1306 results about "Geographic information system" patented technology

The invention provides an information system engineering supervision project risk adaptive assessment method and system. According to the project management scheme, a dynamic knowledge graph is formed by constructing a data model fusing a building information model and a geographic information system. The three-dimensional coordinate track of the construction machinery is captured in real time by using an ultra wide band positioning device array, and the space occupied hot area distribution is generated by using a multipath interference suppression technology. An operation simulation environment is established based on a digital twinning technology, and a space-time risk topology network is established to early warn path conflicts and safety spacing problems. And according to network node density characteristics, dynamically adjusting a risk assessment parameter weight, and assessing an equipment collision probability and a construction process conflict index. Finally, the stress threshold value and the signal sampling frequency are adjusted according to the composite risk level result feedback, and construction management and safety guarantee are optimized. According to the technical scheme provided by the invention, the efficiency and safety of information system engineering supervision project risk adaptive assessment can be improved.

The invention relates to the technical field of environment monitoring, in particular to an underground water pollution source traceability identification method and system, and the method comprises the following steps: S1, collecting the flow velocity, flow direction and water level change data of underground water in a polluted region in real time; s2, constructing a preliminary underground water flow model; s3, simulating a migration path of pollutants in underground water, and predicting a potential pollution source position; s4, processing the collected underground water flow velocity and pollutant diffusion path data, and removing abnormal data interference; s5, generating a spatial distribution map of the potential pollution source in combination with a geographic information system; and S6, verifying pollutant components and concentration distribution thereof, and confirming the accuracy of a traceability result. According to the invention, by combining a multi-pollutant traceability algorithm, an underground water flow model and a geographic information system technology, a pollutant migration path is accurately simulated and a pollution source spatial distribution map is generated, so that the precision and reliability of underground water pollution source traceability are greatly improved.

The invention relates to the technical field of intelligent agriculture and ecological internet of things, in particular to an ecological irrigation decision dynamic optimization method and related equipment. Comprising the following steps: acquiring multi-source environment data, acquiring a soil profile humidity gradient in real time through a soil humidity sensor array, acquiring future rainfall probability distribution, a temperature change rate and a wind speed predicted value in combination with a weather forecast interface, and synchronously accessing a geographic information system to acquire terrain elevation and crop distribution data. The three technical bottlenecks of model dimension collapse, parameter estimation instability and optimization response lag in a traditional irrigation decision-making system are systematically solved by constructing a space-time coupling analysis framework and a closed-loop optimization mechanism of multi-source heterogeneous data.

The invention provides an intelligent runoff pollution monitoring and response method and system, and the method comprises the steps: arranging a plurality of monitoring points in a runoff region, collecting water quality, hydrological and meteorological data in real time through a sensor, transmitting the data to a data processing center through a wireless network, carrying out the preprocessing, storage and analysis, and calculating the comprehensive pollution index of each monitoring point. And comparing with a set index threshold value. When the comprehensive pollution index exceeds a threshold value, the system identifies and evaluates key water quality parameters so as to determine a reasonable parameter threshold value; once data of a monitoring point exceeds a preset pollution threshold value, an alarm mechanism is triggered, then a pipe network water flow model and a geographic information system are combined to reversely track a pollution path, accurately position a pollution source and provide a basis for pollution control, and the process comprises the steps of screening suspected pollution source nodes, calculating a propagation path probability and preferentially checking a high-probability path. The traced pollution source or path probability is lower than a preset value.

The invention discloses a karst collapse risk analysis method and system based on geological big data mining, and the method comprises the steps: collecting multi-source heterogeneous geological data, and carrying out the data fusion through employing a Tucker decomposition-based tensor decomposition algorithm; cleaning, complementing and standardizing the fused data; feature selection and construction: selecting features related to the karst collapse risk; carrying out feature extraction on the preprocessed data; based on the features extracted by the feature engineering, constructing a risk assessment model by using a graph convolutional neural network, and optimizing model performance through an ensemble learning method; carrying out risk assessment and prediction by utilizing the trained model, and carrying out visualization through a geographic information system; and real-time risk assessment is realized based on an edge computing technology, and the model is continuously optimized. According to the method and the system, complex heterogeneous data can be processed, the time change trend of geological parameters can be accurately captured, the prediction accuracy under complex geological conditions is high, and the timeliness of early warning is greatly improved.

