100 results about "Regional planning" patented technology

The embodiment of the invention discloses a landslide disaster evolution analysis method and system based on a coupling model, and the method comprises the steps: carrying out the multi-source data integration of geological structure monitoring data, landform distribution data and hydrological environment monitoring data of a target seismic region, and generating a comprehensive monitoring data set; based on the data set, establishing an interaction association relationship of the target equation set, and constructing a geology-landform-hydrology coupling model; performing dynamic simulation and quantitative evaluation on the instability probability and the landslide scale of the potential landslide mass by using the coupling model according to a preset scene parameter combination, and generating an image-text annotation quantitative evaluation report; and finally, carrying out vulnerability analysis and risk assessment on the disaster-bearing body based on the report, generating a comprehensive guidance report containing a disaster-bearing body vulnerability spatial distribution diagram, landslide risk prevention and control measure suggestions and a regional space planning optimization scheme, and providing a scientific basis for landslide disaster prevention and control and regional planning.

The present invention relates to the field of store location recommendation, and discloses a store location recommendation method integrating multi-dimensional features, which includes the following steps: S10. Collect multi-dimensional data of the area where the candidate store location is located, and the multi-dimensional data includes: pedestrian flow, number of competing products, price, industry market size growth rate, regional planning trend, and consumer population change trend; S20. Preprocess the multi-dimensional data, including data cleaning and normalization processing; S30. Input the preprocessed multi-dimensional data into the store location recommendation model to obtain the recommendation value of each candidate store location; S40. After arranging the recommendation values of each candidate store location in descending order, obtain the store location recommendation sequence. The multi-dimensional data of the present invention is used for store location recommendation and fully considers various key factors affecting store operation, more comprehensively depicts the business environment of the candidate area, and thus can provide more accurate store location recommendations for stores, effectively improving the accuracy of location selection.

A position point planning method, comprising: displaying an electronic map on a user interaction interface, the electronic map comprising a region to be operated for a movable platform (S101); synchronously displaying an auxiliary planning identifier on the electronic map along with a cursor, wherein the auxiliary planning identifier synchronously moves in response to the movement of the cursor, and the auxiliary planning identifier is used for providing a user with an indication of whether there is an abnormal factor that is not suitable for planning position points within a preset range with reference to the cursor (S102); and, after step S102 has been executed, in response to an input operation of the user, generating and marking a position point at the position currently indicated by the cursor (S103). The method can improve the rationality of position point planning.

This invention discloses a method for planning U-turns of automated vehicles in narrow passages in mines, comprising: S1, determining the starting area for U-turn planning; S2, performing tunnel area planning to generate interval navigation paths and local paths; S3, performing chamber area planning: the automated vehicle travels to the starting area for U-turn planning based on the tunnel area planning results, establishes a discrete map of the chamber planning area and sets a step size Sn, expands nodes until the target point is reached, and generates a collision-free path; S4, post-processing the collision-free path generated in step S3: a nonlinear optimization planning problem is modeled using a constructed objective function for the discrete points of the collision-free path, and a corresponding solver is used to obtain the final smooth path solution. This method can quickly and effectively complete U-turn trajectory planning in narrow areas using the chamber space, achieving relatively coherent U-turn actions, ensuring the real-time performance of the planning algorithm, and improving vehicle traffic efficiency.

An orchard picking robot path planning algorithm comprises the following steps: (1) constructing a two-dimensional grid map according to an orchard top view or a planning map; (2) classifying obstacle areas and customizing a picking sequence; (3) acquiring a peripheral angular point coordinate set of the picking area; (4) determining a connection point set of adjacent regions; (5) performing regional path planning by using an improved A * algorithm and integrating a preliminary path; (6) optimizing the path through an arc fitting smoothing method; and (7) drawing a final path. According to the method, a complex orchard environment can be effectively modeled and analyzed, regional planning and integration are carried out by means of the improved A * algorithm, and complex conditions of numerous obstacles, irregular layout and the like in an orchard can be handled. And an arc fitting smoothing method in path optimization processing further improves the performability and smoothness of the path in a complex environment. The method can adapt to a complex orchard environment, and provides efficient and safe path planning for the picking robot.

