Life circle outdoor fitness facility intelligent supplement method and system based on genetic algorithm

Abstract

This invention discloses a method and system for intelligently supplementing outdoor fitness facilities in residential areas based on genetic algorithms. It relates to the fields of urban planning, landscape architecture, artificial intelligence, and sports science. The method includes using a genetic algorithm to supplement outdoor fitness facilities based on the existing facility layout, generating a facility supplementation scheme that meets planning requirements and maximizes overall benefits through iterative optimization. It constructs a complete logical system encompassing outdoor fitness facility configuration principles, multi-level residential area delineation, placement constraints, and placement steps, transforming higher-level planning requirements into implementable steps and achieving precise facility supplementation. Simultaneously, it establishes a dynamic linkage mechanism between placement needs and constraints, automatically determining the feasibility of site construction, thus improving the efficiency, accuracy, and objectivity of the judgment.

Description

Technical Field

[0001] This invention relates to the fields of urban planning, landscape architecture, artificial intelligence, and sports science, specifically to a method and system for intelligently supplementing outdoor fitness facilities in living areas based on genetic algorithms. Background Technology

[0002] Existing methods for planning the layout of outdoor fitness facilities can provide specific basis for the location of outdoor fitness facilities to a certain extent, but the planning results are not systematic and the planning results based solely on the user's perspective are highly accidental and subjective, ignoring the synergistic and mutually exclusive effects between facilities, which can easily lead to resource waste and service blind spots.

[0003] Furthermore, among the solutions in the public domain, there are two major problems with the planning of outdoor fitness facilities: First, it is difficult to achieve multiple objectives simultaneously. In practice, the focus is on the number and scale of facilities required by higher-level planning, while theoretical research focuses on environmental assessment and user travel characteristics. The two cannot be integrated when implemented. Second, the planning efficiency is low. Traditional methods require a lot of on-site surveys and site feasibility studies, which consume manpower and resources. Moreover, due to data acquisition limitations, it is difficult to maximize the layout benefits in a dynamic environment. Summary of the Invention

[0004] To address the shortcomings mentioned in the background section, the present invention aims to provide a method and system for intelligently supplementing outdoor fitness facilities in living areas based on genetic algorithms, which solves the problems of disconnect between planning requirements and implementation, and poor spatial adaptability in the prior art.

[0005] Firstly, the objective of this invention can be achieved through the following technical solution: a method for intelligently supplementing outdoor fitness facilities in a living circle based on a genetic algorithm, the method comprising the following steps: Acquire outdoor fitness-related data, which includes spatial carrier data, existing outdoor facility data, and residential land data; the outdoor fitness-related data is acquired based on a predetermined research scope. The spatial carrier data is analyzed for attributes to obtain the physical attributes and comprehensive potential of the spatial carrier; the placement requirements of outdoor fitness facilities are determined based on the pre-planned facilities; the spatial carrier data and the existing outdoor facility data are overlaid, and the usable area of ​​the spatial carrier is determined based on the overlay results. The spatial carrier data, physical attributes of the spatial carrier, comprehensive potential of the spatial carrier, existing outdoor facility data, residential land data, available area of ​​the spatial carrier, and placement requirements of outdoor fitness facilities are input into a pre-established genetic algorithm model, and the optimal layout scheme of outdoor fitness facilities is output.

[0006] The beneficial effects of this invention are: This invention uses a genetic algorithm to supplement outdoor fitness facilities based on the existing facility layout. It generates a facility supplementation scheme that meets planning requirements and maximizes comprehensive benefits through iterative optimization. It constructs a complete logical system of outdoor fitness facility configuration principles, multi-level living circle delineation, placement constraints, and placement steps, transforming higher-level planning requirements into implementable steps and achieving precise facility supplementation. At the same time, it establishes a dynamic linkage mechanism between placement needs and constraints, which can automatically determine the feasibility of site construction, thereby improving the efficiency, accuracy, and objectivity of the judgment. Attached Figure Description

[0007] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Figure 1 This is a schematic diagram of the method flow of the present invention; Figure 2 This is a schematic diagram of the overall framework of the present invention; Figure 3 This is an example diagram of the planning unit of the present invention; Figure 4 This is an example diagram of the spatial carrier identification results of the present invention; Figure 5 This is an example diagram of space carrier data processing according to the present invention; Figure 6 This is an example diagram illustrating the physical properties of the space carrier of the present invention; Figure 7 This is an example diagram of the current facility data attributes of the present invention; Figure 8 This is an example diagram of the community clustering results of this invention; Figure 9 This is an example spatial carrier diagram of the present invention; Figure 10 This is an example diagram of the final facility allocation result of the present invention; Figure 11 This is a schematic diagram of the system structure of the present invention. Detailed Implementation

[0008] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0009] Example 1: like Figure 1As shown, a method for intelligently supplementing outdoor fitness facilities in a community based on genetic algorithms includes the following steps: Acquire outdoor fitness-related data, which includes spatial carrier data, existing outdoor facility data, and residential land data; the outdoor fitness-related data is acquired based on a predetermined research scope. Outdoor fitness-related data were collected by dividing each neighborhood within the pre-defined research area into community living circle units of a pre-defined size based on urban main roads, urban water systems, and urban mountains.

[0010] Specifically, the process of defining the research scope includes the following arrangements: Based on higher-level planning or urban features, the research area is divided into multiple 15-minute community living circles.

[0011] After determining the research scope, based on the city's higher-level planning, 15-minute community living circle units are delineated. If no community living circle units are delineated, each block within the research scope is divided into community living circle units with an area of ​​130h㎡ to 200h㎡ based on the city's main roads, water systems, and mountain ranges.

[0012] Define the set of community living circle units as C, and it exists that: , where n is the number of community living circle units within the research scope.

[0013] In this example, the main urban area of ​​a city is taken as the research scope. Based on the higher-level planning and urban features, the research scope is divided into 107 community living circle units in ArcGIS Pro software.

[0014] In this specific project, to accommodate the preceding data format, this example further divides each community living circle unit into several adjacent 20 m × 20 m fishing nets.

