Community layout planning method and electronic equipment

Abstract

The invention discloses a community layout planning method and electronic equipment, and the method comprises the steps: sequentially carrying out the iteration updating of a community layout scheme, inputting a community layout design model, obtaining a first evaluation result corresponding to a first evaluation index, and carrying out the iteration of a target number of iterations; taking a community layout scheme corresponding to the first evaluation result meeting the first target condition as a first target community layout scheme, and determining a plurality of community spatial form simulation results corresponding to the first target community layout scheme; obtaining a second evaluation result corresponding to each second evaluation index according to the plurality of community spatial form simulation results and the plurality of second evaluation indexes; and determining a second target community layout scheme according to the plurality of obtained second evaluation results and the corresponding community spatial form simulation results. Therefore, a community layout scheme with more reasonable functional area layout can be obtained, so that the traffic efficiency is effectively improved, the carbon emission is reduced, and the life convenience of users is improved.

Description

Technical Field

[0001] The present application relates to the technical field of community layout planning, and in particular to a community layout planning method and electronic equipment. Background Art

[0002] Community layout refers to the distribution characteristics of production and living space within a community and their mutual relationships. It mainly includes the distribution of functional areas such as user points, commercial areas, leisure and entertainment areas, educational venues, green plants, public places, as well as the traffic planning of the road network.

[0003] With the development of computer technology, community layout planning can now be achieved through computer technology based on Geographic Information Systems (GIS). However, this technology is mostly limited to displaying basic geographic data and simple spatial analysis. In addition, due to the increasingly serious problem of global climate change, the construction of low-carbon communities has become a key direction for sustainable urban development.

[0004] Most existing community layout planning methods rely on empirical formulas or single-index models, focusing on land utilization and living comfort. Community layouts determined by these methods often have overly simplistic functional zones, such as designating one portion of the community's land as a single commercial street and another portion as a single high-rise residential area. This results in poorly rationalized functional zone layouts. This can lead to longer daily commutes, repeated trips, isolation of ecological patches within the community, and damage to biodiversity. This in turn leads to low traffic efficiency, increased carbon emissions from transportation, and reduced convenience for users. Summary of the Invention

[0005] The present application provides a community layout planning method and electronic equipment, which are used to solve the community layout planning methods existing in the prior art. Since the community layout planning methods rely on empirical formulas or single indicator models, the functional area settings of the determined community layout are often too single, resulting in poor rationality of the functional area layout, low traffic efficiency, increased traffic carbon emissions, and affecting the convenience of users' lives.

[0006] In order to solve the above technical problems, in the first aspect, the implementation method of the present application discloses a community layout planning method, which includes: inputting the initial community layout plan into the community layout design model for corresponding processing to obtain a first evaluation result corresponding to the first evaluation index, the community layout plan includes the layout information of each functional area included in the community, and the first evaluation index includes the total carbon emissions, the average travel distance of users and the land utilization rate; adjusting the layout information of each functional area included in the initial community layout plan to update the community layout plan to obtain an updated community layout plan, inputting the updated community layout plan into the community layout design model for corresponding processing to obtain a first evaluation result corresponding to the first evaluation index, and Iterate the community layout plan and generate the first evaluation result corresponding to the updated community layout plan until the target number of iterations is reached; the community layout plan corresponding to the first evaluation result that meets the first target condition among the multiple first evaluation results obtained is used as the first target community layout plan; determine the multiple community space form simulation results corresponding to the first target community layout plan according to the functional types of the adjacent functional areas corresponding to each functional area and the traffic accessibility between the functional areas; obtain the second evaluation results corresponding to each second evaluation indicator based on the multiple community space form simulation results and the multiple second evaluation indicators; determine the second target community layout plan based on the multiple second evaluation results and the corresponding community space form simulation results.

[0007] Using the above technical solution, the initial community layout plan is input into the community layout design model for corresponding processing to obtain a first evaluation result corresponding to the first evaluation index including total carbon emissions, average user travel distance and land utilization rate. Then, the community layout plan corresponding to the first evaluation result that meets the first target condition among the multiple first evaluation results is used as the first target community layout plan. According to the functional types of adjacent functional areas corresponding to each functional area and the traffic accessibility between the functional areas, the multiple community space form simulation results corresponding to the first target community layout plan are determined; according to the multiple community space form simulation results and the multiple second evaluation indicators, the second evaluation results corresponding to each second evaluation indicator are obtained; according to the multiple second evaluation results and the corresponding community space form simulation results, the second target community layout plan is determined. Therefore, the first evaluation results corresponding to the total carbon emissions, the average travel distance of users and the land utilization rate are determined through the community layout design model, and then the second evaluation result is obtained based on the first target community layout plan corresponding to the first evaluation result that meets the first target condition and multiple second evaluation indicators; based on the multiple second evaluation results obtained and the corresponding community space form simulation results, the second target community layout plan is determined, which can accurately quantitatively evaluate the designed community layout plan, thereby making the layout information of each functional area in the community layout plan more reasonable, and obtaining the second target community layout plan with more reasonable layout information of the functional areas, that is, obtaining a community layout result with more reasonable layout information of the functional areas, so that after the actual application of the second target community layout plan, it can effectively shorten the average travel distance of users, reduce traffic carbon emissions and community building operation carbon emissions, significantly improve the low-carbon performance of the community, and improve the living comfort of users.

[0008] According to another specific implementation method of the present application, the implementation method of the present application discloses a community layout planning method, in which the second evaluation result is an evaluation score corresponding to the second evaluation indicator, and the second target community layout plan is determined based on the multiple second evaluation results obtained and the corresponding community space form simulation results, including: determining the second target community layout plan based on the community space form simulation result corresponding to the highest evaluation score among the multiple evaluation scores.

[0009] The adoption of the above technical solution can make the layout information of each functional area in the second target community layout plan more reasonable, further improving the low-carbon performance of the community and the living comfort of users.