The invention provides a case reasoning method based on machine learning and related equipment. The method comprises the following steps: acquiring a target area planning case and a historical area planning case library; calculating a local similarity between the target area planning case and each historical area planning case in a historical area planning case library to obtain a scene factor similarity for pairing the plurality of historical area planning cases in pairs to generate a plurality of training samples, and training based on the training samples and machine learning to obtain a scene factor weight; based on the scene factor weight and the scene factor similarity, obtaining the global similarity between the target area planning case and each historical area planning case, and extracting the solution of the historical area planning case with the highest global similarity as the solution of the target area planning case; and storing the target area planning case and the solution of the target area planning case in a historical area planning case library to improve the accuracy and efficiency of case reasoning.

A method and system for safe maintenance of an underground pipeline corridor based on a smart gas regulatory IoT. The method is executed by a gas company management platform of a system for safe maintenance of the underground pipeline corridor based on the smart gas regulatory IoT, and the method includes: determining, based on a safety factor of an inspection region, a mandatory machine inspection region; generating regional planning data based on the mandatory machine inspection region, and the region inspection type of the remaining region; determining a target pipeline corridor region and an inspection instruction based on the regional planning data; determining, based on the safety factor and / or a regional importance degree of the inspection region, a monitoring frequency of an environmental monitoring device and a supervisory equipment in the inspection region, and adjusting the monitoring frequency based on a corresponding control instruction.

The invention relates to the technical field of edge calculation optimization, and discloses an edge calculation optimization method, system, equipment and medium based on multi-station fusion, and the method comprises the steps: obtaining and preprocessing the first data of a charging facility of an electric vehicle in a target region, constructing a first local state evaluation model, and constructing a second global situation awareness model, and the operation situation of the station is grasped to support regional planning. And according to the second model, the power grid time-of-use electricity price and renewable energy output prediction data, a third multi-target resource optimization model is constructed, multi-factor optimization resource configuration is considered, and a win-win situation of economic and environmental benefits is realized. And constructing a fourth distributed collaborative decision-making model based on the third model, and improving decision-making efficiency and accuracy in combination with edge calculation characteristics. And calling a fourth model through an upper-layer coordination function to generate an optimal strategy, and executing a lower-layer control function to realize seamless connection of decision execution. The steps are progressive layer by layer to form a complete optimization system, efficiency and stability are improved, cost is reduced, and global resources are reasonably utilized.

The invention relates to a new energy development regional planning method based on a digital twinborn technology. The method comprises the following steps: collecting regional multi-source data, and constructing a regional information model based on the digital twinborn technology; collecting regional power grid data and constructing a new energy development capability capacity constraint based on the regional power grid data; forest data of a surrounding area of the area is collected and superposed with three-area three-line vector data of the territorial space to generate a new energy development avoidance constraint; after the new energy development avoidance constraint acts on the regional information model, constructing a new energy development region through the constrained regional information model, and performing building available surface evaluation on the constructed new energy development region to obtain an evaluated new energy development region; and setting the equipment capacity in each evaluated new energy development area based on the new energy development capability capacity constraint.

The invention discloses a sky path planning design method and system based on an artificial intelligence algorithm, and relates to the technical field of unmanned aerial vehicles, and the technical scheme is characterized by comprising the following steps: obtaining environment data of a flight area of an unmanned aerial vehicle, and obtaining environment condition data of the flight area according to the environment data; setting a sub-planning area of the unmanned aerial vehicle according to the environmental condition data, and setting a planning parameter and a planning weight corresponding to the sub-planning area; real-time monitoring parameters of the sub-planning areas are collected, and sub-area planning coefficients of the sub-planning areas are obtained according to the real-time monitoring parameters, the planning parameters and the planning weights; performing comparative analysis on the sub-region planning coefficient and a preset planning coefficient threshold to obtain a first high-risk sub-planning region; obtaining a first high-risk area factor corresponding to the first high-risk sub-planning area; and obtaining the influence area factor of the first high-risk area factor according to the area correlation model, so that the unmanned aerial vehicle can actively avoid the path during planning, and is prevented from falling into a high-risk environment.