[0015] The spatial carrier data is analyzed for attributes to obtain the physical attributes and comprehensive potential of the spatial carrier; the placement requirements of outdoor fitness facilities are determined based on the pre-planned facilities; the spatial carrier data and the existing outdoor facility data are overlaid, and the usable area of ​​the spatial carrier is determined based on the overlay results. The physical attributes of a spatial carrier include its area and shape, and the comprehensive potential of the spatial carrier includes its environmental potential and its land potential. The environmental potential is determined by the comprehensive environment of the community living circle unit, including at least one of the following: surrounding activity level, facility richness, environmental pleasantness, and transportation accessibility. The potential of the land parcel is determined by the properties of the spatial carrier itself, including at least one of surface cover, vegetation composition, and land parcel enclosure.

[0016] Specifically, in this embodiment, the process of identifying and determining the attributes of space carrier data includes the following steps: Obtain vector data of the spatial carrier into which outdoor fitness facilities can be placed.

[0017] The spatial carriers for outdoor fitness facilities are urban plots of land with available construction space that allow for the placement of outdoor fitness areas. Their specific composition can be determined based on demand, such as existing green spaces, planned green spaces, vacant land, and strategic reserve land. Vector surface data of these spatial carriers can be obtained from open data platforms or government websites. The vector surface data of these spatial carriers is then divided into various community living circle units based on their boundaries.

[0018] Define the set of spatial carriers of the Xth community living circle unit as Then it exists: ,in l 'm' represents the spatial carrier, and 'm' represents the number of spatial carriers in the community living circle unit.

[0019] In this example, the spatial carriers include existing urban green spaces and vacant urban land.

[0020] In this example, the vector data of the city's existing green space comes from documents provided by the government. For the identification of vacant urban land, high-precision remote sensing imagery (1 m) of the city in 2025 was downloaded from the Google Earth platform. The Deeplab V3 image semantic segmentation deep learning model was used to identify "grassland," "bare land," and "hard ground" as vacant land.

[0021] Based on the boundaries of community living circle units, the vector surface data of existing urban green space and vacant urban land are divided into each community living circle unit. The existing urban green space and vacant urban land in each community living circle unit together constitute the spatial carrier of outdoor fitness facilities in that community living circle unit.

[0022] Furthermore, to maintain the format of the preceding project data, in ArcGIS Pro, the segmented fishing nets are combined with the existing urban green space vector surface data and the urban vacant land vector surface data, respectively. The "carrier" attribute field of fishing nets with an overlap area > 50% is assigned a value of 1. Taking the 24th community living circle unit as an example (X=1), this community living circle unit has a total of 5324 fishing nets, of which 400 have a "carrier" attribute field of 1. Assigning values ​​to fishing nets is an optional operation.

[0023] Calculate the area and shape properties of the spatial carrier.

[0024] In geographic information system software, it serves as a spatial carrier. l Add field attributes "Area" and "Shape".

[0025] Use geometric calculation tools to calculate the area of ​​spatial carrier i of the Xth community living unit. According to the provisions on "Pocket Park Size Classification and Green Space Ratio" in the "Pocket Park Construction Guidelines (Trial)" compiled by the General Office of the Ministry of Housing and Urban-Rural Development, the usable area is obtained by deducting the green space ratio. , will The green space ratio in this plan is as follows, entered into the "Area" attribute of the spatial carrier: Table 1. Pocket Park Size Classification and Green Space Ratio Then the following relationship exists: The format of the "shape" attribute is ( .in, and The m-th spatial carrier in the x-th community living circle unit x The maximum width and length of the built-in rectangle that can be accommodated, in meters (m). The specific calculation method is as follows: For the spatial carrier of the Xth community living circle unit (Vector surface), which can accommodate a maximum built-in rectangle. Defined as: Where R is any element completely contained in The area of ​​the inner rectangle (its sides can be at any angle to the coordinate axes) is Area(R).

[0026] Let the width and height of the rectangle be... , Then the "shape" attribute field middle: , satisfy The unit is meters (m).

[0027] In this example, taking the 24th community living circle unit (X=24) as an example, after processing in ArcGIS Pro software, there are a total of 28 spatial carriers.

[0028] The comprehensive potential of a spatial carrier is calculated, which consists of two parts: environmental potential and land potential.

[0029] Environmental potential is determined by the comprehensive environment of the community living circle unit. Integrating knowledge from landscape architecture, urban and rural planning, sports science, and sociology, environmental potential indicators are selected based on needs, such as surrounding activity level, facility richness, environmental pleasantness, and transportation accessibility. Based on the data characteristics of each environmental potential indicator, basic data is obtained from open-source data platforms, supplemented by machine learning algorithms for data analysis, and the processed data is then entered into geographic information system software.

[0030] The potential of a land parcel is determined by the inherent attributes of its spatial structure. Integrating knowledge from landscape architecture, urban and rural planning, sports science, and sociology, land parcel potential evaluation indicators are selected based on requirements, such as land cover, vegetation composition, and parcel enclosure. Based on the characteristics of each parcel's potential indicator data, basic data is obtained from open-source data platforms, supplemented by machine learning algorithms for data analysis, and the processed data is then entered into geographic information system software.

[0031] In geographic information system software, the sub-indicators of environmental potential are normalized. Based on the discrete characteristics of the indicator data, objective weighting methods such as entropy weighting, CRITIC method, or coefficient of variation method are used to determine the weight of each indicator. Weighted superposition calculation is then performed to obtain the comprehensive environmental potential. Similarly, the sub-indicators of land parcel potential are normalized. Based on the discrete characteristics of the indicator data, objective weighting methods such as entropy weighting, CRITIC method, or coefficient of variation method are used to determine the weight of each indicator. Weighted superposition calculation is then performed to obtain the comprehensive land parcel potential. The applicable scenarios for the above methods of determining the weights of environmental potential indicators and land parcel potential indicators are as follows: 1) Coefficient of variation method: This method is suitable for situations where there are few indicators, the indicators are independent of each other, and the data distribution is close to a normal distribution. The data must be normalized non-negative continuous values. For example, if the potential of a land parcel only includes three indicators: building density, plot ratio, and land slope, and the data are all continuous normal distribution values ​​with no obvious correlation between the indicators, the coefficient of variation method is suitable. It automatically assigns weights based on the dispersion of the indicators themselves.

[0032] 2) Entropy weight method: This method is suitable for situations with a large number of indicators, a large number of evaluation units, and sufficient sample size. It requires that the data have been normalized into positive vector values. For example, environmental potential includes more than five indicators such as green space ratio, hydrological regulation capacity, landscape connectivity, ecological sensitivity, and noise interference. The evaluation units are thousands of grids or plots, with a large sample size and rich information. The entropy weight method is suitable for this situation, as it uses the magnitude of information entropy to determine the importance of the indicators.