The invention provides a green land carbon sink amount estimation method for ecological restoration planning, and the method comprises the steps: precisely collecting the vegetation coverage rate, species distribution, soil type and other data of a green land through integrating remote sensing images, unmanned aerial vehicle monitoring, a geographic information system and other technical means; the method comprises a vegetation carbon reserve model, a soil carbon reserve model and an environmental factor correction module, the vegetation carbon reserve is calculated by adopting an Allometric model, the soil carbon reserve is subjected to multi-layer estimation, and the carbon sink amount is corrected by utilizing meteorological conditions and topographic factors, so that the accuracy and applicability of estimation are improved, and the estimation accuracy is improved. According to the method, dynamic estimation of the carbon sink amount is realized through time sequence analysis and in combination with vegetation growth cycles and seasonal changes, and visual result display and decision support functions are provided. The method is widely applicable to various ecological environments such as urban green land, wet land and mountain land, and scientific basis is provided for ecological restoration planning and carbon sink monitoring.

The invention provides a cross-modal remote sensing image-text retrieval method based on multistage semantic collaborative matching, which comprises the following steps of: extracting a region of interest by using a semantic segmentation algorithm through an image preprocessing module, segmenting a remote sensing image into a plurality of regions and generating image blocks; respectively extracting global features, regional features and pixel-level features of the image, and carrying out fine-grained coding on key regions such as fine-grained ground feature edges and the like; the text multi-level coding module is used for carrying out three-level feature coding of documents, sentences and words on texts based on a pre-training language model to ensure multi-level understanding of the texts; in the multi-level matching and fusion module, the similarity between the remote sensing image and the text description is calculated through a cross attention mechanism, weighted fusion is carried out on features of all levels, and finally a retrieval score is output. The method not only improves the accuracy and robustness of image-text retrieval, but also can be widely applied to the fields of remote sensing monitoring, environment change recognition, geographic information systems and the like.

The invention relates to the technical field of intelligent water conservancy, and discloses a cross-regional water transfer project intelligent scheduling method and system, and the method comprises the steps: building a digital twin system based on a geographic information system, hydrological monitoring data and a spatial topological structure, and integrating a meteorological evolution prediction model, a basin hydrological response model and a water demand prediction model; predicting a water demand and an adjustable water amount by using a space-time convolutional neural network and a gating circulation unit; establishing a multi-objective optimization model taking water supply benefit, ecological influence and energy consumption cost as optimization objectives; an optimal water transfer scheme is generated through a Markov decision process and multi-agent cooperation; and carrying out robustness evaluation on the scheme and generating an emergency scheduling plan. According to the method, the scheduling efficiency and adaptability of the water transfer project are remarkably improved, and efficient configuration of water resources and quick response under extreme situations are achieved.

The invention discloses an intelligent cable fault accurate positioning and early warning method and system, and the method comprises the steps: collecting the temperature gradient, strain distribution and partial discharge signals of the whole length of a cable in real time through a distributed optical fiber sensing network, and generating a multi-dimensional feature matrix of the operation state of the cable; based on the multi-dimensional feature matrix, outputting a preliminary fault positioning coordinate; generating corrected fault coordinates according to the topological structure data of the cable laying environment and the electromagnetic interference distribution diagram; historical fault data, real-time operation parameters and the corrected fault coordinates are fused, and a fault risk thermodynamic diagram in a future preset duration is output; and based on the fault risk thermodynamic diagram and real-time monitoring data, generating fault first-aid repair information by using a dynamic priority algorithm, synchronously triggering an early warning signal, and visually displaying a fault positioning result and a risk area in a three-dimensional geographic information system. According to the embodiment of the invention, rapid positioning, accurate early warning and intelligent disposal of the cable fault can be realized.