[0010] According to another specific implementation method of the present application, the implementation method of the present application discloses a community layout planning method, the community layout design model includes a community carbon emission calculation module, the layout information includes building layout information and traffic layout information, the community layout plan is input into the community layout design model for corresponding processing, and a first evaluation result corresponding to the first evaluation indicator is obtained, including: inputting the building layout information and traffic layout information into the community carbon emission calculation module to obtain the total carbon emissions, and the total carbon emissions include building operation carbon emissions and transportation travel carbon emissions.

[0011] By adopting the above technical solution, a more accurate total carbon emissions can be obtained, thereby increasing the accuracy of the first evaluation result.

[0012] According to another specific implementation of the present application, the implementation of the present application discloses a community layout planning method, which includes determining the total carbon emissions by the following formula:

[0013] C total =C b +C t

[0014]

[0015] Among them, C total is the total carbon emissions, C b is the carbon emissions from building operation, C t is the carbon emissions from transportation, E i is the annual energy consumption of different buildings, EF i is the carbon emission factor of different buildings, D j is the annual travel distance of different transportation modes, M j is the number of users using the transportation mode, EF j is the carbon emission factor of transportation mode.

[0016] According to another specific implementation of the present application, the implementation of the present application discloses a community layout planning method, which determines the initial community layout plan in the following way: obtaining initial community data, the initial community data including terrain data of the existing community, building distribution geographical data, energy consumption data and traffic data; preprocessing the initial community data to obtain a target database, the target database including community road network data; obtaining a road integration heat map based on the community road network data and a preset road integration algorithm; and determining the initial community layout plan based on the road integration heat map.

[0017] By adopting the above technical solution, the road integration heat map obtained based on the initial community including the terrain data of the existing community, the geographical data of building distribution, the energy consumption data and the traffic data can provide a spatial structure basis for the community layout, making the layout information included in the initial community layout plan more reasonable.

[0018] According to another specific implementation of the present application, the implementation of the present application discloses a community layout planning method, wherein the road integration heat map includes multiple road segment integrations, and the method includes determining the road segment integration using the following formula:

[0019]

[0020] Among them, Integration i is the integration degree of the road section, i is the target road section node, j and k are other road section nodes, is the topological distance between nodes i and j, is the topological distance between nodes j and k.

[0021] According to another specific implementation method of the present application, the implementation method of the present application discloses a community layout planning method, which also includes: determining the ecological corridor network based on the green space information, water body information, terrain slope information and vegetation coverage information included in the second target community layout plan, so that the minimum cumulative resistance value between adjacent ecological patches included in the ecological corridor network is less than or equal to the resistance value threshold.

[0022] By adopting the above technical solution and setting an ecological corridor network with a minimum cumulative resistance threshold, and through cost path analysis, the planned ecological corridor network can effectively connect various ecological patches, increase the ecological connectivity index, improve the ecological connectivity of the community, and significantly improve the ecological environment and living comfort.

[0023] According to another specific implementation of the present application, the implementation of the present application discloses a community layout planning method, which also includes: adjusting the building spacing and height included in the second target community layout plan based on the temperature and wind speed distribution on a typical summer day to obtain an updated second target community layout plan.

[0024] By adopting the above technical solution and adjusting the building spacing and height ratio through microclimate simulation, the proportion of high-temperature areas in the community can be reduced, reflecting the synergistic effect of ecological network construction and building layout optimization, and significantly improving the ecological environment and living comfort.

[0025] According to another specific implementation method of the present application, the implementation method of the present application discloses a community layout planning method, in which the layout information also includes traffic layout information. The method also includes: determining the traffic flow prediction result corresponding to the second target community layout plan; and adjusting the traffic layout information included in the second target community layout plan based on the traffic flow prediction result to obtain an updated second target community layout plan.

[0026] The adoption of the above technical solutions can greatly improve the convenience of users' lives and enhance their living comfort.

[0027] On the second aspect, the implementation method of the present application also discloses a community layout planning device, including: a first processing module, used to input the initial community layout plan into the community layout design model for corresponding processing, and obtain a first evaluation result corresponding to a first evaluation index, the community layout plan includes the layout information of each functional area included in the community, and the first evaluation index includes the total carbon emissions, the average travel distance of users, and the land utilization rate; the first processing module is used to adjust the layout information of each functional area included in the initial community layout plan to update the community layout plan, obtain an updated community layout plan, input the updated community layout plan into the community layout design model for corresponding processing, obtain a first evaluation result corresponding to the first evaluation index, and iteratively update the community layout plan and generate The first evaluation result corresponding to the updated community layout plan is repeated until the target number of iterations is reached; a third processing module is used to take the community layout plan corresponding to the first evaluation result that meets the first target condition among the multiple first evaluation results obtained as the first target community layout plan; a fourth processing module is used to determine the multiple community space form simulation results corresponding to the first target community layout plan according to the functional types of the adjacent functional areas corresponding to each functional area and the traffic accessibility between the functional areas; a fifth processing module is used to obtain the second evaluation results corresponding to each second evaluation indicator based on the multiple community space form simulation results and the multiple second evaluation indicators; a sixth processing module is used to determine the second target community layout plan based on the multiple second evaluation results obtained and the corresponding community space form simulation results.

[0028] In the third aspect, the implementation method of the present application also discloses an electronic device, including: a processor, and a memory communicatively connected to the processor; the memory stores a computer program; the processor executes the computer program stored in the memory, so that the electronic device implements the community layout planning method provided by any implementation method of the first aspect above.

[0029] In a fourth aspect, the implementation method of the present application provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, it is used to implement the community layout planning method provided by any implementation method of the first aspect mentioned above.

[0030] In a fifth aspect, the implementation of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the community layout planning method provided by any one of the implementations of the first aspect above.

[0031] It can be understood that the beneficial effects of the second to fifth aspects mentioned above can also be found in the relevant description of the first aspect mentioned above, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 This is a flow chart of a community layout planning method provided by an embodiment of the present application;

[0033] Figure 2 This is a flow chart of determining an initial community layout plan provided by an embodiment of the present application;

[0034] Figure 3 This is another flowchart of the community layout planning method provided in the embodiment of the present application;

[0035] Figure 4 This is a schematic diagram of the changes in the functional area before and after the optimization of the community functional layout provided in the embodiment of the present application;

[0036] Figure 5 This is a schematic diagram of the changes in the proportion of carbon emissions from travel modes before and after the optimization of community functional layout provided in an embodiment of the present application;

[0037] Figure 6 This is a structural diagram of a community layout planning device provided in an embodiment of the present application;

[0038] Figure 7 This is a structural diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0039] As mentioned above, in the existing technology, community layout planning methods rely on empirical formulas or single indicator models, so the community layout determined is often too simple in the functional area settings, and the settings of each functional area are not rational, resulting in low traffic efficiency, increased traffic carbon emissions, and affecting the convenience of users' lives.

