7 results about "Spatial network" patented technology

The invention discloses an urban green land carbon sink dynamic accounting method and system based on multi-source data fusion and spatial network modeling. The method comprises the following steps: collecting urban green space carbon sink original data and preprocessing the data, and constructing a space * time * feature structure carbon sink data cube; identifying green land source plaques based on the spatial dimension data; taking the source ground plaque as an initial node, constructing a resistance surface by using a dynamic resistance factor, simulating a carbon flow in combination with a circuit theory, and generating a carbon flow gallery and a carbon flow density grid; inputting multi-source data into the carbon density dynamic calibration model, and outputting a dynamic grid; constructing a multi-scale prediction engine, and outputting carbon density prediction results under different time scales; and combining GIS and BIM technologies, inputting a prediction result and an urban space structure into a three-dimensional visual platform, generating a carbon density thermodynamic diagram and a carbon flow gallery evolution diagram, and realizing carbon sink dynamic accounting. According to the invention, the precision and space-time continuity of carbon sink accounting can be obviously improved.

The invention discloses a multi-dimensional traditional village clustering protection and utilization system construction method, and relates to the technical field of building protection, and the method is technically characterized in that the method comprises the steps: S1, selecting a research village cluster, and determining the spatial distribution type of the village cluster; s2, constructing a village cluster network based on a gravitation model, and mining village cluster space resources; s3, dividing village cluster areas according to the condensation subgroups and administrative demands, and improving the competitiveness of key areas; and S4, determining a grading and classification development strategy: carrying out grading protection and grading development on the village cluster according to resources. According to the method, a theoretical basis and an optimization regulation and control method are provided for clustered collaborative development of the traditional village centralized connected district by constructing a quantitative clustered protection and utilization system for defining a spatial distribution type, revealing a spatial network structure, mining spatial resource endowment, delimiting a spatial structure, implementing spatial individuals and determining a grading and classification development strategy; and a new thought is provided for protection and utilization of other cultural heritage areas.

The invention relates to a video stream pushing method and system based on a cloud mobile phone and a storage medium, and the method comprises the steps: firstly collecting cloud mobile phone task data, spatial network features and service labels in real time, and generating preprocessing data through a noise reduction auto-encoder, LSTM interpolation and normalization processing; secondly, a bidirectional gating circulation unit is combined with an attention mechanism to extract time features to construct a spatial relation graph model to excavate a spatial propagation rule, the time features, the spatial features and a service type coding vector are input into a gating fusion unit to generate a fusion feature vector, and then a network output resource demand prediction result is predicted; and finally, executing three-level resource allocation based on a prediction result, accessing external risk early warning data, switching resource suppliers by an evaluation system, and encrypting and monitoring full-link data. According to the scheme, the CPU and memory utilization rate is improved, the plug flow delay and the resource allocation response time are reduced, the limitation of traditional static allocation is broken through, and dynamic resource optimization is achieved.

A causal inference engine relies on a category database and a graph database. Via a loader, a category generator, and a spatial web generator, input data is received in disparate formats and converted into a normalized attribute vector comprising a mathematical model, experiment, experimental data, and miscellaneous attributes. The normalized attribute vectors are then loaded into a category database and a graph database. Specifically, the loader makes use of a multi-formal combinatorial parser, and an ontology store to convert the different data and formats into normalized attribute vectors. The category generator reviews mathematical model attributes in the normalized attribute vectors to associate vectors into mathematical categories. The spatial web generator performs similarity scores in the attributes of the vectors to determine placement in a graph database. The data in the category database and the graph database are then utilized by the causal inference engine to perform inferences.

This invention discloses a method and system for locating users in underground parking garages based on a lighting fixture composite controller. The method includes: a mobile terminal device sending a location request to the composite controller of the smart lighting fixtures; the composite controller receiving the request and obtaining the mobile terminal device ID and wireless signal strength value, and uploading the relevant information to a server via a wireless router gateway; the server constructing a parking garage spatial network topology using the composite controller as a graph node, the spacing between lighting fixtures as edges, and the wireless signal strength value as node features, and aggregating the signal features through a graph neural network to obtain the mobile terminal's location information; after the mobile terminal sends a search request, the server combining current and historical location information to formulate a guidance route and sending brightness control signals to designated smart lighting fixtures to provide lighting guidance. This invention integrates lighting fixtures with positioning functions, eliminating the need for dedicated positioning equipment, providing intuitive search instructions, and effectively improving the user experience of locating users in underground parking garages.

The invention discloses a rainfall prediction method, system and device and a readable storage medium, and relates to the technical field of rainfall prediction. According to the rainfall prediction method provided by the invention, a dynamic graph neural network is introduced, and according to collected meteorological time sequence data of a plurality of meteorological data sources, a time-varying spatial dependency relationship among meteorological elements is dynamically captured; low-resolution spatial features output by the graph neural network are input to a multi-scale downscaling dynamic module, a high-resolution spatial feature sequence is obtained, and the spatial precision of rainfall prediction under complex terrains and extreme weather is conveniently and remarkably improved; realizing collaborative modeling of a high-resolution spatial feature sequence and a time sequence in a to-be-predicted region by utilizing a time sequence diagram spatial network, and enhancing the reduction capability of a rainfall generation mechanism; the defect that the rainfall prediction result of a rainfall prediction method disclosed in the prior art is poor in precision and robustness under complex weather conditions is overcome.

The application discloses a kind of green space network optimization method and system for urban shrinkage, it is related to landscape architecture, urban and rural planning technical field, through high-resolution remote sensing image identification vacant land and combining machine learning algorithm establishes vacant land identification model, analysis vacancy rate and adopts K-means clustering division grid unit type, constructs vacant land conversion potential evaluation database and determines index weight using objective weighting method.Green space network is constructed based on graph theory model and the connection of node is analyzed using gravity model.Setting three target preference scenarios of life, ecology and production, and simulating network performance changes through global efficiency to determine the optimization threshold, finally combining network topology structure index and potential value, the importance and conversion priority of node are divided.It can scientifically evaluate the potential of green space in the process of urban shrinkage, optimize the spatial layout, improve the overall performance of green space network, and provide scientific support for the planning and management of green space.