The invention discloses a robot high-priority subregion grinding and polishing path planning method and system for a complex curved surface. The method comprises the following specific steps: S1, acquiring three-dimensional data of a complex curved surface, and selecting effective processing points; s2, processing effective points based on curved surface information to obtain an area center point, and determining a sub-area by considering the position and the normal distance; s3, defining a priority evaluation function, and arranging the sub-region processing sequence according to the size; s4, performing path planning on the sub-regions, and optimizing the path spacing by adopting a golden section method; and S5, the curved surface redundant material is updated in real time along with polishing, and sub-region and path planning is conducted again till the whole curved surface is polished. A new method is provided for robot grinding of the complex curved surface, real-time updating of the residual allowance of the curved surface material is achieved, subarea planning and path planning are continuously updated, key grinding and polishing are conducted on the key area of the complex curved surface, and the method has important significance on high-quality machining of the robot.

The invention discloses a household robot article searching method and system based on a multi-source pre-built map, and the method comprises the following steps: S1, controlling a household robot to move in a household scene through employing an autonomous synchronous positioning and mapping technology, obtaining environment data obtained by a multi-source sensor carried by the household robot, and storing the environment data in a database; constructing an environment map fusing the ground occupation information and the overlook visual information, wherein the environment map is used as a multi-source pre-established map for subsequent article search; s2, calculating three types of scores of each landmark in the home scene; calculating the comprehensive score of each landmark according to the three types of scores of each landmark, and selecting the first K landmarks with the highest comprehensive score to construct an associated landmark set; and S3, in combination with the multi-source pre-established map and the associated landmark set, constructing a high-low layer collaborative target exploration mechanism, and realizing layer-by-layer reasoning from region planning to action execution. According to the method, the semantic reasoning result is accurately sent to the ground, the actual navigation behavior is driven, and the accuracy of target positioning and the efficiency of path planning are improved.

The application relates to a smart city-based urban planning decision feasibility analysis system, aiming to solve the problems of experience dominance, static solidification, appeal imbalance and technology isolation in traditional urban planning. The system includes four modules: data collection, algorithm processing, decision output and dynamic optimization. The data collection module dynamically collects urban basic space, dynamic monitoring, industry and livelihood data and completes preprocessing; the algorithm processing module realizes spatial structure quantization, resource allocation optimization, planning risk assessment and dynamic feasibility prediction; the decision output module generates a planning scheme containing land use layout, energy configuration and public service facility distribution parameters; the dynamic optimization module updates and threshold triggering mechanism, iteratively adjusts the planning scheme. The system is suitable for new area planning and stock area renovation scenarios, realizes the transformation of planning decision, and improves the scientificity and landing effect of planning decision.

The application relates to the technical field of municipal engineering inspection, and discloses a method and system for unmanned aerial vehicle (UAV) inspection applied to municipal engineering. The method comprises the following steps: determining a first inspection priority of a target municipal management area based on the facility importance degree and spatial dependence relationship of each grid unit of the target municipal management area; in response to a first inspection instruction, controlling different slave groups in a UAV formation to sequentially inspect each grid unit according to the first inspection priority to obtain first municipal inspection data; and in response to a second inspection instruction, controlling the different slave groups in the UAV formation to sequentially conduct secondary inspection on each grid unit according to a pre-set second inspection priority to obtain second municipal inspection data. The application realizes full-process optimization from regional planning to local fine operation, and significantly improves the accuracy and efficiency of municipal engineering inspection.

The invention discloses a regional planning method suitable for xanthoceras sorbifolia bunge planting, which comprises the steps of obtaining various influence factors of xanthoceras sorbifolia bunge planting, the various influence factors including climate, soil, terrain and land utilization types; determining zoning factors and zoning indexes of shiny-leaved yellowhorn planting based on the various influence factors; formulating a zoning factor grid point data set based on the zoning factors and the zoning indexes; based on the zoning factor grid point data set, obtaining refined climate zoning data of shiny-leaved yellowhorn through an agricultural climate zoning method; and processing the refined climate division data to obtain a refined shiny-leaved yellowhorn planting area planning map. According to the method, various factors influencing shiny-leaved yellowhorn planting and growth such as meteorological factors, terrain factors and land utilization type factors are comprehensively considered, and the precision of shiny-leaved yellowhorn planting area planning is improved.