[0040] Specifically, traditional community layouts often focus on land use efficiency and living comfort, ignoring the impact of factors such as building energy consumption, transportation, and the ecological environment on carbon emissions. For example, overly sparse functional zoning leads to long commutes, increasing transportation carbon emissions; and illogical public service facility layouts force users to make repeated trips, further exacerbating energy consumption. Furthermore, existing community planning lacks systematic consideration of environmental factors such as microclimate and ecological connectivity, making it difficult to achieve truly low-carbon goals.

[0041] Although GIS technology has been incorporated into some community planning efforts, it's often limited to displaying basic geographic data and performing simple spatial analysis, such as using GIS to map current land use and calculate green space. These applications fail to fully leverage GIS's strengths in spatial simulation, data fusion, and multi-objective optimization, and are unable to comprehensively optimize community layout from multiple perspectives, including carbon emissions, transportation efficiency, and ecological function. For example, when demarcating functional areas, GIS spatial syntax analysis of road network accessibility and user travel patterns is not combined, resulting in high levels of transportation carbon emissions. In ecological planning, the lack of GIS-based ecological network construction has isolated ecological patches within communities, impairing biodiversity.

[0042] Existing low-carbon community layout optimization methods lack systematicity and dynamic adaptability. For example, some studies focus solely on building energy consumption, ignoring other sources of carbon emissions such as transportation and public facilities. Some optimization schemes struggle to balance low-carbon goals with user convenience needs in practical applications. Furthermore, the traditional planning process is relatively independent of each other, making data sharing and interoperability difficult. This leads to a disconnect between optimization schemes and actual construction needs, making it impossible to effectively guide the implementation of low-carbon communities. Therefore, a comprehensive layout optimization method based on GIS spatial analysis is urgently needed to achieve the coordinated improvement of low-carbon goals and community functions.

[0043] Based on this, the present application provides a community layout planning method, which determines the first evaluation results corresponding to the total carbon emissions, the average travel distance of users and the land utilization rate through a community layout design model, and then obtains the second evaluation result based on the first target community layout plan corresponding to the first evaluation result that meets the first target condition and multiple second evaluation indicators; determines the second target community layout plan based on the multiple second evaluation results obtained and the corresponding community space form simulation results, and can accurately perform quantitative evaluation on the designed community layout plan, thereby making the layout information of each functional area in the community layout plan more reasonable, and obtaining the second target community layout plan with more reasonable layout information of the functional areas, so that after the actual application of the second target community layout plan, it can effectively shorten the average travel distance of users, reduce traffic carbon emissions and community building operation carbon emissions, significantly improve the low-carbon performance of the community, and improve the living comfort of users.

[0044] Next, with reference to the accompanying drawings, the steps and advantages of the community layout planning method provided by this application are described in detail.

[0045] like Figure 1 As shown, the community layout planning method provided by this application includes the following steps.

[0046] S100: Inputting the initial community layout plan into the community layout design model for corresponding processing to obtain a first evaluation result corresponding to a first evaluation indicator.

[0047] For example, this application takes a new community covering an area of ​​50 hectares and with a planned population of 12,000 as the community layout planning object.

[0048] Among them, the community layout plan includes the layout information of each functional area included in the community, and the first evaluation indicator includes the total carbon emissions, the average travel distance of users and the land utilization rate.

[0049] S200: Adjust the layout information of each functional area included in the initial community layout plan to update the community layout plan, obtain an updated community layout plan, input the updated community layout plan into the community layout design model for corresponding processing, obtain a first evaluation result corresponding to the first evaluation indicator, and iteratively update the community layout plan and generate the first evaluation result corresponding to the updated community layout plan in sequence until the target number of iterations is reached.

[0050] For example, the community layout plan provided in this application may include layout information for functional areas such as residential, commercial, and public services. The community layout plan may be designed by engineers based on their experience based on community design requirements, or it may be designed by computer software based on community layout requirements input by a user.

[0051] Furthermore, the community layout design model can be an optimization model with the goals of minimizing carbon emissions, minimizing the average travel distance of users, and maximizing land use efficiency. The model is solved using the non-dominated sorting genetic algorithm NSGA-II, with a population size of 80 and an iteration number of 150 (that is, the target iteration number).

[0052] The specific steps involved building a multi-objective optimization model using the Pymoo library in the Python environment. With the goals of minimizing carbon emissions, minimizing average user travel distance, and maximizing land use efficiency, the model was solved using the non-dominated sorting genetic algorithm (NSGA-II). The population size was set at 80, with a crossover probability of 0.8, a mutation probability of 0.1, and 150 iterations. The community land was divided into 12 functional area units. The layout information for each functional area could include high-rise residential buildings (floor area ratio 3.0), neighborhood businesses (building area 2000 m2), and community health service centers (building area 1500 m2).

[0053] In one embodiment of the present application, in the initial plan (i.e., the initial community layout plan), the commercial center was located in the northwest corner of the community, resulting in an average shopping trip distance of 800 meters for users. After iterative algorithm optimization, the commercial center was moved to a highly accessible area on the east side, and convenient commercial outlets were added to each residential cluster, shortening the average trip distance to 300 meters. At the same time, the layout of residential and public service facilities was adjusted, and facilities such as kindergartens and community activity centers were placed within a 5-minute walk. After optimization, the land mixed use index increased from 0.35 to 0.58.

[0054] S300: The community layout plan corresponding to the first evaluation result that meets the first target condition among the multiple first evaluation results obtained is used as the first target community layout plan.