The invention discloses a scenic spot visitor flow prediction method and system, an equipment terminal and a storage medium thereof, particularly relates to the technical field of scenic spot management, and is used for solving the problem that a comprehensive analysis and dynamic prediction method for a scenic spot visitor flow rule is lacked in the prior art. Multi-source tourist behavior data are collected and preprocessed, and a scenic spot functional area node relation model based on a group behavior principle and a geographic information system is constructed; generating a dynamic distribution state of the functional area by calculating a tourist crowding degree parameter and a dynamic distribution parameter; based on the historical visitor flow data and the real-time monitoring data, constructing a visitor flow propagation matrix and optimizing a migration weight; in combination with the propagation matrix and the dynamic distribution parameters, predicting scenic spot people flow in different time periods in the future, and generating time-period people flow distribution data; finally, the potential high-risk area is marked by analyzing the tourist density; and the precision and the dynamic adaptive capacity of scenic spot people flow prediction are improved.

The invention relates to the technical field of geographic information systems, in particular to a GIS-based urban land planning analysis method and system, and aims to construct a multi-scale space-time cube model by integrating remote sensing, historical planning, mobile terminals and social media data, generate standardized urban temporary land data and improve the urban land planning analysis efficiency. Adaptive feature extraction is adopted to identify temporary land, a hierarchical classification system is established, abnormal changes are monitored through a time sequence model, an association diagram of the temporary land and an urban function network is constructed, an interaction relation is analyzed, finally, differentiated urban planning optimization suggestions are proposed, efficient configuration and management of urban land resources are assisted, and through fusion of multi-source data, the urban planning optimization suggestions are optimized. Multi-dimensional cognition of space, time, functions and relations is achieved, and the understanding depth of temporary land is fundamentally improved.

The invention provides a first-aid information processing method and system based on multi-source data fusion. The method comprises the following steps of: performing deep association matching and modeling on an emergency event by utilizing a multi-source heterogeneous data stream, a geographic position, a timestamp and environmental perception data which are acquired in real time to obtain a dynamic emergency event situation model; according to the dynamic first-aid event situation model, a resource optimization algorithm is adopted to evaluate and select the most suitable first-aid resource, and a first-aid resource configuration scheme and instant guidance information are obtained; updating the state of the patient based on the first-aid resource allocation scheme and the instant guidance information, and obtaining a dynamically adjusted first-aid process and an optimized path scheme through geographic information system path planning analysis, first-aid strategy adjustment and resource allocation path optimization; and integrating various feedback data related to the dynamically adjusted emergency process and the optimized path scheme, carrying out post analysis, and generating an optimized guide. According to the technical scheme provided by the invention, the first-aid information processing efficiency is greatly improved.

The invention relates to the technical field of underground drainage pipeline monitoring and hidden danger analysis, and provides an underground drainage pipeline hidden danger data analysis method based on big data, which comprises the following steps: acquiring data such as flow, water level, pressure and pipeline structure by using a multi-source sensor to form an original monitoring data set; preprocessing the data, extracting time domain, frequency domain and spatial topological features, and constructing a multi-dimensional feature vector; and inputting the feature vectors into a pre-trained hidden danger prediction model, and outputting hidden danger types and position coordinates. And constructing a spatio-temporal data analysis model based on the hidden danger position, generating a spatio-temporal correlation feature matrix, and performing dynamic risk assessment to obtain hidden danger development trend parameters. And the hidden danger information is mapped to a geographic information system, a three-dimensional visual analysis result is generated, and a graded early warning instruction is transmitted to a drainage pipe network operation and maintenance management system through a communication interface. The operation and maintenance management efficiency of the drainage pipeline can be improved, the hidden danger checking cost is reduced, and the safety and reliability of the drainage system are enhanced.