[0033] 3) CRITIC method: This method is suitable for situations where there is correlation or conflict between indicators, and it is necessary to simultaneously reflect the distinguishing ability of the indicators and the contradiction between them. Normalized values ​​are required. For example, in environmental potential, ecological suitability and green space ratio are strongly positively correlated, while traffic disturbance and ecological suitability are in conflict. There is a clear correlation between the indicators, and it is necessary to consider both dispersion and conflict. The CRITIC method is suitable for this situation.

[0034] The comprehensive environmental potential and the comprehensive land potential are superimposed using an equal-weighting method to obtain the final comprehensive potential.

[0035] The updated space carrier A new attribute field, "Comprehensive Potential," has been added and defined as follows: The value range is [0,1]. The vector planes of each space carrier and the comprehensive potential raster layer are overlaid, and the average value of the comprehensive potential of the raster contained within the vector plane range is entered into the "Comprehensive Potential" attribute field to obtain the comprehensive potential of each space carrier.

[0036] In this example, environmental indicators were selected as environmental potential indicators, such as surrounding activity level, facility abundance, environmental pleasantness, and transportation accessibility; the site's own indicators were selected as land cover, vegetation composition, and site enclosure degree. Specific descriptions and data sources are shown in Tables 2 and 3 below: Table 2 Environmental Potential Indicators Table 3 Land Plot Potential Indicators The process of overlaying spatial carrier data with existing outdoor facility data, and determining the usable area of ​​the spatial carrier based on the overlay results, is as follows: Spatial overlay of spatial carrier data and existing outdoor facility data is used to determine the area of ​​existing outdoor facilities within the spatial carrier. The usable area of ​​the space is obtained by subtracting the area of ​​the existing outdoor facilities from the area of ​​the space carrier.

[0037] Specifically, based on the higher-level plan, the types, quantities, and area requirements of the outdoor fitness facilities to be planned are determined. Outdoor fitness facilities are divided into mandatory facilities and optional facilities.

[0038] The mandatory facilities are those stipulated in the city's higher-level planning for each community living circle and are required to be included. Based on relevant documents on fitness facility planning, such as the "Suggestions on the Configuration of Service Elements in Urban Community Living Circles (15 Minutes)" - 2021, the "Standards for Improving the Construction of Residential Communities" - 2020, the "Opinions on Building a Higher-Level Public Service System for National Fitness" - 2022, and the "Standards for Planning and Design of Urban Residential Areas" (GB50180-2018), the walking distances of the 5-minute, 10-minute, and 15-minute living circles in each community living circle unit, the types and quantities of outdoor fitness facilities that must be included in different living circle levels, and the upper and lower limits of the area of ​​outdoor fitness facilities in each level of living circle are determined.

[0039] Define the facilities set that must be included in a 5-minute living circle as FA, a 10-minute living circle as FB, and a 15-minute living circle as FC. Each set contains elements that are binary arrays, then: in, These refer to the facility types included in FA, FB, and FC, respectively. Let represent the minimum number of facilities i required, and let x, y, and z represent the number of facility types in the three sets, respectively.

[0040] Optional facilities are outdoor fitness facilities that are not explicitly specified in the higher-level plan but have a positive impact on public health. The specific types of facilities can be specified according to the needs of the regional plan, such as badminton courts, roller skating rinks, tennis courts, outdoor swimming pools, and climbing walls.

[0041] If we define the set of optional placement facilities as FD, then we have: Where 0 indicates that the number of facilities that can be installed in the community living circle unit can be 0, and o represents the types of facilities in the set.

[0042] Suppose there are m types of outdoor fitness facilities among FA, FB, FC, and FD, and the set of all facility types can be represented as F, with each facility type represented as f. Then, the following holds: In this example, the planning mentioned above is summarized as follows: According to the relevant provisions in the "Urban Residential Area Planning and Design Standard" (GB50180-2018), the walking distance of a 15-minute living circle is 800-1000 m, the walking distance of a 10-minute living circle is 500 m, and the walking distance of a 5-minute living circle is 300 m.

[0043] The area of ​​outdoor fitness facilities within a 15-minute living circle is 3150~5620 m², within a 10-minute living circle it is 1310~2460 m², and within a 5-minute living circle it is 770~1310 m².

[0044] The following facilities must be installed within a 5-minute living circle: 1 half-court basketball court, 1 gateball court, 2 table tennis courts, 5 outdoor multi-purpose fitness areas (each 150 m²), 3 children's facilities areas (each 150 m²), and 3 square dance areas (each 150 m²).

[0045] The following facilities must be installed within a 10-minute living circle: one 5-a-side football field, one basketball court, and one volleyball court.

[0046] The following facilities must be installed within a 15-minute living circle: one 7-a-side football field, one basketball court, and one volleyball court.

[0047] Optional installation facilities include: tennis courts, roller skating rinks, skate parks, and badminton courts.

[0048] In this example, m=14, and the corresponding multi-level living circle must be included in the following facility set: The set of optional implantation facilities is as follows: The construction area and size requirements for outdoor fitness facilities are determined based on higher-level planning and construction standards.

[0049] Based on relevant documents on fitness facility planning, such as the "Suggestions on the Allocation of Service Elements in Urban Community Living Circles (15 minutes)" - 2021, the "Standards for Improving the Construction of Residential Communities" - 2020, the "Opinions on Building a Higher-Level Public Service System for National Fitness" - 2022, and the "Standards for Planning and Design of Urban Residential Areas" (GB50180-2018), as well as the standard dimensions of common outdoor fitness facilities, the minimum area and minimum dimensions of all facilities involved are determined.

[0050] Construct a "facilities-minimum area-minimum size" mapping table, and project the mapping table onto the sets of mandatory and optional facilities in the multi-level living circle according to the facility type, transforming the binary tuples into quadruples.

[0051] The transformed set is as follows: in, This represents the minimum area of ​​facility i. These represent the minimum width and minimum length of the footprint occupied by facility i, respectively.

[0052] In this example, the transformed multi-level living circle must incorporate the following facility set: The set of optional implantation facilities is as follows: The current distribution of outdoor fitness facilities within the study area will affect subsequent facility planning. The current distribution of outdoor fitness facilities can be obtained through three methods: government documents, street view recognition, and POI distribution.