[0055] In one implementation of the present application, the first target condition is that during 150 iterations, the updated community layout plan is input into the community layout design model, and the resulting carbon emissions are minimized, the average user travel distance is shortest, and the land utilization rate (also known as land utilization efficiency) is maximized.

[0056] S400: Determine multiple community space morphology simulation results corresponding to the first target community layout plan based on the functional types of adjacent functional areas corresponding to each functional area and the traffic accessibility between the functional areas.

[0057] For example, the results of space syntax analysis are combined with the cellular automaton CA model to simulate the spatial evolution of the layout of different functional areas, and the cellular transformation rules are set according to the functional types of adjacent plots and traffic accessibility to generate layout plans.

[0058] The specific steps are to write the cellular automation (CA) model code in MATLAB and divide the community into 2500 20m×20m cells. Set the conversion rules:

[0059] ① If the integration degree of the cell's adjacent plots is greater than 0.6 and is unoccupied, the probability of conversion to commercial or public service land is 80%.

[0060] ② If the cell is less than 200 meters away from the ecological source, the probability of conversion to green space is 70%.

[0061] Combining the results of space syntax analysis, we conducted 100 iterative simulations to generate three layout schemes: compact, decentralized, and mixed (i.e., multiple community spatial form simulation results; other types of layout schemes may also be included in other implementations of this application). The compact scheme reduces user travel distances by increasing building density and functional mix; the decentralized scheme focuses on the distribution of ecological space and improves green space accessibility.

[0062] S500: Obtaining second evaluation results corresponding to the second evaluation indicators based on the plurality of community space form simulation results and the plurality of second evaluation indicators.

[0063] In one implementation of the present application, the second evaluation index may include at least one of carbon emission intensity, travel convenience, land mixed use index, ecological connectivity, microclimate comfort, green view rate, user satisfaction, and construction cost.

[0064] The second evaluation index can be obtained by performing simulation calculations based on the initial design intention of the community after obtaining multiple community space form simulation results, presetting some user living parameters and traffic parameters.

[0065] S600: Determine a second target community layout plan based on the obtained multiple second evaluation results and the corresponding community space form simulation results.

[0066] The community layout planning method provided in the present application inputs the initial community layout plan into the community layout design model for corresponding processing to obtain a first evaluation result corresponding to the first evaluation index including total carbon emissions, average user travel distance and land utilization rate, and then takes the community layout plan corresponding to the first evaluation result that meets the first target condition among the multiple first evaluation results obtained as the first target community layout plan, and determines multiple community space form simulation results corresponding to the first target community layout plan according to the functional types of adjacent functional areas corresponding to each functional area and the traffic accessibility between the functional areas; obtains second evaluation results corresponding to each second evaluation index according to the multiple community space form simulation results and the multiple second evaluation indexes; and determines the second target community layout plan according to the multiple second evaluation results obtained and the corresponding community space form simulation results. Therefore, the first evaluation results corresponding to the total carbon emissions, the average travel distance of users and the land utilization rate are determined through the community layout design model, and then the second evaluation result is obtained based on the first target community layout plan corresponding to the first evaluation result that meets the first target condition and multiple second evaluation indicators; based on the multiple second evaluation results obtained and the corresponding community space form simulation results, the second target community layout plan is determined, which can accurately quantitatively evaluate the designed community layout plan, thereby making the layout information of each functional area in the community layout plan more reasonable, and obtaining the second target community layout plan with more reasonable layout information of the functional areas, that is, obtaining a community layout result with more reasonable layout information of the functional areas, so that after the actual application of the second target community layout plan, it can effectively shorten the average travel distance of users, reduce traffic carbon emissions and community building operation carbon emissions, significantly improve the low-carbon performance of the community, and improve the living comfort of users.

[0067] In another implementation of the present application, the second evaluation result is an evaluation score corresponding to the second evaluation indicator. Based on the multiple second evaluation results obtained and the corresponding community space form simulation results, the second target community layout plan is determined, including: determining the second target community layout plan based on the community space form simulation result corresponding to the highest evaluation score among the multiple evaluation scores.

[0068] For example, an evaluation system including carbon emission intensity, travel convenience, and land mixed use index indicators is constructed, and the entropy weight-TOPSIS method is used to calculate the comprehensive score of each scheme (i.e., the simulation results of multiple community spatial morphology).

[0069] Specifically, an evaluation system can be constructed that includes eight indicators: carbon emission intensity, travel convenience, land use mix index, ecological connectivity, microclimate comfort, green view rate, user satisfaction, and construction cost. The entropy weight-TOPSIS method is used to calculate the comprehensive score of each scheme. For example, the following formula can be used for calculation:

[0070]

[0071] Among them, S i is the relative closeness of solution i, are the distances from the solution to the positive and negative ideal solutions, respectively.

[0072] The original data was standardized in Excel, and the entropy weight was calculated using Python to determine the indicator weights (carbon emission intensity 0.25, travel convenience 0.2, land mixed use index 0.15, etc.).

[0073] After calculation, the hybrid solution scored the highest (0.82) among the above solutions and was selected as the final optimization solution.

[0074] In another implementation of the present application, Figure 2 As shown, the method includes determining an initial community layout plan through the following steps:

[0075] S110: Acquire initial community data, which includes terrain data of the existing community, building distribution geographic data, energy consumption data, and traffic data.

[0076] S120: Preprocess the initial community data to obtain a target database, which includes community road network data.

[0077] S130: Obtain a road integration heat map based on the community road network data and a preset road integration algorithm.

[0078] S140: Determine the initial community layout plan based on the road integration heat map.

[0079] Exemplarily, multi-source data collection and preprocessing are first performed (ie, initial community data is obtained).

[0080] Satellite remote sensing and drone aerial surveys are used to obtain geographic data on community topography and building distribution. Energy consumption and carbon emission data are collected through electricity meters and carbon emission monitoring equipment. Data cleaning algorithms are used to remove outliers and the data are uniformly converted into the SHP format supported by GIS.