The invention discloses an urban building three-dimensional automatic modeling and visualization method, and belongs to the technical field of building three-dimensional modeling. The method comprises the steps that point cloud data, high-resolution images and geographic information system data of urban buildings are acquired, data cleaning, registration and alignment are carried out, and preliminary building digital representation is formed; accurately segmenting each building, and identifying the contour and main structural features of the building; based on the data integrity and the building complexity, adaptively selecting a proper reconstruction strategy to carry out three-dimensional reconstruction; in the reconstruction process, the geometric structure is analyzed and optimized in real time, and potential topological problems are repaired; automatically generating missing details based on a predefined architectural style library and a component library, and performing material inference and texture mapping; a graph structure is used for representing the relation between the buildings, and the positions and orientations of the buildings are adjusted through a global optimization algorithm; a rendering engine supporting multi-level detail switching is developed, and smooth visualization and interaction of a large-scale city scene are achieved.

The invention provides a photovoltaic power station operation state monitoring method based on unmanned aerial vehicle inspection, and the method comprises the steps: carrying out the surveying and mapping of the geographic position, landform and photovoltaic array layout of a photovoltaic power station through employing a surveying and mapping technology and a geographic information system, so as to build a digital photovoltaic power station model; acquiring technical parameters of each component of the photovoltaic power station, and mapping the technical parameters to the digital photovoltaic power station model; based on a preset inspection plan and the digital photovoltaic power station model, automatically generating an unmanned aerial vehicle inspection path; obtaining monitoring data obtained by the unmanned aerial vehicle according to the unmanned aerial vehicle inspection path, wherein the monitoring data comprises an appearance image of a photovoltaic array, temperature distribution of a photovoltaic module and illumination intensity data of different areas of a photovoltaic power station; vectorizing the monitoring data to obtain an input vector; and the operation state monitoring model performs feature extraction on the input vector so as to analyze the operation state of the photovoltaic power station.

The invention discloses a dam seepage stability analysis method based on flood forecasting, and relates to the technical field of hydraulic engineering safety monitoring, comprising the following steps: S1, integrating a flood forecasting system and a seepage monitoring system into a data acquisition layer, and acquiring flood forecasting data and seepage monitoring data by a sensor of the data acquisition layer; s2, performing space-time alignment on the flood forecast data and the seepage monitoring data through a space-time coupling interface of the dynamic fusion layer, and generating a dynamic driving variable of a seepage field boundary condition based on a flood routing model and a geographic information system spatial interpolation technology; through the space-time coupling interface, space-time alignment and dynamic driving variable generation of flood forecast data and seepage monitoring data are achieved, the problem that the real-time flood routing process cannot be reflected due to the fact that the boundary condition is static or lagged in traditional analysis is solved, the seepage field calculation boundary condition can be dynamically updated along with flood forecast, and the real-time flood routing process cannot be reflected. And the timeliness and accuracy of model calculation are improved.

The invention relates to the technical field of geographic information systems, in particular to a map tile data efficient access method and system based on hybrid storage and intelligent layering, and the method comprises the following steps: constructing a multi-level storage architecture, carrying out dynamic heat analysis, carrying out intelligent layering scheduling, preloading and space prediction, and carrying out transmission and access optimization. The method has the beneficial effects that the multi-level storage pool is constructed by combining the advantages of object storage and a distributed file system; adopting a dynamic tile popularity analysis model to realize hot data cache acceleration and cold data hierarchical archiving; and meanwhile, a tile request preloading mechanism is introduced, and an access path is optimized in combination with a spatial locality prediction algorithm. According to the method, the storage cost can be remarkably reduced, the tile request delay is reduced, quick response in a high-concurrency scene is supported, and the method is suitable for application scenes such as Internet map services and smart cities.

The invention relates to the technical field of coal mine disaster monitoring, in particular to a gas coal mine goaf coupling disaster monitoring method, an electronic device and a storage medium, and the gas coal mine goaf coupling disaster monitoring method comprises the following steps: obtaining comprehensive data of a goaf through a sensor network, and carrying out data preprocessing to obtain standardized data; constructing a digital twinborn model through a 3D modeling and geographic information system technology; performing data synchronization and model correction processing on the digital twinborn model, and optimizing parameters and states of the digital twinborn model; constructing a fluid-solid-heat multi-field coupling model through a computational fluid mechanics and finite element analysis method; constructing a risk assessment model through an analytic hierarchy process and a fuzzy comprehensive evaluation method; training a disaster early warning model by using a machine learning algorithm based on the standardized data and the risk assessment model; a digital twinborn model, standardized data, a risk assessment model and a disaster early warning model are integrated, and a visual interaction platform is constructed. According to the monitoring method, multiple disaster elements can be coupled and dynamically evolved, and the disaster prediction accuracy and timeliness are greatly improved.