The invention discloses a power distribution network multi-region wind-solar-storage collaborative planning method and device, electronic equipment and a storage medium. The method comprises the steps of obtaining historical data of each sub-region of a power distribution network to be optimized, hardware parameters of fire-solar-storage equipment and operation and maintenance cost; generating a plurality of typical scenes according to the historical data; according to the operation and maintenance cost and the hardware parameters, constructing a wide-area planning upper-layer model and model related constraints; calculating uncertainty factors of each typical scene according to historical data and hardware parameters of the typical scenes; according to the operation and maintenance cost, the hardware parameters and the uncertainty factors, constructing a plurality of sub-region planning lower-layer models and model related constraints; according to historical data of a typical scene, carrying out collaborative iteration solution on the upper layer model and the lower layer model to generate an optimal solution of the model; and according to the optimal solution of the model, power distribution network wind-solar-storage collaborative planning is carried out. By implementing the invention, the configuration scheme of renewable energy sources and stored energy can be optimized, and the overall operation cost is reduced.

The invention discloses a land value evaluation method and device based on a deep convolutional neural network, and the method comprises the steps: building a land value evaluation index system of a target region, building a network analytic hierarchy model, carrying out the sensitivity analysis of the land value evaluation index system, obtaining an impact factor weight matrix corresponding to the land value evaluation index system, and obtaining an impact factor weight matrix; and taking the influence factor weight matrix corresponding to the historical land value index evaluation index system of the target area as an input parameter, taking the historical land value index of the target area as an output parameter, and training the deep convolutional neural network to obtain a land value evaluation model. And obtaining an influence factor weight matrix corresponding to the land value evaluation index system of the target area planning, and evaluating the land value index of the target area planning based on the land value evaluation model. The method is suitable for the situation that the house price and land price samples are few, the correlation between the land value and the evaluation index can be accurately and adaptively constructed, and the land value is updated.

The application discloses a district distributed energy system (DDES) station-network collaborative optimization technology considering load point access order. According to regional planning data of the research object, the energy distance method is combined with the K-means clustering method to solve the site selection and scale of the energy station. A pipe planning algorithm based on the shortest path method (DA) and the genetic algorithm (GA) is adopted to solve the simultaneous optimization problem of pipe layout and pipe diameter. On this basis, the coupling of the energy station and the pipe network is analyzed, and an energy station equipment capacity configuration optimization model is established, taking the annualized construction cost and operation cost of the equipment as the target, and establishing mathematical models of the internal combustion engine, the auxiliary boiler, the electric refrigerator unit and the absorption refrigerator unit. The equipment capacity configuration of the energy station is obtained by solving the mixed integer linear programming problem, realizing the DDES station-network collaborative optimization design, and improving the economy and technology of the system.

The invention relates to the technical field of regional planning, in particular to a regional planning method based on grid calculation and multi-objective optimization. According to the method, the target area is recursively divided into the multi-level grid units, the unique space-time identifier is allocated, the static attribute data and the dynamic attribute data are stored, and data are provided for planning of the target area. Taking the processed dynamic attribute data and the processed static attribute data as full-amount input data, and inputting the full-amount input data into a multi-objective optimization model consisting of an economic benefit objective function, an ecological bearing capacity objective function, a traffic capacity objective function and a social satisfaction objective function; and carrying out optimization solution on the multi-objective optimization model by adopting an improved multi-objective optimization algorithm, and outputting a planning scheme of all grid units, thereby realizing accurate planning on target areas such as ports, cities, bases and the like.

The invention discloses a tobacco selling license reasonable layout management method based on data analysis, and the method comprises the steps: carrying out the grid division of a jurisdiction area, and obtaining basic information; calculating a retail point relative stable value of each grid; carrying out regional attribute division and dynamic adjustment according to the relative stable value; and performing personalized regional planning according to regional characteristics. The retail point number of each region can be scientifically determined, resource waste and market oversaturation are avoided, and the supervision efficiency is improved.