[0081] Specifically, in one implementation of this application, a DJI M300 RTK drone equipped with a five-lens camera was used to conduct aerial surveys at an altitude of 120 meters and a 75% overlap rate, acquiring 0.05-meter resolution imagery. This imagery, combined with control point data collected by a Trimble R10 GNSS receiver, was used to generate a 3D real-world model in ContextCapture software. Simultaneously, 1:1000 topographic data from the National Basic Geographic Information Database was accessed to obtain elevation and contour information.

[0082] In terms of energy data collection, Schneider EcoStruxure smart electricity meters (accuracy 0.1kWh) and Sensus gas flow meters are installed in 20 residential buildings and 3 commercial buildings, and the data is transmitted in real time to the community energy management platform via the LoRaWAN network.

[0083] Traffic data is obtained by connecting with the traffic management department's API to obtain traffic volume and speed data of the three surrounding main roads.

[0084] The raw data was processed in ArcGIS Pro. Anomalous energy consumption data was removed using the 3σ principle. For example, records where a commercial building's daily electricity consumption exceeded the mean by three standard deviations were marked for deletion. CAD-formatted terrain data was converted to an ESR Shapefile format, and energy consumption data was compiled into a CSV file and imported into a geodatabase. Finally, a comprehensive database (the target database) was constructed, encompassing 28 layers, including building outlines, road networks, energy consumption monitoring points, and traffic flow.

[0085] In one implementation of the present application, in step S130, a road integration heat map is obtained based on the community road network data and a preset road integration algorithm, and the integration of the community road network can be calculated using a GIS space syntax module.

[0086] Specifically, the community road network data (i.e., the aforementioned road network) was imported into the ArcGIS Space Syntax module, with road intersections and endpoints as analysis nodes, and the topological distance calculation rule set as the number of turns. The integration degree of each road segment was calculated using the following formula:

[0087]

[0088] Among them, Integration i is the integration degree of the road section, i is the target road section node, j and k are other road section nodes, is the topological distance between nodes i and j, is the topological distance between nodes j and k.

[0089] Calculations show that the section of the community's east side connecting to the city's main road has an integration index of 0.82, making it a highly accessible area. Meanwhile, the integration index for the west side branch roads is only 0.25, placing it in a low-access area. Based on this, an integration heat map was created to provide a spatial structural basis for functional layout (i.e., community layout design).

[0090] In another implementation of the present application, the community layout design model includes a community carbon emission calculation module, the layout information includes building layout information and traffic layout information, the community layout plan is input into the community layout design model for corresponding processing, and a first evaluation result corresponding to the first evaluation indicator is obtained, including: inputting the building layout information and traffic layout information into the community carbon emission calculation module to obtain the total carbon emissions, and the total carbon emissions include building operation carbon emissions and transportation travel carbon emissions.

[0091] The community carbon emission calculation module can also be constructed using the energy consumption data and traffic data included in the aforementioned target database.

[0092] In another implementation of the present application, carbon emissions are divided into two parts: building operation and transportation.

[0093] That is, in another implementation of the present application, the method includes determining the total carbon emissions by the following formula:

[0094] C total =C b +C t

[0095]

[0096] Among them, C total is the total carbon emissions, C b is the carbon emissions from building operation, C t is the carbon emissions from transportation, E i is the annual energy consumption of different buildings, EF i is the carbon emission factor of different buildings, D j is the annual travel distance of different transportation modes, M j is the number of users using the transportation mode, EF j is the carbon emission factor of transportation mode.

[0097] For example, in one implementation of the present application, the carbon emission factor EF of the building is i The value is 0.617kgCO2 / kWh, the carbon emission factor of private cars is 0.272kgCO2 / km, and the carbon emission factor of public buses is 0.08kgCO2 / km.

[0098] Taking a residential building as an example, the annual electricity consumption is 5 million kWh, then C b =5000000×0.617=3085000kgCO2. The total annual travel distance of community users by private car is 1.2 million kilometers, and the total annual travel distance by public transportation is 600,000 kilometers. Then C t=1200000×0.272+600000×0.08=386400kgCO2. The total annual carbon emissions of the community are C total =3085000+386400=3471400kgCO2.

[0099] In one implementation of the present application, the method also includes: determining an ecological corridor network based on the green space information, water body information, terrain slope information and vegetation coverage information included in the second target community layout plan, so that the minimum cumulative resistance value between adjacent ecological patches included in the ecological corridor network is less than or equal to the resistance value threshold.

[0100] For example, using GIS cost distance analysis tools, with green spaces and water bodies as ecological sources, and taking terrain slope and vegetation coverage factors into consideration, resistance surfaces are set to construct an ecological corridor network, so that the minimum cumulative resistance value between adjacent ecological patches does not exceed the threshold Rmax.

[0101] For example, using two parks within the community as ecological source areas, a resistance surface was constructed in ArcGIS based on terrain slope, vegetation cover, and land use type, with a minimum cumulative resistance threshold of Rmax = 1500. Through cost path analysis, three 15-meter-wide ecological corridors were planned to connect the ecological patches, increasing the ecological connectivity index from 0.42 to 0.57.

[0102] In one implementation of the present application, the method further includes: adjusting the building spacing and height included in the second target community layout plan based on the temperature and wind speed distribution on a typical summer day to obtain an updated second target community layout plan.

[0103] For example, the optimized layout plan (i.e., the second target community layout plan) was imported into the ENVI-met software to simulate the temperature and wind speed distribution on a typical summer day. By adjusting the building spacing and height ratio, the proportion of high-temperature areas in the community was reduced. Specifically, the optimized plan was imported into the ENVI-met software to simulate the temperature and wind speed distribution at 14:00 on a typical summer day (July 20). By adjusting the building layout, the building spacing and height ratio was controlled at 1:1.3, and two landscape water bodies and strip green spaces were added. The simulation results show that the proportion of high-temperature areas above 35°C dropped from 25% to 9%, and the comfortable area with a wind speed of 1.5-3.0m / s accounted for 62%.

[0104] In one implementation of the present application, the layout information also includes traffic layout information, and the method also includes: determining the traffic flow prediction result corresponding to the second target community layout plan; adjusting the traffic layout information included in the second target community layout plan based on the traffic flow prediction result to obtain an updated second target community layout plan.

[0105] For example, based on GIS traffic flow prediction results, shared bicycle parking spots are arranged at community entrances and exits.