[0053] Method 1: Government Documents. Obtain the outdoor fitness facility registration list from the local government or its official website, obtain the specific location description or latitude and longitude information of the facilities, compare and refer to the latest high-definition remote sensing imagery to determine the specific location of the facilities, and finally record the location in the geographic information system software.

[0054] Method 2: Street View Recognition. Collect street view images covering the entire study area. Based on deep learning algorithms, construct a training set to train a deep learning target recognition model, obtaining a high-precision outdoor fitness facility target recognition model. Apply the mature model to the street view images to obtain the distribution of outdoor fitness facilities within the study area. Finally, record the distribution results in geographic information system software.

[0055] Method 3: POI Distribution. Download the POI vector point data of fitness facilities from the open map platform, perform data cleaning in the geographic information system software, delete indoor fitness facilities (such as gyms, indoor swimming pools, etc.), and obtain the final distribution of outdoor fitness facilities.

[0056] Finally, the vector point data of outdoor fitness facilities obtained through the three methods undergoes final data cleaning, classifying all data into facility types appearing in set F. Assuming there are ultimately m facility types, and the current set of outdoor fitness facilities is E, then: in, Let i be the i-th facility among the m-th facilities.

[0057] For updated space carriers (Already includes attributes "shape", "area", and "overall potential") Add attribute field " "", , ..., The symbols "" and "" represent the presence or absence of existing outdoor fitness facilities, respectively. The spatial carrier... l If the elements in E are combined with the existing outdoor fitness facilities, and these elements fall within the spatial carrier... l In the middle, then l The corresponding attribute field is changed to 1, and vice versa. For example, if (Facility type is) (Serial number 1) falls within In the middle, and If there are no other existing outdoor fitness facilities, then attribute field " "Assign a value of 1, and 0 for everything else."

[0058] Use space carrier The usable area for renovation is calculated by subtracting the area of ​​the existing outdoor fitness facilities from the original area. And the "Area" field.

[0059] The information that can be obtained is: 1) vector point data of all existing outdoor fitness facilities within the research scope; 2) the composition of existing outdoor fitness facilities in the spatial carrier.

[0060] In this example, m=14. The properties of existing outdoor fitness facilities are as follows: The spatial carrier data, physical attributes of the spatial carrier, comprehensive potential of the spatial carrier, existing outdoor facility data, residential land data, available area of ​​the spatial carrier, and placement requirements of outdoor fitness facilities are input into a pre-established genetic algorithm model, and the optimal layout scheme of outdoor fitness facilities is output.

[0061] The processing procedure of the pre-established genetic algorithm model is as follows: The residential land data is divided into living circles based on the preset DBSCAN density clustering algorithm to obtain the range of multi-level living circles. Based on the demand for outdoor fitness facilities and the current data on outdoor facilities, the missing amount of outdoor fitness facilities in the multi-level living circles is determined as the outdoor facilities to be added. Based on the physical properties of the spatial carriers, potential spatial carriers that meet the placement constraints of the outdoor facilities to be added are selected from the multi-level living circles; wherein, the placement constraints include site constraints and facility mutual exclusion constraints. Based on the comprehensive potential of the spatial carrier, determine the placement priority of the undetermined spatial carrier, select the undetermined spatial carrier with the highest placement priority to place the outdoor facilities to be added; generate an initial layout plan; The initial layout scheme is iteratively optimized based on a preset fitness function and a genetic algorithm. The layout scheme corresponding to the optimal fitness function is obtained through selection, crossover, and mutation operations, which serves as the optimal layout scheme for outdoor fitness facilities.

[0062] Specifically, by acquiring the collection of spatial carriers (In this step, medium element The area is already included. ,"shape"( "Comprehensive potential" and the relevant attributes of the existing facilities " "、...、" "property).

[0063] Add a new facility field to it. " "、...、" ", " respectively represent the number of facilities to be added in subsequent planning. If it is 1, then If the number of newly added facilities of this type is 0, then No new facilities of this type will be added. " "、...、" "The initial value is 0."

[0064] The process of delineating residential areas based on the preset DBSCAN density clustering algorithm is as follows: Using the residential land vector surface of the residential land data as the clustering sample, the centroid coordinates of the residential land vector surface are used as the spatial location; Based on the DBSCAN density clustering algorithm, the clustering samples are clustered with a pre-set neighborhood radius and minimum clustering net number to obtain multiple clusters; For residential land within each cluster, the centroid coordinates are calculated using an area-weighted average. Using the center of the cluster as the delineation center of the living circle, and the preset standard walking distance corresponding to the living circle, a multi-radius buffer zone is generated as the range of the multi-level living circle.

[0065] Specifically, different levels of community living circles are defined within each community living circle unit. The scope is determined based on different usage scenarios.

[0066] If the community living circle unit already has planned 5-minute, 10-minute, and 15-minute living circles, then the research scope will be converted into vector surface data in the geographic information system software.

[0067] If there is no existing community living circle unit plan, the residential land cluster center is used as the center of the different levels of living circles, and the walking distance of the different levels of living circles is used as the radius to delineate the buffer zone, thus obtaining the scope of the different levels of living circles. The specific calculation method is as follows: Residential land data acquisition: Land use data within the research area was obtained from official government channels, entered into Geographic Information System (GIS) software, and residential land vector surface data was extracted. This data is denoted as a set. ,in Let be the vector surface of the i-th residential land.

[0068] Residential land sample construction: Each residential land vector surface As independent cluster samples, their set geometric centroid coordinates are extracted. As a spatial location, its area can be preserved at the same time. As weights.

[0069] DBSCAN-based residential land density clustering: The DBSCAN density clustering algorithm is used to identify residential land clusters. Compared with traditional clustering methods such as K-Means and hierarchical clustering, this algorithm does not require manual pre-setting of the number of clusters and can adaptively generate clusters based on the actual spatial distribution of residential land. It can identify residential spaces of any irregular shape, such as strips and clusters, which is more in line with the actual urban construction pattern. At the same time, it can automatically remove low-density and isolated noise data, avoid the interference of scattered residential land on the cluster centers, ensure the rationality and accuracy of subsequent delineation of living circle centers, and has a high degree of compatibility with the spatial analysis logic of geographic information systems.

