140 results about "Site selection" patented technology

The application provides a kind of large-span underground powerhouse site selection evaluation index weight calculation method, belong to the intersection technical field of geology engineering and artificial intelligence, including the following steps: define the ontology model of geological risk knowledge graph;Based on BERT model, model fine-tuning is carried out to generate GEO-KG-BERT model, so that GEO-KG-BERT model can accurately identify the core entity and key relationship in geological text;The core entity and key relationship are extracted using the GEO-KG-BERT model, and the key relationship of the ontology model of "node-edge-attribute" is constructed;Based on the geological risk knowledge graph, the number of relationships, path intensity and importance are calculated;The importance of all geological indicators is normalized to generate an initial weight vector;The initial weight vector is corrected to obtain the final weight vector.The application calculates the weight of the large-span underground powerhouse site selection evaluation index based on the knowledge graph and GEO-KG-BERT model, and dynamically corrects the semantic support parameters based on the GEO-KG-BERT model, which improves the objectivity and accuracy of the risk evaluation result.

The application discloses a kind of based on multi-source data fusion's catering intelligent decision-making method and system, it belongs to site selection decision-making technical field, by using big language model to carry out knowledge extraction to multi-source data, and to this construction catering site selection knowledge graph, based on knowledge graph automatically calculates geographic position index, traffic accessibility index, consumption potential index and the objective weight of competitive environment index, simultaneously using big language model to the qualitative description of the region to be selected is retrieved to obtain membership vector, according to objective weight and membership vector calculation comprehensive suitability degree score, the recommended site selection region is obtained by ordering comprehensive suitability degree score, it quantifies index weight by catering site selection knowledge graph, avoids subjective dependence on expert experience, quantifies index using big language model, significantly improves the accuracy and efficiency of catering site selection, adapts to large-scale multi-source heterogeneous data scene, and in the face of dynamic factors can respond to update in time, convenient for application and promotion.

The application discloses a multi-level guarantee site selection method based on a network structure. The application introduces a multi-level site selection method based on a task mission. In view of the actual demand of government operation and management under the epidemic background, different site selection targets are determined according to different guarantee level task missions, thereby completing the construction of a three-level site selection model for epidemic life material guarantee, and improving the authenticity and feasibility of the guarantee site selection model. Moreover, according to the node site selection condition of the lower level, the application selects the node of the upper guarantee level, and forms a stable and convenient network guarantee system. In addition, the application divides the node site selection model of the first guarantee level with a large number of nodes into two stages through a two-stage algorithm, introduces secondary site selection based on heuristic rules for the residential area with high demand, reduces the complexity of the solution of the first stage, and effectively improves the site selection efficiency.

The application discloses a land-air collaborative composite traffic network design method considering park-and-ride, and plans and designs a land-air collaborative composite traffic network with a vertical take-off and landing field as a center in a future land-air collaborative composite traffic network background, and proposes a corresponding network design model and a solving algorithm, mainly including: (1) a two-level planning model related to site selection, capacity allocation and integration of a landing field of an electric vertical take-off and landing aircraft (eVTOL) and ground parking facilities; (2) for a network equilibrium model in the two-level planning model, a modified improved gradient projection (M-iGP) algorithm is designed in an augmented Lagrange multiplier (ALM) framework; (3) a sensitivity analysis (SAB) algorithm is used to solve the two-level planning model, and the model and the algorithm are verified and analyzed in a Sioux Falls network.

This disclosure provides a method and system for selecting the site of pumped storage power stations based on spatial constraints and elastic buffers, relating to the field of data processing technology. The method includes: acquiring a set of spatial constraint elements corresponding to the pumped storage power station; determining the constraint control rules corresponding to each spatial constraint element in the set; applying range constraints to each associated spatial constraint element based on the constraint control rules; generating at least one elastic buffer corresponding to each spatial constraint element; determining engineering requirement indicators and geological assessment indicators; and filtering the elastic buffer based on the engineering requirement indicators and geological assessment indicators to obtain the target effective construction area. This solution enables differentiated management of different types of spatial constraint elements, thereby ensuring the safety of pumped storage power station construction, and allows for multi-dimensional filtering of elastic buffers to determine the target effective construction area, ensuring the accuracy and practicality of the target effective construction area.