[0106] For example, based on GIS traffic flow prediction, 6 shared bicycle parking spots are set up within 500 meters of the community entrance and exit, with each spot accommodating 30-50 bicycles. (Q is assumed to be a peak hour passenger flow of 800 people / h, α = 0.15, and T = 2 times / h) Three electric shuttle bus routes are planned, with dedicated lanes and an intelligent dispatching system to achieve seamless connection with the subway station.

[0107] In one implementation of the present application, the method may further include: adjusting the building spacing and heights included in the second target community layout plan based on the temperature and wind speed distribution on a typical summer day to obtain an updated second target community layout plan; then determining a traffic flow prediction result corresponding to the updated second target community layout plan; and adjusting the traffic layout information of the updated second target community layout plan based on the traffic flow prediction result to obtain a new second target community layout plan.

[0108] In one implementation of the present application, the method further includes: using GIS solar radiation analysis function to identify that the annual solar radiation amount of the community building roof exceeds the minimum value H min =1200kW·h / m 2 In areas with high land use, solar photovoltaic panels are prioritized for layout, and the installed capacity is calculated according to the formula P = A·η·H, where A is the available area, η is the conversion efficiency with a value of 0.18, and H is the average annual solar radiation.

[0109] In one implementation of the present application, the proximity of commercial and residential land is constrained in the multi-objective optimization step of functional layout (i.e., the process of adjusting the initial community layout plan) through GIS buffer analysis and spatial connection operations.

[0110] In one implementation of the present application, in the comprehensive scheme evaluation decision-making step (that is, the process of determining the second community layout plan based on the evaluation score), expert ratings and user voting data are introduced, and the evaluation index weights are dynamically adjusted through the Analytic Hierarchy Process (AHP).

[0111] In one implementation of the present application, step S400, i.e., the spatial morphology dynamic simulation step, combines the community population density distribution data to set the population density threshold in the cell transformation rule. When the regional predicted population density exceeds D max =150 people / hectare, it will be converted into public service facility land first.

[0112] In one implementation of the present application, the method further includes a sponge city connection design step: using a GIS hydrological analysis module to identify community catchment areas, and arranging rain gardens in low-lying areas. The area A is calculated based on the formula Determine, where V is the design rainfall, h is the water storage depth of the rain garden, which is 0.3 meters, and η is the comprehensive runoff coefficient, which is 0.7.

[0113] In one implementation of the present application, the method further includes a green view rate guarantee step: through GIS spatial overlay analysis, a green view rate within the community building cluster is achieved to be no less than 30%, and vertical greening is used to supplement areas that do not meet the standards.

[0114] In one implementation of the present application, the method further includes establishing a building energy consumption benchmark database and using a machine learning algorithm to predict the energy consumption of buildings with different functions.

[0115] In one implementation of the present application, the method further includes a flexible space reservation step: demarcating 10% of the total land area of ​​flexible development land at the edge of the community, and the location selection comprehensively considers traffic accessibility and ecological sensitivity, and is determined through a GIS spatial suitability evaluation model.

[0116] In one implementation of the present application, the method further includes a historical and cultural protection step: utilizing GIS spatial buffer analysis to demarcate protection areas around historical buildings within the community and prohibit the construction of new high-rise buildings.

[0117] In one implementation of the present application, the method further includes, in the multi-source data collection and preprocessing steps, establishing a data dynamic update mechanism, collecting energy and carbon emission data in real time, and automatically synchronizing them to the GIS database through the data interface.

[0118] In one implementation of this application, the community layout planning method provided by this application can also be called a low-carbon community mixed-function layout optimization method based on GIS spatial analysis, such as Figure 3 As shown, the steps include:

[0119] S10: Multi-source data acquisition and preprocessing: Integrate satellite remote sensing and smart meter data, convert them into GIS standard format after cleaning, and build a community multidimensional database (i.e., target database).

[0120] S20: Space Syntax Core Analysis: Calculates road network integration, evaluates node accessibility, and provides a basis for spatial structure optimization for functional layout.

[0121] S30: Quantitative assessment of carbon emissions: Calculate building energy consumption and transportation carbon emissions, establish a carbon emissions inventory, and identify key areas for emission reduction.

[0122] S40: Multi-objective optimization of functional layout: Genetic algorithm is used to balance carbon emissions, travel distance, and land efficiency to generate the optimal functional area layout plan.

[0123] S50: Dynamic simulation of spatial morphology: Combining space syntax and cellular automata to simulate the spatial evolution of different layout schemes and generate a set of alternative schemes.

[0124] S60: Comprehensive scheme evaluation strategy: Construct an 8-index evaluation system, use the entropy weight-TOPSIS method to calculate the score, and screen the optimal low-carbon layout scheme.

[0125] As shown in Table 1, the results of the comparison table of the implementation effect of the community layout optimized by the community layout planning method provided by this application and the community layout that has not been optimized are as follows:

[0126] Evaluation Metrics Original plan Optimization plan Improvement <![CDATA[Annual total carbon emissions (kgCO2)]]> 3471400 2573400 -25.9％ Average travel distance of users (meters) 800 520 -35.0％ Land use mix index 0.35 0.58 65.7％ Ecological Connectivity Index 0.42 0.57 35.7％ Proportion of high temperature areas (%) 25 9 -64.0％ User satisfaction score (100 points) 68 90 32.4％

[0127] Table 1: Comparison of the implementation effects of optimized and unoptimized community layouts

[0128] As can be seen from the data in Table 1, the method provided in this application has achieved significant optimization in multiple dimensions. In terms of carbon emissions, by adjusting the functional layout to reduce building energy consumption and travel distance, the total annual carbon emissions were reduced by 25.9%; travel convenience was significantly improved, and the average travel distance was shortened by 35%, thanks to the reasonable layout of commercial and public service facilities. The land mixed use index increased by 65.7%, reflecting that the functional layout is more compact and efficient, reducing ineffective commuting. The improvement in ecological connectivity and microclimate comfort reflects the synergistic effect of ecological network construction and building layout optimization. Among them, the ecological connectivity index increased by 35.7%, and the proportion of high-temperature areas decreased by 64.0%. The user satisfaction score increased by 32.4%, indicating that the optimization plan takes into account both low-carbon goals and user life needs, verifying the effectiveness and practicality of this application method in low-carbon community planning.