[0070] Two parameters, neighborhood radius ε and minimum clustering net number MinPts, are pre-defined. Spatial distances are calculated using the centroid of the residential land vector surface as nodes to determine the core point and its neighborhood range. The specific calculation method is as follows: Any two residential land vector surfaces Euclidean distance: In the formula These are residential land vector planes. The coordinates of the centroid.

[0071] Residential land vector surface The neighborhood radius ε is: The core point is determined as follows: if the number of neighborhood faces of a residential land vector surface is not less than the minimum clustering grid number, then that surface is a core point. The clustering criteria are as follows: based on density accessibility and density reachability rules, spatially connected residential land vector surfaces are grouped into the same cluster C; low-density, isolated surfaces are identified as noise and removed. The total number of clusters k is adaptively determined by the spatial distribution of residential land, without being pre-set. ; satisfy: Residential land cluster center calculation: For residential land within each cluster, the centroid coordinates are calculated by weighting the area of ​​the residential land area. It serves as the delineation center of a living circle under unregulated conditions.

[0072] Let the m-th cluster be... The number of residential land vector surfaces is : =| |; The area of ​​each surface is The center point of this cluster coordinate( )for: Multi-level community living circle delineation: Taking the center of each residential land cluster as the center, and based on the standard walking distances corresponding to the three levels of community living circles (5 minutes, 10 minutes, and 15 minutes) in the standard, circle radii of 1000 m, 500 m, and 300 m are set respectively. Multi-radius buffer zones are generated in the geographic information system software to finally obtain the vector surface range of different levels of living circles.

[0073] Record the spatial carriers included within the multi-level living circle, defined by the cluster center. Within a 5-minute living circle centered on the center, the collection of spatial carriers includes: _LA, the collection of spaces within a 10-minute living circle is _LB, the collection of spaces within a 15-minute living circle is _LC.

[0074] Where x, y, and z represent the number of spatial carriers contained in the three sets, respectively.

[0075] Based on relative spatial relationships, the following relationship exists: .

[0076] In this example, we use living circle 21 as a special case. After clustering, this community's living circle units generate two cluster centers, which can cover the service areas of two residential areas. In the figure, blue represents the residential area, red represents the cluster centers, and the radii of the three concentric circles are 300 m, 500 m, and 1000 m, respectively. The site constraints are set as follows: Outdoor fitness equipment is configured on a spatial carrier. If the area and size meet the requirements, it is allowed to be placed in the spatial carrier; otherwise, it cannot be placed in the spatial carrier. The area requirement is set as follows: the minimum area and minimum size of the facility to be placed are both smaller than the available area of ​​the space carrier and the minimum size of the largest built-in rectangle of the remaining space. The mutual exclusion constraints for the facilities are set as follows: The same type of outdoor fitness equipment is not allowed to be placed in the same space.

[0077] In this embodiment, the constraint setting process is as follows: The placement constraints include two types of constraints: site constraints and facility mutual exclusion constraints.

[0078] Site constraints mean that outdoor fitness equipment can only be placed in a space if both the area and dimensions meet the requirements. If either the area or the dimensions do not meet the requirements, the equipment cannot be placed in the space. The specific relationship can be expressed as follows: Acquire spatial carrier set (In this step, medium element The area is already included. ,"shape"( "Comprehensive potential" Current facility-related attributes " "、...、" "New facility-related attributes" " "、...、" The multi-level living circle must include the facility set FA, FB, FC and the optional facility set FD (quadruple consisting of "facility"-"quantity"-"minimum area" and "minimum width-minimum length").

[0079] Design space carrier The facilities already installed in the middle are as follows (Including existing facilities and newly installed facilities), for any facility f, its actual geometric coverage area (vector surface, such as the rectangular / circular area occupied by the facility) in geographic space is denoted as . Then the remaining space Defined as: The corresponding attributes are: Remaining space The actual area is minus Area of ​​facility i ; ( Remaining space The width and length of the maximum built-in rectangle that can be accommodated.

[0080] The two site constraints that must be satisfied are: 1) The minimum area of ​​facility a Smaller than space carrier remaining space area ; 2) The minimum width minus the minimum length of a certain facility to be installed (a) meets the following requirements: in,( , ) represents the minimum width and minimum length of facility a, ( , ) as a space carrier The remaining space is the minimum width and length of the largest built-in rectangle.

[0081] Correspondingly, for Add an attribute field "Placement Facility" to input. The specific facility types are named in the text, separated by commas, such as " Add the attribute field "Remaining Area" and enter the data. Numerical value; add a field "Remaining Shape", enter ( Size pair. The two values ​​mentioned above are dynamically updated during subsequent facility configuration.

[0082] The meaning of facility mutual exclusion is: to ensure that different types of outdoor fitness facilities can be evenly distributed and provide coordinated services within the community living unit, the same facilities cannot be placed in the same spatial carrier. For facility type i, the following relationship exists: In this example, the site constraints are explained in detail below, taking into account the specific site conditions: Example space carrier 1 and example space carrier 2 are two sites with the same area and shape. Example space carrier 2 contains the existing outdoor fitness facilities: table_tennis.

[0083] The following facilities cannot be placed in Example Space Carrier 1: 5_football, basketball, volleyball, 7_football, tennis, roller_skating, and skateboarding. Among them, only the volleyball facility cannot be placed because its shape does not conform (the longest side is 21 m); the other facilities do not conform in either area or shape.

[0084] The following facilities cannot be placed in Example Space Carrier 2: 5_football, basketball, volleyball, 7_football, tennis, roller_skating, skateboarding, and table_tennis. Among them, the volleyball facility cannot be placed because its shape does not meet the requirements (the longest side is 21 m), the table_tennis facility cannot be placed because of the mutual exclusion principle of facilities, and the remaining facilities cannot be placed because their area and shape do not meet the requirements.

[0085] To ensure that the configuration of outdoor fitness facilities meets planning requirements, rules for their placement must be established. The key points are: 1. Meeting the mandatory placement requirements of outdoor fitness facilities across multiple levels of residential areas; 2. Meeting the upper and lower limits of the planned outdoor fitness facility area; 3. Using the existing distribution of outdoor fitness facilities as the basis for planning.

[0086] To achieve the above goals, the insertion steps are defined as follows: In this community living circle unit, the center of the k-th cluster is used to determine... Whether the existing outdoor fitness facilities in the multi-level living circles centered at (k=1,2,...m) meet the planning requirements, and record the lack of various facilities in each level of living circle.