The application discloses a power distribution area collaborative planning method and system based on a neural network agent model, and the method comprises the following steps: constructing a double-layer optimization model of flexible interconnection and energy storage collaborative planning of a power distribution area; randomly generating a candidate site and capacity scheme satisfying the constraint conditions of the double-layer optimization model, and performing optimization calculation of a running model on each candidate site and capacity scheme to obtain a real total cost of the whole life cycle corresponding to each candidate scheme, thereby forming a training sample set; performing supervised training on a preset neural network agent model; generating and iteratively updating a site and capacity scheme, evaluating the predicted total cost of the site and capacity scheme by using the neural network agent model, optimizing the site and capacity scheme according to the predicted total cost, and outputting a final target site and capacity scheme and a corresponding collaborative running strategy until a convergence condition is satisfied. The method effectively solves the problems of disconnection of 'planning-construction-operation', low calculation efficiency and the like in traditional planning, and realizes collaborative improvement of safety and solution efficiency.

This application provides a method, apparatus, equipment, and storage medium for the site selection and planning of medium-voltage flexible interconnection equipment, belonging to the field of power distribution technology. The method includes: acquiring basic data of the target medium-voltage distribution network; constructing a power grid structure fusion model based on the basic data, calculating electrical centrality indicators, load fluctuation impact indicators, and economic sensitivity indicators; selecting key candidate nodes for flexible interconnection equipment from the power grid structure fusion model based on the electrical centrality indicators, load fluctuation impact indicators, and economic sensitivity indicators; constructing a multi-objective optimization model based on the key candidate nodes and the power grid structure fusion model; solving the multi-objective optimization model using an improved genetic algorithm to obtain the optimal solution set for the site selection schemes of the flexible interconnection equipment; and obtaining a list of site selection schemes for the flexible interconnection equipment based on the optimal solution set. The method, apparatus, equipment, and storage medium for the site selection and planning of medium-voltage flexible interconnection equipment provided in this application can improve the economic efficiency and reliability of power distribution network operation.

The application discloses a wind power generation site selection method based on ancient storm deposition background and relates to the field of power generation site selection, which comprises the following steps: setting a unified space reference, forming an input data set, performing wind source basin assimilation fusion, generating modern wind field three types of grids, and configuring a modern wind field deposition response calibration reference domain. Long-term wind direction and wind speed prior are established by using storm deposition records and direction evidence, annual uncertainty caused by only relying on short-term wind measurement is reduced, hard constraint filtering is formed by using soft sediment deformation risk coding and boundary stability marking, a penalty term is introduced into scoring, ground investigation and construction stage risks are reduced, candidate area output synchronously gives evidence chain index and uncertainty level, short-term wind measurement review, ground investigation review and deviation backwriting self-calibration iteration are performed, and finally, site selection achievement package containing superimposed graph and evidence chain list is solidified, so that site selection decision transparency and landing efficiency are improved.

The application discloses an intelligent commercial site selection method and device based on big data analysis and a medium, relates to the technical field of big data analysis, and comprises the following steps: collecting a commercial site selection coupling data set, performing feature alignment, and forming a standard space-time data stream; adopting an Apache Flink stream processing engine to perform complex event mode recognition on the standard space-time data stream, and forming a reference point address digital portrait; inputting the reference point address digital portrait and the commercial site selection coupling data set into a deep learning site selection model; performing time series modeling and space encoding through a feature coding layer; performing space clustering analysis and similarity calculation through a similarity measurement layer; and outputting a site selection similarity cloud map. Through the Apache Flink stream processing engine and the deep learning site selection model, the application enhances the fusion precision between multi-source data and significantly improves the dynamic prediction capability of commercial site selection.

The application discloses a substation site selection geographic information identification method, system, device and medium, comprising: performing geographic feature extraction on first geographic data of a substation planning area to obtain geographic information features, and performing site selection constraint quantization based on the geographic information features to obtain substation site selection constraints; inputting second geographic data of the substation planning area into a semantic segmentation model to obtain a target suitable construction area in the substation planning area output by the semantic segmentation model; performing area screening on each position space area in the target suitable construction area based on the substation site selection constraints to obtain a target position space area; and performing site selection point screening on each site selection point in the target position space area based on a power shortage area to obtain a final substation site selection point. The application guarantees the rationality of substation site selection and improves the reliability of substation site selection.

The application discloses a site selection method and device, equipment, medium and product, and relates to the technical field of data processing. The site selection method comprises the following steps: acquiring grain flow stream data; determining a feasible time for each transportation node that meets a first constraint condition according to the grain flow stream data, wherein the first constraint condition indicates that the grain can be unloaded at the transportation node and the ship can safely sail on the waterway; establishing a multi-objective integer programming model, wherein an objective function of the model is used to realize the dual objectives of minimizing the time-related grain loss risk and the task overdue cost, and a second constraint condition of the model comprises a storage transportation channel feasibility constraint condition based on the transportation node and the grain storage institution and a grain unloading operation feasibility constraint condition based on the grain flow task requirement and the feasible time; generating a candidate site selection scheme according to the second constraint condition; and solving the multi-objective integer programming model based on the candidate site selection scheme to obtain a site selection scheme that minimizes the objective function value under the condition of meeting the second constraint condition. The application can balance the feasibility and economy of grain transportation.