The invention belongs to the field of disaster early warning, and provides a disaster early warning method and system based on key target detection and image segmentation, and the method comprises the steps: obtaining the real-time image data of a site, and carrying out the preprocessing of an image; processing the preprocessed image through a YOLOv5 target detection algorithm, detecting a key target in a disaster site, and outputting a category label and a bounding box of the target; performing pixel-by-pixel segmentation processing on a bounding box region output by target detection by using a U-Net image segmentation algorithm to generate an accurate segmentation mask of the target; and inputting the image segmentation mask, historical disaster data, meteorological data and geographic information system data into an LSTM prediction model, carrying out multi-source data fusion and time sequence analysis, and outputting dynamic prediction information and early warning levels of disasters. According to the invention, real-time monitoring and early warning of disasters are realized, the response speed of the early warning system is obviously improved, more comprehensive disaster early warning information is provided, high precision of disaster prediction is ensured, and the phenomena of false alarm and missing alarm are reduced.

The invention discloses a three-dimensional GIS (geographic information system) system for safety assessment of an urban gas pipeline internet of things. A gas pipe network monitoring and assessment system combining the internet of things, a mobile internet and BIM / GIS information is established. Firstly, an overall framework based on sensing, transmission, knowing and use of the internet of things is established; secondly, a front-end sensing system deployment scheme is established, a database system is built, and index data are collected and stored; thirdly, a gas leakage hazard model is constructed, and possible hazard consequences are evaluated; 4, a pipe network monitoring system application layer module is constructed, and underground space information management, safety analysis, prediction and early warning and an auxiliary decision making module are achieved; and establishing a gas pipe network risk identification module, a basic information checking module, a monitoring and explosion early warning module, a three-dimensional visualization module and an auxiliary decision-making module. The system monitors the operation condition of the gas pipe network in real time, analyzes the operation rule of the gas pipe network, evaluates the risk of the gas pipe network, predicts, early warns and decides in time, changes passive first-aid repair into active protection, and is high in monitoring stability, precision and efficiency.

The invention discloses a method and system for estimating irrigation water consumption and water utilization efficiency, and relates to the technical field of water resource management, and the method comprises the steps: collecting the plant stem flow rate, canopy temperature and soil profile water content data of a target area through a multi-source sensing device, and obtaining a gradient and permeability distribution diagram of a geographic information system; dividing the farmland of the target area into sub-areas with different irrigation priorities based on a soil conductivity mutation point detection algorithm; constructing a dynamic water demand model fused with the plant transpiration hysteresis effect, performing space-time correlation analysis on the stem flow rate data and the soil moisture content gradient, and calculating the real-time water demand intensity of each sub-region; the method comprises the following steps: accessing short-time rainfall prediction data of a meteorological radar, dynamically correcting a future irrigation decision by adopting a sliding time window mechanism, and triggering a gradient delay irrigation instruction when the predicted rainfall amount exceeds an irrigation threshold value; and calculating the actual moisture utilization efficiency based on the inversion data of the moisture content of the irrigated soil and the unmanned aerial vehicle multispectral image.

The invention discloses an intelligent city management information visualization comprehensive management method and system, particularly relates to the technical field of city management, and is used for solving the problem of misalignment of emergency response caused by false association and causal confusion in the prior art. Precise management is realized through multi-modal time sequence data feature alignment, causal chain network dynamic construction and a visual decision mapping technology, firstly, multi-dimensional event features of video monitoring, sensors and text work orders are extracted, a cross-modal association chain is constructed, interference chains are screened out through causal strength evaluation and anti-fact verification, and a visual decision mapping algorithm is established. According to the method, dynamic correction parameters are generated in combination with space-time weights and feedback priorities, finally, a visual guidance scheme is output by fusing a causal chain network and a geographic information system, decision optimization is driven through causal logic, and city event disposal accuracy and cross-department cooperation efficiency are remarkably improved.