[0087] Let the set of missing facilities within the 5-minute living circle in the k-th cluster of living circle X be . The missing facilities in the 10-minute living circle are collected as follows The missing facilities in the 15-minute living circle are collected as ,exist: Configure the missing facilities within the 15-minute living circle of the k-th (k=1,2,...m) cluster in this community living circle unit: based on The facilities are then placed sequentially. (Regarding the set...) The space carrier that meets the placement constraints is determined based on its potential value. Perform weighted random selection: Extract the set of spatial carriers that meet the constraints: ,in ; Calculate the potential value of all space carriers in set S. The sum of: ; Each space carrier The probability of being selected is: ; Using a roulette wheel method, select a spatial carrier located at S and attempt to place the facility.

[0088] If all If the insertion constraint is not met, skip the facility and proceed to the next type of missing facility configuration until... All missing facilities have been installed.

[0089] Each time a facility is installed, it will be combined with... Spatial carrier elements in the set are matched to the set. Corresponding element in Update the set of placement facilities for this space carrier. and will " "、...、" Change the corresponding column in the blank to 1, and update the remaining space. , 、( .

[0090] Configure the missing facilities within the 10-minute living circle of the k-th (k=1,2,...m) cluster in this community living circle unit: based on The facilities are then placed sequentially. (Regarding the set...) The space carrier that meets the placement constraints is determined based on its potential value. Perform a weighted random selection (using the same method and steps as the previous step) to attempt facility placement. If all If the insertion constraint is not met, skip the facility and proceed to the next type of missing facility configuration until... All missing facilities have been installed.

[0091] Each time a facility is installed, it will be combined with... Spatial carrier elements in the set are matched to the set. Corresponding element in Update the set of placement facilities for this space carrier. and will " "、...、" Change the corresponding column in the blank to 1, and update the remaining space. , 、( .

[0092] Configure the missing facilities within the 5-minute living circle of the k-th (k=1,2,...,m) cluster in this community living circle unit: based on The facilities are then placed sequentially. (Regarding the set...) The space carrier that meets the placement constraints is determined based on its potential value. Perform a weighted random selection, and then attempt to place the facility. If all If the insertion constraint is not met, skip the facility and proceed to the next type of missing facility configuration until... All missing facilities have been installed.

[0093] Each time a facility is installed, it will be combined with... Spatial carrier elements in the set are matched to the set. Corresponding element in Update the set of placement facilities for this space carrier. and will " "、...、" Change the corresponding column in the blank to 1, and update the remaining space. , 、( .

[0094] For each of the k-th (k=1,2,...,m) clusters, outdoor fitness facilities are installed within 15-minute, 10-minute, and 5-minute living circles. During the installation process, all outdoor fitness facilities to be installed are first prioritized by area from smallest to largest (smaller facilities have higher priority). High-priority facilities are installed first, and then low-priority facilities are randomly added until the total area of ​​outdoor fitness facilities within the current living circle meets the upper and lower limits of the configuration area specified in the planning document, at which point the installation of facilities stops.

[0095] Finally, the area of ​​outdoor fitness facilities in all living areas of all clusters is calculated. For living areas that do not meet the area standards, facilities are randomly added or deleted. The deletion operation must retain the facilities and their quantities required by FA, ​​FB, and FC. This operation is repeated until the area of ​​outdoor fitness facilities in all living areas of all clusters meets the planning standards.

[0096] Each time a facility is installed, the space is updated. Collection of implantation facilities and will " "、...、" Change the corresponding column in the blank to 1 or 0, and update the remaining space. , 、( .

[0097] The fitness function includes at least one of the following metrics: facility richness, facility service coverage, and facility demand responsiveness.

[0098] An evaluation index for judging the quality of outdoor fitness facility layout results is selected as the fitness function for outdoor fitness facility layout based on genetic algorithm.

[0099] This method does not specify specific indicator types to enhance its versatility. Indicator selection should reflect the distribution characteristics of fitness facility abundance, demand responsiveness, and service coverage. By calculating the fitness function for each option, the method is encouraged to continuously evolve towards the optimal overall indicator.

[0100] In this example, the fitness function includes the following metrics: facility richness, facility service coverage, and facility demand responsiveness. The calculation methods are shown in Table 4 below: Table 4 In this embodiment, the process of iteratively optimizing the initial layout scheme based on a preset fitness function and a genetic algorithm is as follows: N initial layout schemes are randomly generated, and a genetic algorithm is used to carry out multi-objective iterative optimization. Through selection, crossover, and mutation operations, the population is driven to evolve in the direction that satisfies the constraints and the optimal comprehensive fitness function, and finally converges to the Pareto optimal solution set.

[0101] Chromosome coding and population initialization Chromosome coding: Each outdoor fitness facility layout scheme is coded as a chromosome X, with the chromosome length equal to the total number of spatial carriers. The product of the total number of facility types m, each gene corresponds to a "certain spatial carrier". Should a certain type of facility be configured? The status of "" can be either 0 or 1 (0 indicates not configured, 1 indicates configured), which is related to the defined newly added facility attribute field " " "、...、" One-to-one correspondence: in This indicates whether the p-th space carrier is equipped with the i-th type of facility.

[0102] Population initialization: Based on N initial layout schemes, N chromosomes are generated to form an initial population P(0). Each chromosome satisfies site constraints and facility mutual exclusion constraints. The initial population size N is 50~200 (which can be adaptively adjusted according to the size of the study area).

[0103] Fitness function and constraint penalty The defined fitness function is used as the multi-objective fitness function, and penalties are imposed on schemes that violate the insertion constraints to construct the comprehensive fitness function Fitness(X): in, The standardized score for the w-th reward indicator; Let w be the weight coefficient of the w-th indicator, satisfying It can be determined by the analytic hierarchy process and expert scoring method; P(X) is the penalty term for constraint violation, and the number and degree of violation of site constraints and facility mutual exclusion constraints in chromosome X are counted. This is a penalty coefficient, which takes a positive value and is used to ensure that the insertion requirement is always met.

[0104] Selective Operations – Elite Retention and Pareto Classification Pareto classification: For all individuals in the current population P(t), Pareto dominance is determined based on multi-objective fitness, and the population is divided into different Pareto levels. in, The non-dominated solution set (Pareto optimal front) indicates that all individuals in the solution set exhibit multi-objective equilibrium behavior.