The application relates to the technical field of new energy vehicles, and provides a new energy vehicle charging pile space layout method and an operation management platform.The method comprises the following steps: acquiring the position attributes of existing charging piles in a target area; determining hot spot areas according to the first clustering results of the position attributes of the existing charging piles; determining candidate construction sites based on the hot spot areas and a preset site selection strategy; creating virtual charging piles for each candidate construction site, and collecting user demand data based on the virtual charging piles; screening target charging piles from the virtual charging piles based on the user demand data, and generating a charging pile layout plan according to the target charging piles. Based on the above method, reasonable charging pile layout plans can be acquired in the preparation stage of new charging pile construction, so as to provide effective suggestions for the site selection of charging piles.

The application provides a charging station position determination method and device, electronic equipment and a storage medium. The method comprises the following steps: in response to a selected site selection range in an interactive interface, performing regional division on the site selection range to obtain a candidate region; querying positioning information of a vehicle in the site selection range and charging monitoring data of a built charging station in the candidate region; determining charging demand parameters of the vehicle in the candidate region according to the positioning information of the vehicle; determining charging supply parameters of the candidate region according to the charging monitoring data of the built charging station in the candidate region; and performing classification processing on the candidate region according to the charging demand parameters and the charging supply parameters, so as to display a type label of the candidate region on the interactive interface. In this way, the type label of the candidate region is displayed on the interactive interface, the site selection of the charging station position is considered from the perspective of whether the charging supply and demand of the charging station in the candidate region are balanced, and the utilization efficiency of the charging gun in the subsequently selected charging station is improved.

This application relates to the field of land use selection technology, and provides a land use selection method and related equipment. The method includes: acquiring a regional map of a target area and extracting multiple land parcels from the regional map; aggregating all land parcels to obtain multiple candidate land parcels, and acquiring spatial information for each candidate land parcel; calculating a selection score for each candidate land parcel based on user location requirements and the spatial information of all candidate land parcels; and determining the final selected land parcel from all candidate land parcels based on all selection scores. The method of this application can improve the rationality of land use selection.

This invention relates to intelligent transportation technology and aims to provide a data-driven robust site selection method for heterogeneous risk management in drone-assisted accident handling. The method includes: cleaning and preprocessing historical traffic incident data, extracting accident tags and performing quantitative classification based on the U-I-A multidimensional evaluation framework to obtain a structured dataset; decomposing uncertain demand into basic normal demand and multi-source heterogeneous fluctuations, and establishing a structured uncertainty set based on the quantitatively classified structured dataset; modeling the robust site selection planning model as a minimax robust optimization problem, and then equivalently reconstructing it into a solvable single-stage mixed integer linear programming model; using a solver to solve the problem, obtaining the globally optimal hangar site selection scheme and the number of supporting drones, and outputting the results. This site selection method enhances the reliability and robustness of the drone emergency response system; it enables scientific planning of drone site deployment, achieving rapid and stable emergency response.

This application relates to the field of power grid planning technology and provides a method, apparatus, equipment, and medium for determining the capacity and location of substations. The method includes: First, collecting load data of each user in the area to be planned; Second, dividing the reasonable power supply range of existing substations based on the load data of each user in the area to be planned and preset constraints; users within the reasonable power supply range are powered by existing substations, including existing users and planned users; Third, matching the site capacity to existing users and planned users outside the reasonable power supply range, and planning the location of substations based on the site capacity; Fourth, merging the planned substations and existing substations to obtain new existing substations; Fifth, repeating steps two through four for the new existing substations until no new planned substations are needed. This application can achieve the site selection and capacity determination of substations and distribution stations while minimizing the construction and operation costs of low-voltage lines.

This invention relates to the fields of deep space exploration engineering planning and artificial intelligence technology, specifically disclosing a method for selecting a lunar south pole research station based on a multimodal large model. The method includes: constructing a site selection index toolkit containing various evaluation tools; acquiring and fusing multi-source data from the lunar south pole to construct a unified multimodal semantic grid and comprehensive cost model; encoding environmental features and mission objectives into cue vectors using an encoder; calculating the similarity between the cue vectors and tool capabilities based on the multimodal large model, dynamically filtering matching toolchains and generating adaptive weight parameters; iteratively optimizing the site selection evaluation results through a closed-loop optimization mechanism of "evaluation-feedback-adjustment" until convergence conditions are met; and finally outputting the optimal or near-optimal site selection scheme, supporting dynamic relocation under data and mission updates. This invention achieves intelligent fusion of multi-source data and multi-objective adaptive decision-making in complex environments, significantly improving the scientific rigor, objectivity, and efficiency of lunar research station site selection.