The invention relates to a true orthophoto generation method based on a three-dimensional Gaussian model, a storage medium and equipment, and aims to solve the problems of low image quality, low generation speed, detail loss and the like in the prior art. The method comprises the following steps: firstly, acquiring image data through an unmanned aerial vehicle or aerial photography, and extracting a camera attitude and sparse point cloud by using a motion recovery structure (SfM) technology; secondly, constructing a three-dimensional Gaussian model based on the sparse point cloud, and performing iterative training through top view orthographic projection in combination with a gradient descent algorithm; in the training process, a densification strategy, a point deleting strategy, a blocking strategy and an image pyramid strategy are innovatively introduced, so that the detail expressive force and the overall quality of the image are remarkably improved. Specifically, according to the densification strategy, fine detail reconstruction is achieved by dynamically increasing Gaussian ball density, and according to the point deletion strategy, rendering efficiency is improved and computing resource allocation is optimized by eliminating redundant Gaussian balls. The image pyramid strategy generates a multi-level visual effect through multi-scale training, and the blocking strategy improves the reconstruction precision through local optimization. Finally, on the basis of the trained three-dimensional Gaussian model, real-time generation of a high-quality true orthophoto in a large-scale scene can be realized. The method has remarkable advantages in the aspects of efficiency, precision and practicability, provides important technical support for the fields of geographic information systems, urban planning, disaster monitoring and the like, and has wide application prospects.

The invention discloses a power station digital road network topology dynamic construction method for complex mountain photovoltaic, and relates to the technical field of photovoltaic power station construction, and the method comprises the steps: obtaining mountain terrain data and shelter data of a target area based on a geographic information system and a remote sensing technology; establishing a digital road network topology model by using the collected data, and simulating photovoltaic array layouts under the conditions of different terrains and shelters; in the digital road network topology model, shielding interference analysis is carried out, and the influence degree of shielding interference on the power station layout is evaluated. According to the power station digital road network topology dynamic construction method for complex mountain photovoltaic, through digital road network topology dynamic construction, the layout of a photovoltaic array is optimized so as to adapt to complex mountain terrains, interference of topographic relief, gradient change and shelter distribution is comprehensively analyzed, the shelter effect is reduced to the maximum extent, and the power station digital road network topology dynamic construction method has the advantages that the power station digital road network topology dynamic construction method is suitable for the complex mountain terrains; therefore, the power generation efficiency of the photovoltaic array is improved, and a photovoltaic power station is always kept in a high-efficiency operation state.

The invention discloses a soil nutrient recycling method and system based on prediction driving, and belongs to the technical field of agricultural soil management.The method specifically comprises the steps that soil nutrient content data are obtained through sampling, and soil nutrient abnormal areas are preliminarily screened in combination with a geographic information system and a remote sensing technology; soil physicochemical properties are measured in the soil nutrient abnormal area, soil nutrient form distribution is measured through X-ray diffraction and near infrared spectroscopic analysis, and nutrient stability and release potential are evaluated; constructing a soil nutrient cyclic dynamic model based on multi-source data, and simulating nutrient evolution; according to simulation results, crop requirements, soil states and environmental factors, an accurate fertilization scheme is formulated; intelligent management and precise fertilization of soil nutrients are realized, and the fertilizer utilization rate and the agricultural production efficiency are improved.

The invention discloses a submarine cable fault online diagnosis and positioning method and system based on an optical fiber sensing technology, and relates to the technical field of optical fiber sensing, and the method comprises the steps: obtaining a real-time strain data flow of a submarine cable through a distributed optical fiber strain measurement device; carrying out space-time alignment and abnormal value correction processing on the original data set, and constructing a target data set; coordinate mapping is carried out on the target data set and a geographic information system of a submarine cable laying line, and a fault diagnosis layer with multi-dimensional visualization features is generated; an interactive fault analysis panel is generated on a geographic information system interface, and the deviation ratio between the strain theoretical threshold value and the actual measurement value of each monitoring point in the target data set is calculated; according to the submarine cable fault online diagnosis and positioning method and system based on the optical fiber sensing technology, rapid positioning of fault features is achieved, the fault response efficiency is improved, and long-term stable operation of a submarine communication network is ensured.