[0105] Fitness ranking: Within the same Pareto level, ranking is based on crowding distance. The larger the crowding distance, the more evenly individuals are distributed in the target space, which is more conducive to maintaining population diversity. Elite selection: Selecting N individuals from high-ranking, highly crowded individuals to form the parent individuals of the next generation. At the same time, the Pareto optimal frontier individuals of the previous generation are retained to the next generation to avoid the loss of excellent solutions.

[0106] Cross-operation – Constraint-compliant fragment exchange Using a single-point or multi-point crossover strategy, parent individuals are paired up to exchange partial gene fragments and generate offspring with their own genes. The crossover probability pc ranges from 0.6 to 0.9. During the crossover process, it is necessary to ensure that the offspring individuals still satisfy the insertion constraints. Two parent individuals, X1 and X2, are randomly selected; Randomly generate a crossover point k, and swap the gene fragments after k in X1 and X2 (new facility types added in the aggregation space vector). For the generated offspring individuals Perform constraint checks; if the insertion constraints are violated, revert to the parent gene fragment and make local corrections (delete the non-compliant facility configuration) to satisfy the constraints.

[0107] Check whether the crossover meets the planned area and facility requirements. If not, repeat the variation operation.

[0108] Each time a facility is modified, the space carrier is updated. Collection of implantation facilities and will " "、...、" Change the corresponding column in the blank to 1 or 0, and update the remaining space. , 、( .

[0109] Mutation Operations – Local Perturbation and Constraint Repair The mutation strategy employed is a flip mutation, randomly flipping a gene position in the chromosome (from 1 to 1 or from 1 to 0). The mutation probability pm ranges from 0.01 to 0.1. Constraint repair is required after mutation. Randomly select a gene from chromosome X Reverse its value ("A_em" changes from 1 to 0 or 0 to 1); If the flip results in a violation of site constraints (insufficient remaining space, shape mismatch) or mutual exclusion of facilities, then the mutation operation shall be revoked. Mutation operations aim to introduce population diversity and prevent the algorithm from getting trapped in local optima.

[0110] Check whether the modified version meets the area and facility requirements in the plan. If not, repeat the modification operation.

[0111] Each time a facility is modified, the space carrier is updated. Collection of implantation facilities and will " "、...、" Change the corresponding column in the blank to 1 or 0, and update the remaining space. , 、( .

[0112] Iterative convergence judgment Referring to the general convergence criteria in the field of multi-objective optimization of urban and rural spaces and authoritative books and literature in the field of genetic algorithms such as "Genetic Algorithms" (Wang Xiaoping), a maximum number of iterations is set. (e.g., 200-500 generations), and the convergence threshold (generally) During the iteration process, the changes in the Pareto optimal frontier are continuously monitored: in, Let be the Pareto optimal solution set for the t-th generation. for The nearest neighbor in the previous generation Pareto front.

[0113] The iteration terminates when any of the following conditions are met: The number of iterations reached ; Pareto optimal frontier change over consecutive generations T (e.g., 5 generations) < This means that the population has converged to a stable Pareto optimal solution set.

[0114] After terminating the iteration, start from the Pareto optimal frontier of the final population. In the process, the output is the layout scheme that satisfies the constraints and has the optimal overall fitness function benefit: 1) Selection of Pareto optimal solution set: All individuals in the study meet the placement constraints and planning area and facility type standards, and no individual can improve other reward indicators without reducing at least one reward indicator, thus achieving Pareto optimality under multiple objectives. 2) Selection of the overall optimal solution: If a single optimal solution needs to be output, the solution with the highest overall benefit can be selected from the Pareto optimal frontier solution set based on decision preferences (such as indicator weights). 3) Scheme Mapping and Visualization: Output the optimal chromosome X Medium space carrier collection Ultimately, this yields the spatial carriers within the Xth community living circle unit. area ( ),shape(( ), comprehensive potential ( ), existing facilities (" " "、...、" ”), new facilities (“ " "、...、" Summary of newly added facilities () ), remaining area ( ), remaining shapes (( )information.

[0115] Data analysis and summarization at different levels can be conducted based on research needs (such as calculating the total number and types of facilities included in the 15-minute, 10-minute, and 5-minute living circle levels respectively; and statistically analyzing the facility composition of multiple community living circle units).

[0116] In this example, taking living circle 24 as an example, the overall optimal solution is output as follows: Figure 10 Among them, red represents newly added outdoor fitness facilities, and light yellow represents existing outdoor fitness facilities.

[0117] Example 2: To achieve the above objectives, based on Example 1, this invention discloses an intelligent supplementation system for outdoor fitness facilities in a living area based on a genetic algorithm, comprising: The data acquisition module 11 is used to acquire outdoor fitness-related data, which includes spatial carrier data, current outdoor facility data, and residential land data; the outdoor fitness-related data is acquired based on a preset research scope. The data processing module 12 is used to identify and determine the attributes of the spatial carrier data to obtain the physical attributes and comprehensive potential of the spatial carrier; determine the placement requirements of outdoor fitness facilities based on the preset facility plan; and overlay the spatial carrier data and the existing outdoor facility data to determine the available area of ​​the spatial carrier based on the overlay result. The facility layout module 13 is used to input spatial carrier data, spatial carrier physical attributes, spatial carrier comprehensive potential, existing outdoor facility data, residential land data, available area of ​​spatial carrier, and outdoor fitness facility placement requirements into a pre-established genetic algorithm model, and output the optimal outdoor fitness facility layout scheme.

[0118] Based on the same inventive concept, this invention also provides a computer device, comprising: one or more processors, and a memory for storing one or more computer programs; the programs include program instructions, and the processor executes the program instructions stored in the memory. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, used to implement one or more instructions, specifically for loading and executing one or more instructions stored in a computer storage medium to implement the above-described method.

[0119] It should be further explained that, based on the same inventive concept, the present invention also provides a computer storage medium storing a computer program, which, when executed by a processor, performs the above-described method. This storage medium can be any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In the present invention, the computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0120] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this disclosure. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0121] The foregoing has shown and described the basic principles, main features, and advantages of this disclosure. Those skilled in the art should understand that this disclosure is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of this disclosure. Various changes and modifications can be made to this disclosure without departing from its spirit and scope, and all such changes and modifications fall within the scope of this disclosure as claimed.