The application relates to a renewable energy site selection method considering ecological service value and belongs to the technical field of renewable energy site selection. The application considers the ecosystem influence of energy deployment, and proposes a renewable energy site selection method which comprehensively considers energy supply potential, economic, social, technical cost and ecosystem influence, and the method comprises the following steps: collecting basic data, processing obtained geographic information data; screening ecosystem service types, and determining various indexes involved in site selection; setting a limiting factor, and removing unfeasible patches in a region to be selected; calculating traditional index values and ecosystem service value related index values; determining the index weight by using an analytic hierarchy process; and quantitatively evaluating site selection suitability to obtain a renewable energy suitability distribution map. Therefore, the economic, social, technical and ecological comprehensive benefits of renewable energy site selection are optimized.

The application belongs to the technical field of charging facilities, and discloses a charging station site selection and capacity configuration optimization method based on multi-source space-time data, which collects six-dimensional full multi-source space-time data of vehicles, power grids and the like, divides basic and vehicle-end characteristic data categories, performs full-process standardized processing, completes exception correction, missing completion and unification of CGCS2000 space coordinate system and dynamic time granularity, also realizes vehicle-network space-time calibration and builds an integrated index database of GeoHash coding; improves planning basic data precision, eliminates space-time matching deviation of different data sources, realizes rapid retrieval and linkage query of vehicle-network charging data; through construction of a three-level space-time constraint system, high feasibility alternative stations are screened, multi-dimensional decision variables are determined and a site selection-capacity-vehicle-end adaptation collaborative correlation matrix is built, five core multi-objective optimization directions are established, and an improved NSGA-III algorithm is used for solving and sorted by an entropy weight-TOPSIS method.

This invention relates to a distribution network reconfiguration method based on distributed generation and SOP (Standard Operating Procedure) optimization configuration, belonging to the technical field of new energy grid connection and distribution network optimization operation. The method includes: performing site selection and capacity determination on the original distribution network using an improved gray wolf algorithm based on a constructed distributed generation optimization configuration model; updating the distribution network structure to form a new distribution network structure, constructing an SOP optimization configuration model, and optimizing the SOP configuration using an improved sensitivity analysis method; connecting the optimal access location and capacity of the distributed generation obtained from site selection and capacity determination, along with the SOP optimized configuration capacity and location, to the distribution network, constructing a distribution network demand response model; constructing a distribution network reconfiguration model based on the distribution network demand response model, reconfiguring the distribution network, obtaining the distribution network disconnection results, and thus obtaining a new topology. It aims to solve the technical problems of increased voltage fluctuations, increased network losses, and bidirectional power flow caused by a high proportion of distributed generation access to the distribution network.

The present application relates to a layered photovoltaic power station site selection and wiring collaborative optimization method based on a graph neural network, comprising: constructing a weighted directed graph, establishing an objective function with the minimum construction cost as the target; using a layered solving strategy of Benders decomposition to iteratively solve the main problem and the sub-problem; using a graph neural network acceleration module to learn the topological structure and solving result of the sub-problem, obtaining a photovoltaic power station layout candidate scheme; verifying the optimality and feasibility of the photovoltaic power station layout candidate scheme, and performing local correction when the verification fails, and outputting the photovoltaic power station layout optimization scheme after the verification passes. The present application introduces a graph neural network acceleration model in the Benders decomposition framework, learns and predicts the topological structure and solving law of the sub-problem, realizes the rapid generation of the approximate cut plane and the initial solution guidance of the main problem, thereby significantly improving the solving efficiency while maintaining the accuracy of the optimal solution.

The present application relates to the technical field of power grid geographic information, and particularly relates to a GIS-based power grid icing monitoring station site optimization method.The present application discloses a GIS-based power grid icing monitoring station site optimization method, which utilizes GIS spatial analysis technology to identify the transmission line tower sites in the measured power grid region that should be subjected to icing monitoring, optimizes the existing icing monitoring terminal site distribution, calculates the optimal tower sites of the proposed newly added icing monitoring points, realizes the transmission line icing prone section identification and the newly added optimal icing monitoring station site selection design in the measured power grid region, improves the icing monitoring efficiency of the transmission line and potential channels, and solves the redundancy and waste problems of the monitoring device site distribution and site selection.