The invention provides an instrument panel type building engineering construction progress display method, system and device and a medium, and relates to the field of building construction management.The method comprises the steps that geographic information system map data and building information model data of an area where a building project is located are obtained and fused, and then a multi-dimensional display platform of the building engineering progress is constructed and formed; actual progress data, historical construction data and environment data of a construction site are collected, risk factors of construction tasks are analyzed, the dependency relationship between the construction tasks is analyzed through topological sorting, and a construction risk task tree is constructed; a construction risk task tree is adopted to identify potential risks of a construction task, weighted calculation is carried out on risk factors according to weight coefficients, a comprehensive risk assessment score of the construction task is generated, a construction progress sequence is optimized, and integration is carried out through an instrument panel to form a unified visual display interface. Dynamic prediction, real-time display and automatic adjustment can be realized, and the accuracy of construction progress monitoring is improved.

The invention discloses a power distribution network visual management and control method and device, a storage medium and a product, and the method comprises the steps: obtaining the multi-dimensional information of a power distribution network in a target region, carrying out the preprocessing of the multi-dimensional information, obtaining a standardized power distribution network data set, carrying out the recognition of a power distribution network problem according to the power distribution network data set, and obtaining a power distribution network fault. The method comprises the following steps: obtaining a structured problem list of a power distribution network, carrying out spatial positioning and attribute mapping processing on the structured problem list in a preset geographic information system to obtain a power distribution network problem spatial distribution representation, and carrying out multi-dimensional analysis and prediction on the operation condition of the power distribution network according to the power distribution network problem spatial distribution representation. And obtaining a management and control strategy of the power distribution network, carrying out resource allocation according to the management and control strategy to obtain a cooperative work flow, and visualizing the problem space distribution representation of the power distribution network and the cooperative work flow in a geographic information system to provide a visual management and control mode. And the management efficiency and safety of the power distribution network are improved.

The present invention discloses a city planning simulation system based on real-scene three-dimensional (3D) and relates to the technical field of city planning. The system comprises the following components: a data acquisition module, a real-scene three-dimensional (3D) and disaster simulation module, a comprehensive planning module and a comprehensive evaluation module. The present invention plans the optimal emergency evacuation route by utilizing a path planning algorithm and taking into account the area affected by the damaged infrastructure and the recovery time of the infrastructure, thereby not only ensuring the safety and feasibility of the evacuation route but also greatly improving the evacuation efficiency. At the same time, according to the emergency evacuation route planning results and the infrastructure resilience evaluation results, the type and layout of the rescue facilities are determined, the service scope and coverage of the rescue facilities are analyzed by a geographic information system, the layout of the rescue facilities is optimized, and it is ensured that the rescue resources can efficiently and accurately reach the disaster-stricken area.

The invention discloses a homogeneous real estate space intelligent search method and system based on space partition, and relates to the technical field of space data processing and intelligent search. According to the homogeneous real estate space intelligent search method and system based on space partition, the data of the target real estate area is obtained and preprocessed, so that the accuracy and integrity of the data are ensured; dividing the pre-processed area into a plurality of space subareas through a geographic information system, extracting homogeneous features through a clustering algorithm, and analyzing a peripheral matching adaptation degree index of each subarea in combination with geographic position preference of a user to form a homogeneous house resource set; and searching and matching the homogeneous house resource set through a collaborative filtering algorithm, generating a user recommended house resource list, calculating a matching degree index of house resources in each partition, setting a dynamic feedback mechanism, and sorting the recommended house resource list in real time, so as to improve the user satisfaction. Personalized housing resource recommendation is provided for the user, and the convenience and accuracy of real estate transaction are improved.