Claims

1. A method for intelligently supplementing outdoor fitness facilities in a living circle based on a genetic algorithm, characterized in that, The method includes the following steps: Acquire outdoor fitness-related data, which includes spatial carrier data, existing outdoor facility data, and residential land data; the outdoor fitness-related data is acquired based on a predetermined research scope. The spatial carrier data is analyzed for attributes to obtain the physical attributes and comprehensive potential of the spatial carrier; the placement requirements of outdoor fitness facilities are determined based on the pre-planned facilities; the spatial carrier data and the existing outdoor facility data are overlaid, and the usable area of ​​the spatial carrier is determined based on the overlay results. The spatial carrier data, physical attributes of the spatial carrier, comprehensive potential of the spatial carrier, existing outdoor facility data, residential land data, available area of ​​the spatial carrier, and placement requirements of outdoor fitness facilities are input into a pre-established genetic algorithm model, and the optimal layout scheme of outdoor fitness facilities is output.

2. The intelligent supplementation method for outdoor fitness facilities in a living circle based on a genetic algorithm according to claim 1, characterized in that, The outdoor fitness-related data were collected by dividing each neighborhood within the preset research scope into community living circle units of preset area based on urban main roads, urban water systems, and urban mountains.

3. The intelligent supplementation method for outdoor fitness facilities in a living circle based on a genetic algorithm according to claim 1, characterized in that, The physical attributes of the spatial carrier include the area and shape attributes of the spatial carrier, and the comprehensive potential of the spatial carrier includes environmental potential and land potential; The environmental potential is determined by the comprehensive environment of the community living circle unit, including at least one of the following: surrounding activity level, facility richness, environmental pleasantness, and transportation accessibility. The potential of the land parcel is determined by the properties of the spatial carrier itself, including at least one of surface cover, vegetation composition, and land parcel enclosure.

4. The intelligent supplementation method for outdoor fitness facilities in a living circle based on genetic algorithm according to claim 1, characterized in that, The process of overlaying spatial carrier data and existing outdoor facility data, and determining the usable area of ​​the spatial carrier based on the overlay result, is as follows: Spatial overlay of spatial carrier data and existing outdoor facility data is used to determine the area of ​​existing outdoor facilities within the spatial carrier. The usable area of ​​the space is obtained by subtracting the area of ​​the existing outdoor facilities from the area of ​​the space carrier.

5. The intelligent supplementation method for outdoor fitness facilities in a living circle based on a genetic algorithm according to claim 1, characterized in that, The processing procedure of the pre-established genetic algorithm model is as follows: The residential land data is divided into living circles based on the preset DBSCAN density clustering algorithm to obtain the range of multi-level living circles. Based on the demand for outdoor fitness facilities and the current data on outdoor facilities, the missing amount of outdoor fitness facilities in the multi-level living circles is determined as the outdoor facilities to be added. Based on the physical properties of the spatial carriers, potential spatial carriers that meet the placement constraints of the outdoor facilities to be added are selected from the multi-level living circles; wherein, the placement constraints include site constraints and facility mutual exclusion constraints. Based on the comprehensive potential of the spatial carrier, determine the placement priority of the undetermined spatial carrier, select the undetermined spatial carrier with the highest placement priority to place the outdoor facilities to be added; generate an initial layout plan; The initial layout scheme is iteratively optimized based on a preset fitness function and a genetic algorithm. The layout scheme corresponding to the optimal fitness function is obtained through selection, crossover, and mutation operations, which serves as the optimal layout scheme for outdoor fitness facilities.

6. The intelligent supplementation method for outdoor fitness facilities in a living circle based on a genetic algorithm according to claim 5, characterized in that, The process of delineating residential areas based on the preset DBSCAN density clustering algorithm is as follows: Using the residential land vector surface of the residential land data as the clustering sample, the centroid coordinates of the residential land vector surface are used as the spatial location; Based on the DBSCAN density clustering algorithm, the clustering samples are clustered with a pre-set neighborhood radius and minimum clustering net number to obtain multiple clusters; For residential land within each cluster, the centroid coordinates are calculated using an area-weighted average. Using the center of the cluster as the delineation center of the living circle, and the preset standard walking distance corresponding to the living circle, a multi-radius buffer zone is generated as the range of the multi-level living circle.

7. The intelligent supplementation method for outdoor fitness facilities in a living circle based on a genetic algorithm according to claim 6, characterized in that, The site constraints are set as follows: Outdoor fitness equipment is configured on a spatial carrier. If the area and size meet the requirements, it is allowed to be placed in the spatial carrier; otherwise, it cannot be placed in the spatial carrier. The area requirement is set as follows: the minimum area and minimum size of the facility to be placed are both smaller than the available area of ​​the space carrier and the minimum size of the largest built-in rectangle of the remaining space. The mutual exclusion constraints for the facilities are set as follows: The same type of outdoor fitness equipment is not allowed to be placed in the same space.

8. The intelligent supplementation method for outdoor fitness facilities in a living circle based on a genetic algorithm according to claim 7, characterized in that, The fitness function includes at least one of the following metrics: facility richness, facility service coverage, and facility demand responsiveness.

9. A smart supplementation system for outdoor fitness facilities in a living circle based on a genetic algorithm, comprising the smart supplementation method for outdoor fitness facilities in a living circle based on a genetic algorithm as described in any one of claims 1 to 8, characterized in that, include: The data acquisition module is used to acquire outdoor fitness-related data, which includes spatial carrier data, current outdoor facility data, and residential land data; the outdoor fitness-related data is acquired based on a preset research scope. The data processing module is used to identify and determine the attributes of spatial carrier data to obtain the physical attributes and comprehensive potential of the spatial carrier; determine the placement requirements of outdoor fitness facilities based on the pre-set facility plan; and overlay the spatial carrier data and the existing outdoor facility data to determine the usable area of ​​the spatial carrier based on the overlay result. The facility layout module is used to input spatial carrier data, spatial carrier physical attributes, spatial carrier comprehensive potential, existing outdoor facility data, residential land data, available area of ​​spatial carrier, and the placement requirements of outdoor fitness facilities into a pre-established genetic algorithm model, and output the optimal layout scheme for outdoor fitness facilities.

10. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that, The memory stores a computer program that can run on a processor. When the processor loads and executes the computer program, it employs the intelligent supplementation method for outdoor fitness facilities in a living circle based on a genetic algorithm, as described in any one of claims 1 to 9.

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