This invention relates to artificial intelligence technology and discloses a method, apparatus, device, and storage medium for selecting charging pile sites. The method includes: based on charging data of electric vehicles within a target area, statistically analyzing the set of vehicles with the highest charging demand and constructing a distribution map of the largest charging vehicles; based on charging records of each charging station, obtaining the user distribution range of each charging station; based on the charging convenience level of users in each region under the combined influence of different charging stations, constructing a user charging convenience map, and obtaining a charging difficulty map based on a preset threshold; obtaining the central area of ​​the charging difficulty map through clustering, acquiring the set of human geographical environment types in the central area, using a pre-constructed charging area scale prediction model for prediction, and selecting the location corresponding to the smallest environmental type as the charging pile site selection area. This invention can improve the effectiveness of charging pile site selection and increase the coordination between charging pile site selection and scale.

This invention discloses a method for joint optimization of base station site selection and antenna parameters, comprising: Step 1, acquiring data of the target area and performing three-dimensional raster modeling to obtain a set of candidate sites; Step 2, calculating the received power of the reference signal received by the raster from the antenna site to ensure that the power meets the standard and that the raster effectively covers the antenna main lobe directivity requirements; Step 3, defining core performance indicators to comprehensively evaluate the antenna deployment scheme; Step 4, treating each candidate site as an intelligent agent, and based on a global-local hybrid reward mechanism, obtaining a globally approximately optimal deployment scheme through autonomous interaction and collaborative learning between the intelligent agent and the environment; Step 5, based on the trained model, inputting cell parameters and outputting the optimal base station site selection and antenna parameter setting scheme.

Title: Location Planning with Periodicity Consideration. A planning method implemented by a vehicle UWB system is proposed. The UWB system has stored a plurality of portable identifiers. Each portable identifier is configured to perform periodic UWB location sessions with the UWB system at a respective periodicity. The method includes a reception S10, for each portable identifier, of a respective programmed UWB location. The method includes a detection S20 of an overlay of UWB locations programmed with at least two portable identifiers. The method includes a determination S30 of a priority identifier. The priority identifier determined is the one with the longest periodicity. The method includes a deprogramming S40 of each UWB location included in the overlay other than the UWB location with the portable identifier determined as priority.The process offers improved utilization of the vehicle's UWB system. [Fig. 2].

This invention discloses a comprehensive evaluation platform for railway line schemes based on a large model, relating to the field of railway line planning technology. The invention includes a survey and design data collaboration module, a dual-model evaluation core module, a model output optimization module, and a database. The survey and design data collaboration module collects relevant data from various survey areas and constructs an evaluation system. The dual-model evaluation core module assesses the flood control and frost prevention effects of the survey areas based on summer precipitation and winter low-temperature conditions, obtaining scores. The model output optimization module combines the comprehensive evaluation score with the flood control and frost prevention scores to generate and screen candidate railway line schemes. This invention improves the accuracy of environmental assessment, data collaboration, and the scientific nature of scheme optimization in railway line evaluation. It deeply integrates environmental assessment of survey areas with railway line scheme optimization, enhancing the scientific nature, safety, and feasibility of railway line site selection, and reducing subsequent operation and maintenance costs.

This invention discloses a method for site selection evaluation of compressed air energy storage based on multi-source data analysis, belonging to the field of site selection evaluation technology. The method includes: extracting connectivity evidence connected to candidate gas storage caverns based on a minimum closed chain of evidence; converting continuously connected evidence into leakage channel nodes and node connections; blocking conduction interrupted by intact surrounding rock and low-permeability barriers to obtain an underground leakage channel connectivity map; performing path tracing on the underground leakage channel connectivity map; identifying blocking markers in the paths; stopping the extension of paths terminated due to blocking and excluding these paths; and locking high-risk paths that can continuously connect from the candidate gas storage cavern to the external leakage boundary to obtain a risk chain for candidate site selection. This invention improves the stability of candidate gas storage cavern access judgment and the accuracy of sealing risk identification.

This application provides a planning method for a resource-saving, low-carbon data industrial park, relating to the fields of renewable energy and energy conservation technology. The method includes: acquiring a set of environmental parameters for a target area and processing the set of environmental parameters; constructing a regional resource assessment model based on the processed environmental parameter set to integrate multiple energy potential parameters and their interactions, thereby outputting dynamic resource assessment results; constructing a site selection planning evaluation system based on the resource assessment results and pre-set park construction demand constraints; and optimizing the indicator weights in the site selection planning evaluation system through a dynamic weight adjustment mechanism, according to the temporal variation pattern of the interactions, to generate an optimized site selection planning scheme.