional model data format, material library is the rendering material of basic geographic data, more close to actual, realizes the stereoscopic of basic geographic entity, entity and semantic, simultaneously, this method solves the problem that topographic feature is simple to construct multiple types of basic geographic data, saves the tedious artificial modeling procedure, realizes that stock data is quickly converted into three-dimensional expression form basic geographic entity.

The invention discloses a network clue data change analysis method and system based on a knowledge graph, particularly relates to the technical field of data processing, and is used for solving the problem that a clue coordinate mapping result does not conform to an actual geographical current situation due to dependence on a static geographical entity knowledge graph in the prior art. The method comprises the following steps: describing and identifying spatial differences by aggregating multi-platform clue positions, and generating a change pre-check instruction when the differences relate to geographic entities in a preset range; performing topological manifold embedding analysis on the text in combination with the initial coordinates to generate a manifold embedding distance, and detecting a conflict rate of a spatial reference system; when the distance or the conflict rate exceeds a threshold value, triggering knowledge graph updating; and finally, re-matching based on the updated map to obtain a target geographic entity and coordinates. Real-time perception of geographic entity change and dynamic map correction are realized, and the accuracy and reliability of natural resource clue space positioning are effectively improved.

The application discloses a natural resource data association and graph display method and device and a storage medium, and relates to the technical field of geographical entity space identity coding. The method comprises the following steps: generating a space identity code of a geographical entity, wherein the space identity code is used for uniquely identifying the geographical entity in a global range; based on a preset association rule, an association relationship between the space identity code and original codes of at least one natural resource business data is established, and association data is obtained; according to a natural resource business process, a semantic relationship between the association data is defined; and based on the association data and the semantic relationship, a knowledge graph reflecting the space-time change of natural resources is constructed and displayed. The scheme combines the characteristics of geographical entity space identity coding, such as space position determination, global uniqueness and space-time association, and connects multi-source space-time data across businesses, systems and departments through geographical entity space identity coding, so that all-chain data falls on the same space unit.

The invention discloses a live-action three-dimensional geographic entity construction system fusing multi-source data, and relates to the technical field of computer vision and geographic information, the live-action three-dimensional geographic entity construction system comprises a data acquisition module, a data processing module and a model output module, and is characterized in that the data processing module comprises a multi-scale consistency constraint engine; and the engine is connected with the data acquisition module and the model output module, and is used for establishing an incidence relation among different detail level models and controlling a model generation process. According to the live-action three-dimensional geographic entity construction system fusing the multi-source data, by establishing a multi-scale consistency constraint mechanism and a hierarchical semantic topology relationship network, the problems of geometric cracks and texture jumping of the same geographic entity among different detail level models are effectively solved. The system can ensure the visual coherence and consistency of multi-scale expression while keeping the geometric accuracy of the model, so that the model can realize smooth transition among different scaling levels.

The application discloses a kind of based on deep fusion algorithm's multi-source heterogeneous geographic data processing method, comprising: collecting multi-source heterogeneous geographic data, and write into uniform index library;Perform coordinate reference normalization, time series complement and integrity-correctness joint verification, obtain standardized geographic data block;Carry out semantic-space joint matching, generate candidate cross-modal entity pair;Construct cross-modal attention network, extract fusion feature and calculate posterior fusion confidence;Select the highest confidence fusion result in each candidate cross-modal entity pair as target geographic entity, and generate unique fusion identification;The target geographic entity holding unique fusion identification is written into fusion database, and obtains uniform geographic entity dataset.The application solves the problems of low data fusion quality, insufficient fusion process credibility and cross-modal feature matching difficulty in the prior art, improves the fusion precision, efficiency and credibility.

The invention relates to a geographic entity construction and relation generation method and system, and the method specifically comprises the steps: determining target vector layers of a plurality of sources, and extracting layer names, attribute field names and corresponding attribute values from the target vector layers; performing multi-layer screening and comprehensive scoring based on the layer names so as to determine a standard layer category which is optimally aligned with the layer names; taking the standard layer category as a reference basis, performing target standard field mapping on the attribute field name of the target vector layer, and converting an attribute value corresponding to the attribute field name into a standard code so as to realize attribute standardization; obtaining geometric data of the target vector layer, generating a target vector entity based on the geometric data, and binding the corresponding standard attribute with the target vector entity; a topological relation and a membership hierarchical relation between entities and a reference relation between cross-source entities are established on the basis of spatial topological analysis and semantic association analysis, and a structured geographic relation network is formed accordingly.