[0129] Further, if Figure 4 As shown in Figure 2, the area changes of each functional area before and after the optimization of the community functional layout. Figure 4 It can be seen that after the optimization, the area occupied by commercial centers, public green spaces, public facilities and transportation facilities has increased, effectively increasing land utilization.

[0130] like Figure 5 As shown in the figure, the carbon emission proportion of users' travel modes before and after the optimization of community functional layout is significant. It can be seen from the figure that after the optimization, the carbon emission proportion of users' travel modes, whether private cars, public transportation or walking / cycling, has been significantly reduced.

[0131] This application proposes a community layout planning method that uses GIS to integrate multi-source data, accurately quantifying carbon emissions from buildings, transportation, and other areas. This method then uses a multi-objective optimization model to adjust functional layouts. Practical application cases demonstrate that the optimized community has reduced carbon emissions from building operations, shortened average user travel distances, and reduced overall carbon emissions, significantly improving the community's low-carbon performance.

[0132] In terms of spatial rationality, GIS space syntax and cellular automata were used to simulate the evolution of functional zones. The optimized plan increases the proximity of commercial and public service facilities to residential areas, making basic service facilities accessible within a five-minute walk, greatly improving user convenience. Furthermore, through ecological network construction and microclimate simulation, community ecological connectivity has been enhanced, the area of ​​high-temperature areas has been reduced, and the ecological environment and living comfort have been significantly improved.

[0133] In terms of scientific planning decision-making, the comprehensive evaluation system constructed by this method integrates expert experience, user needs, and quantitative data analysis, avoiding the subjectivity of traditional planning. For example, in a pilot community, the optimized solution selected using the entropy weight-TOPSIS method improved its score in a user satisfaction survey while simultaneously meeting multiple goals, including low carbon, convenient, and ecological objectives. Furthermore, the method's built-in flexibility and dynamic data update mechanism make community planning more adaptable, effectively addressing challenges such as future population growth and policy changes, and ensuring the long-term sustainable development of low-carbon communities.

[0134] In another implementation of the present application, Figure 6As shown, a community layout planning device is provided, including: a first processing module, used to input the initial community layout plan into the community layout design model for corresponding processing, and obtain a first evaluation result corresponding to a first evaluation index, the community layout plan includes layout information of each functional area included in the community, and the first evaluation index includes total carbon emissions, average travel distance of users, and land utilization rate; the first processing module is used to adjust the layout information of each functional area included in the initial community layout plan to update the community layout plan, obtain an updated community layout plan, input the updated community layout plan into the community layout design model for corresponding processing, obtain a first evaluation result corresponding to the first evaluation index, and iteratively update the community layout plan and generate an updated community layout plan in sequence. The first evaluation result corresponding to the district layout plan is iterated until the target number of iterations is reached; a third processing module is used to take the community layout plan corresponding to the first evaluation result that meets the first target condition among the multiple first evaluation results obtained as the first target community layout plan; a fourth processing module is used to determine the multiple community space form simulation results corresponding to the first target community layout plan according to the functional types of the adjacent functional areas corresponding to each functional area and the traffic accessibility between the functional areas; a fifth processing module is used to obtain the second evaluation results corresponding to each second evaluation indicator based on the multiple community space form simulation results and the multiple second evaluation indicators; a sixth processing module is used to determine the second target community layout plan based on the multiple second evaluation results obtained and the corresponding community space form simulation results.

[0135] See Figure 7 , Figure 7 The figure shows a schematic diagram of the structure of the electronic device provided in the embodiment of the present application. Figure 7 As shown, the electronic device may include: a transceiver 121 , a processor 122 , and a memory 123 .

[0136] The processor 122 executes the computer-executable instructions stored in the memory, so that the processor 122 implements part of the technical solution of the community layout planning method in the above-mentioned embodiment. The processor 122 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital data processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0137] The memory 123 is connected to the processor 122 via a system bus and communicates with the processor 122. The memory 123 is used to store computer program instructions.

[0138] By way of example and not limitation, the memory 123 may include a hard disk drive (HDD), a floppy disk drive, flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive, or a combination of two or more of these. Where appropriate, the memory 123 may include removable or non-removable (or fixed) media. Where appropriate, the memory 123 may be inside or outside the integrated gateway device. In a specific embodiment, the memory 123 is a non-volatile solid-state memory. In a specific embodiment, the memory 123 includes a read-only memory (ROM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), an electrically rewritable ROM (EAROM), or flash memory, or a combination of two or more of these.

[0139] The transceiver 121 may be used to obtain tasks to be executed and configuration information of the tasks to be executed.

[0140] The system bus can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, among others. The system bus can be divided into an address bus, a data bus, a control bus, and so on. For ease of illustration, the figure shows only one thick line, but this does not imply that there is only one bus or only one type of bus. Transceivers are used to enable communication between the database access device and other computers (e.g., clients, read-write libraries, and read-only libraries). Memory may include random access memory (RAM) and non-volatile memory.

[0141] An embodiment of the present application also provides a chip for running instructions, which is used to execute the technical solution of the community layout planning method in the above embodiment.

[0142] An embodiment of the present application also provides a computer-readable storage medium, which stores computer instructions. When the computer instructions are executed on a processor of an electronic device, the processor of the electronic device executes the technical solution of the community layout planning method of the above embodiment.

[0143] In some possible implementations, various aspects of the method provided in the present application can also be implemented in the form of a program product, which includes program code. When the program product runs on a processor of an electronic device, the program code is used to enable the processor of the electronic device to execute the steps of the method according to various exemplary implementations of the present application described above in this specification. For example, the electronic device can execute the community layout planning method recorded in the embodiments of the present application.

[0144] The program product may employ any combination of one or more readable media. The readable medium may be a readable data medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or component, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0145] The implementation method of the present application also provides a computer program product, which includes a computer program stored in a computer-readable storage medium. At least one processor can read the computer program from the computer-readable storage medium. When at least one processor executes the computer program, it can implement the technical solution of the community layout planning method in the above embodiment.