The invention relates to the technical field of container scheduling, and particularly discloses a scheduling system and method for container transfer between a port and a station. Comprising a transfer area planning module, a transfer area intelligent capacity expansion module, a visual identification perception module, a resource dynamic calculation module, a vehicle transfer scheduling system, a TOS port operation system and a TCS port cloud control scheduling system. The method has the beneficial effects that by arranging a transfer area in a port for container exchange of inner and outer container trucks and reasonably planning the movement route and time of the inner and outer container trucks, interference to the inner container trucks and other operation equipment in the port area during movement of the outer container trucks can be reduced, and the safety of personnel and equipment in port area operation is guaranteed; the operation efficiency of port dispatching operation is improved; the operation process of inner and outer container trucks is reasonably planned, the activity time of the outer container trucks in a harbor area is shortened, the secondary mobility of containers is reduced, and time and energy are saved.

The application relates to the technical field of downhole electronic fences, and particularly discloses a downhole electronic fence system based on UWB accurate personnel positioning, which comprises a data acquisition module: a modeling unit is used to acquire three-dimensional information of a coal mine underground, and a three-dimensional map is established; a regional planning unit is used to mark a predicted dangerous area in a work cycle on the map; a site selection module is used to extract an edge line of the dangerous area, generate a quasi-square area and an external graph, determine a center position of the external graph, and set an infrared emission point which can rotate by 360 degrees at the center; a fence planning module is used to update the edge line of the dangerous area in real time; a target emission point is determined according to the real-time edge line, an emission angle range is adjusted, infrared rays scan the boundary of the dangerous area back and forth at a preset speed, and UWB technology is used to monitor whether personnel enter the dangerous area and trigger a warning; the system dynamically delimits the dangerous area and gives real-time warnings, and personnel safety is ensured.

The embodiments of the present disclosure provide a method for a shared bicycle delivery and an operation area planning in a smart city and an Internet of Things (IoT) system thereof. The method may be implemented based on a management platform of the Internet of Things (IoT) system. The method includes: obtaining reference information of people flow in at least one target area, determining a predicted people flow in the at least one target area at a target time, and determining a demand quantity for shared bicycles; obtaining historical data of shared bicycles in a plurality of reference areas, and predicting a variation quantity of shared bicycles in the at least one target area at the target time; and determining a delivery quantity of shared bicycles in the at least one target area at the target time.

The invention discloses a construction project digital design method and system based on data collaboration, and relates to the technical field of engineering construction information, and the method comprises the steps: obtaining project demand information and construction area environment information, and obtaining construction area geographic information and construction area climate information based on the construction area environment information. According to the method, the construction influence meteorology of the construction area is screened, so that accurate evaluation on the influence of the construction meteorology is ensured, the construction condition of the construction area is accurately analyzed through the engineering construction difficulty coefficient, whether the construction area meets the project design task or not is judged through the construction engineering construction index, waste of resources is avoided, and the construction efficiency is improved. By taking the building area planning with the maximum building area planning priority index as the optimal scheme of the building area planning, the construction engineering design efficiency is improved, the building structure is accurately analyzed through the building foundation quality index, and the stability and reliability of the building are ensured.

The invention relates to the technical field of carbon capture, utilization and storage in industrial data processing, and discloses a regional CCUS planning method and system under carbon flow real-time monitoring. According to the method, high-priority monitoring points are scientifically screened through K-means clustering, and the problem of unreasonable layout of monitoring points in a wide region is solved; through space-time cooperative calibration, time sequence completion and efficient network structure construction, efficient transmission and integration of multi-source carbon flow data are realized, and the data acquisition accuracy is improved; and predicting a carbon flow trend and positioning a potential risk area based on a long-short-term memory network model, optimizing a planning path in combination with a genetic algorithm, generating a precise planning adjustment instruction, and finally implementing the optimization path. According to the method, the core technical problems of unscientific layout of monitoring points in a wide area, low data transmission integration efficiency and insufficient planning optimization accuracy are solved in a targeted manner, closed-loop optimization of carbon flow dynamic monitoring and CCUS planning is realized, and technical support is provided for improving the regional carbon management level and guaranteeing efficient implementation of a carbon capture utilization and storage process.

The present invention belongs to the technical field of drone path planning. Specifically, it is a drone patrol path planning method based on an improved grid method. In order to overcome the defects of the traditional grid method in that the single information is not in line with reality and the local optimum of the deterministic algorithm, and to solve the problems of complex and time-varying environmental information, emergency response to sudden situations, periodic patrol coverage, and hidden danger elimination and tracking, the present invention optimizes the existing grid modeling method to construct a drone safety risk zoning map, a key area level zoning map, and a drone navigation speed and detection distance zoning map, and generates a patrol area environmental information and speed distribution zoning map. The mission control center makes tactical choices, combines static planning with dynamic planning, and combines regional planning with speed planning, thereby meeting the constraints and completing the path optimization task. The present invention has engineering practicality in both the civilian and military fields of drone planning and helps improve the efficiency of mission execution.

The present invention relates to the field of navigation technology, and specifically provides a method and system for autonomous navigation of a quadruped robot for special environments, including: using the recognition result of the depth image by the target detection network to generate semantic tags for the depth point cloud data corresponding to the depth image; using the laser radar mileage calculation method to calculate local odometer information according to the laser point cloud data and the inertial sensor data; fusing the depth point cloud data with semantic tags, the laser point cloud data and the local odometer information to obtain the positioning data in the pre-built point cloud map; using the perception method of the regional planner to build a multi-layer cost map according to the pre-built point cloud map, the latest acquired depth image, the laser point cloud data and the inertial sensor data; using the global planning path algorithm and the local path planning algorithm to generate navigation path information according to the positioning data and the multi-layer cost map. The present invention improves the navigation accuracy.

The invention belongs to the technical field of building planning management, and particularly relates to a building area route planning system applied to building planning design, which comprises a geographic information integration module, a function demand analysis module, a people flow prediction module, a route intelligent generation module, a multi-scheme evaluation optimization module and a result visualization display module. According to the invention, various building area route planning schemes are intelligently generated through the route intelligent generation module according to geographic information, function requirements and people flow prediction information, the various schemes are evaluated to select an optimal scheme, and the optimal route planning scheme is visually displayed. According to the method, key factors in multiple aspects of building area planning can be comprehensively considered, and based on tight cooperation and data interaction of all modules, the whole process of route planning from basic data collection to final scheme display is scientific, intelligent and visual, and the quality and level of building area route planning are remarkably improved; and the working difficulty of planning and designing personnel can be reduced.

The application provides a non-working air conditioner multi-connected intelligent regulation and control system and method based on Internet of Things technology. The method comprises the following steps: obtaining a regional top view, determining a first extension edge and a second extension edge; obtaining the demand attributes of each demand end; dividing each demand end corresponding to the same fixed temperature interval into the same temperature demand group, and arranging in sequence; determining the original terminal proportion of each temperature demand group, splitting the demand sequence to obtain a first sub-sequence and a second sub-sequence; updating the proportion of each temperature demand group located in the same sub-sequence, distributing the first sub-sequence and the second sub-sequence based on the current terminal proportion to the first extension edge and the second extension edge to obtain a first fixed value region sequence and a second fixed value region sequence; determining the allocation region located between the first fixed value region sequence and the second fixed value region sequence, and distributing each demand end with an allocation attribute to the allocation region. The application at least improves the regional planning efficiency.

The invention discloses a natural gas yield zoning planning method based on a GIS (Geographic Information System) technology, and belongs to the technical field of gas reservoir yield area planning. The natural gas yield zoning planning method comprises the following steps: step A, analyzing gas reservoir zoning peak yield; step B, partition yield calculation under multi-factor control; and C, researching the yield planning model under the constraint of the three-dimensional Gaussian mixture model. In order to carry out yield planning and risk analysis on different natural gas areas, it is necessary to carry out natural gas yield partition planning research based on the GIS technology, and the yield peak value distribution situation of all the areas and the influence situation of risk factors are analyzed. Therefore, fuzzy analysis and a multivariate Gaussian mixture model are applied, the peak yield range and the implementation probability of each production area are calculated, a yield peak distribution model diagram is generated, finally, a three-dimensional digital elevation model is established based on the GIS technology, a three-dimensional yield distribution diagram under geographic coordinates is obtained, and guidance is provided for planning and development work of a gas field.