[0146] The present application is described with reference to the flowcharts and / or block diagrams of the methods, apparatuses and computer program products according to the present application. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as the combination of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable information processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable information processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0147] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable information processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1The function specified in one or more boxes.

[0148] These computer program instructions can also be loaded onto a computer or other programmable information processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0149] Those skilled in the art will readily appreciate other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present invention that follow the general principles of this application and include common knowledge or customary techniques in the art that are not disclosed herein.

[0150] It should be noted that, in addition to the implementation of the present application described in the above-mentioned specific embodiments, those skilled in the art can easily understand other advantages and effects of the present application from the contents disclosed in this specification. Although the description of the present application is introduced in conjunction with the preferred embodiment, this does not mean that the features of this invention are limited to this implementation. On the contrary, the purpose of introducing the invention in conjunction with the implementation is to cover other options or modifications that may be extended based on the claims of the present application. In order to provide an in-depth understanding of the present application, the above description contains many specific details, and the present application can also be implemented without using these details. In addition, in order to avoid confusion or blurring the focus of the present application, some specific details will be omitted in the description. It should be noted that, in the absence of conflict, the embodiments in the present application and the features in the embodiments can be combined with each other.

[0151] It should be noted that in this specification, similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings.

[0152] Although the present application has been illustrated and described with reference to certain preferred implementations of the present application, those skilled in the art should understand that the above description is provided as a further detailed explanation of the present application in conjunction with specific implementations, and that the specific implementation of the present application should not be limited to these descriptions. Those skilled in the art may make various changes in form and detail, including simple deductions or substitutions, without departing from the spirit and scope of the present application.

Claims

1. A community layout planning method, characterized in that: The method comprises: Inputting an initial community layout plan into a community layout design model for corresponding processing to obtain a first evaluation result corresponding to a first evaluation indicator, wherein the community layout plan includes layout information of each functional area included in the community, and the first evaluation indicator includes total carbon emissions, average user travel distance, and land utilization rate; Adjusting and processing the layout information of each functional area included in the initial community layout plan to update the community layout plan, obtaining an updated community layout plan, inputting the updated community layout plan into the community layout design model for corresponding processing, obtaining a first evaluation result corresponding to a first evaluation indicator, and iteratively updating the community layout plan and generating the first evaluation result corresponding to the updated community layout plan, until a target number of iterations is reached; The community layout plan corresponding to the first evaluation result that meets the first target condition among the multiple first evaluation results obtained is used as the first target community layout plan; Determining multiple community space morphology simulation results corresponding to the first target community layout plan based on the functional types of adjacent functional areas corresponding to each functional area and the traffic accessibility between the functional areas; Obtaining second evaluation results corresponding to each of the second evaluation indicators based on the multiple community space form simulation results and the multiple second evaluation indicators; A second target community layout plan is determined based on the obtained multiple second evaluation results and the corresponding community space form simulation results.

2. The community layout planning method according to claim 1, characterized in that: The second evaluation result is an evaluation score corresponding to the second evaluation indicator. Based on the obtained plurality of second evaluation results and the corresponding community space form simulation results, a second target community layout plan is determined, including: The second target community layout plan is determined according to the community space form simulation result corresponding to the highest evaluation score among the multiple evaluation scores.

3. The community layout planning method according to claim 2, characterized in that: The community layout design model includes a community carbon emission calculation module. The layout information includes building layout information and traffic layout information. The community layout plan is input into the community layout design model for corresponding processing to obtain a first evaluation result corresponding to the first evaluation indicator, including: The building layout information and the traffic layout information are input into the community carbon emission calculation module to obtain the total carbon emissions, which includes the carbon emissions from building operation and the carbon emissions from traffic travel.

4. The community layout planning method according to claim 3, characterized in that: The method includes determining the total carbon emissions by the following formula: C total =C b +C t Among them, C total is the total carbon emissions, C b Carbon emissions from operating the building, C t is the carbon emission of the transportation, E i is the annual energy consumption of different buildings, EF i is the carbon emission factor of different buildings, D j is the annual travel distance of different transportation modes, M j is the number of users using the transportation mode, EF j is the carbon emission factor of the transportation mode.

5. The community layout planning method according to claim 4, characterized in that: The method includes determining an initial community layout plan by: Acquiring initial community data, wherein the initial community data includes terrain data, building distribution geographic data, energy consumption data, and traffic data of the existing community; Preprocessing the initial community data to obtain a target database, wherein the target database includes community road network data; Obtaining a road integration heat map based on the community road network data and a preset road integration algorithm; An initial community layout plan is determined based on the road integration heat map.

6. The community layout planning method according to claim 5, characterized in that: The road integration heat map includes a plurality of road segment integrations, and the method includes determining the road segment integrations by the following formula: Among them, Integration i is the integration degree of the road section, i is the target road section node, j and k are other road section nodes, is the topological distance between nodes i and j, is the topological distance between nodes j and k.

7. The community layout planning method according to claim 6, characterized in that: The method further comprises: Based on the green space information, water body information, terrain slope information and vegetation coverage information included in the second target community layout plan, an ecological corridor network is determined so that the minimum cumulative resistance value between adjacent ecological patches included in the ecological corridor network is less than or equal to the resistance value threshold.

8. The community layout planning method according to claim 7, characterized in that: The method further comprises: Based on the temperature and wind speed distribution on a typical summer day, the building spacing and height included in the second target community layout plan are adjusted to obtain an updated second target community layout plan.

9. The community layout planning method according to claim 7, characterized in that: The layout information also includes traffic layout information, and the method further includes: Determining a traffic flow prediction result corresponding to the second target community layout plan; According to the traffic flow prediction result, the traffic layout information included in the second target community layout plan is adjusted to obtain an updated second target community layout plan.

10. An electronic device, characterized in that: include: a processor, and a memory communicatively connected to the processor; The memory stores a computer program; The processor executes the computer program stored in the memory to enable the electronic device to implement the community layout planning method as described in any one of claims 1-9.

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