A method, system and storage medium for siting public sports facilities

Abstract

The application discloses a public sports facility site selection method, system and storage medium, and comprises the following steps: constructing a city grid model according to obtained basic data of a to-be-evaluated region; distributing service capacity of a public sports facility to each fine-grained grid in the city grid model, and calculating service capacity values of different categories of public sports facilities in each administrative region for each age group; calculating a friendly degree of all public sports facilities in each administrative region for each age group and a supply-demand matching degree of different categories of public sports facilities for all groups according to the service capacity values; generating an optimization strategy according to the friendly degree and the supply-demand matching degree; and optimizing public sports facility site selection of the to-be-evaluated region according to the optimization strategy. The embodiment of the application can adapt to rapid changes in a current city population structure, and provides a more efficient, detailed and scientific site selection decision scheme for optimizing the layout scale of city public sports facilities.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of urban planning and design, and particularly relates to a public sports facility site selection method and system and a storage medium. BACKGROUND

[0002] Public service facilities are various public and service facilities that provide public service products for citizens, including cultural, educational, medical, sports and other facilities. Sports facilities are a kind of public service facilities. With the development and progress of society and the continuous improvement of living standards, the contradiction between people's increasing demand for a better life and the lagging public sports facility system gradually appears. The insufficient supply, low quality and weak targeting of public sports facilities have become a short board that restricts the high-quality development of cities.

[0003] With the development of China's urbanization process, the population structure of cities is always in dynamic evolution, and the supply and demand relationship between various public services and facilities of cities and the population is also in a dynamic development and change. The previous research method of observing the balance between the supply and demand of public sports facilities and population demand from a static perspective cannot adapt to the rapid changes in the population structure of cities. SUMMARY

[0004] The technical problem to be solved by the present application is to provide a public sports facility site selection method, system and storage medium that can adapt to the rapid changes in the population structure of cities and provide more efficient, detailed and scientific site selection decision-making schemes for optimizing the layout scale of urban public sports facilities.

[0005] To solve the above technical problems, the present application provides a public sports facility site selection method, comprising:

[0006] Obtaining basic data of an area to be evaluated; the basic data includes public sports facility data, city road network data, city population distribution data and city administrative division data;

[0007] According to the basic data, a city grid model is constructed; the fine-grained grid of the city grid model is divided based on the city population distribution data, and the coarse-grained grid is divided based on the city administrative division data;

[0008] In the city grid model, the service capacity of public sports facilities is allocated to each fine-grained grid, and the service capacity value of different categories of public sports facilities to each age group in each administrative area is calculated; the service capacity is obtained according to the use area of public sports facilities;

[0009] According to the service capacity value, the friendliness of all public sports facilities to each age group and the supply and demand matching degree of different categories of public sports facilities to all groups in each administrative area are calculated;

[0010] generate an optimization strategy according to the friendliness and the supply-demand matching degree; the optimization strategy is obtained by simulating changes in layout and scale of public sports facilities in the urban grid model;

[0011] optimize the public sports facility site selection of the to-be-evaluated area according to the optimization strategy.

[0012] As an improvement of the above scheme, the constructing an urban grid model according to the basic data comprises:

[0013] convert the public sports facility data into point features; the point features include facility levels, facility categories, and use areas;

[0014] convert the urban population distribution data into first surface features; the first surface features are fine-grained grids including total population and age group information;

[0015] convert the urban road network data into line features; the line features include urban road network information;

[0016] convert the urban administrative division data into second surface features; the second surface features are coarse-grained grids including administrative region boundary information;

[0017] construct an urban network model according to the point features, the first surface features, the line features, and the second surface features.

[0018] As an improvement of the above scheme, the distributing service capacity of the public sports facilities to each fine-grained grid in the urban grid model and calculating service capacity values of different categories of public sports facilities for each age group in each administrative region comprises:

[0019] calculate maximum travel times of each fine-grained grid and each public sports facility in the urban grid model to obtain service ranges of the public sports facilities;

[0020] calculate service distances of each fine-grained grid and each public sports facility, and combine the service ranges to obtain total demand coefficients of the public sports facilities;

[0021] calculate first service capacities of the public sports facilities distributed to each fine-grained grid according to the total demand coefficients;

[0022] calculate second service capacities of the public sports facilities distributed to each age group in each fine-grained grid according to the first service capacities, as the service capacity values.

[0023] As an improvement of the above scheme, the maximum travel time of each fine-grained grid and each public sports facility is calculated in the urban grid model to obtain the service range of the public sports facility, including:

[0024] In the urban grid model, each fine-grained grid and each public sports facility is traversed, and the travel time is calculated according to the urban road network data;

[0025] The fine-grained grid with a travel time not greater than the preset maximum travel time threshold of the public sports facility is screened as the service range of the public sports facility.

[0026] As an improvement of the above scheme, the service distance of each fine-grained grid and each public sports facility is calculated, and the total demand coefficient of the public sports facility is obtained in combination with the service range, including:

[0027] According to the urban road network data, the service distance of each fine-grained grid and each public sports facility is calculated;

[0028] Through N kij =G(d kij ,d ki0 )∑ m R jm P km , The total demand coefficient N kij of the fine-grained grid j to the public sports facility ki is calculated; wherein m is the label of different age groups; R jm is the number of group m in the fine-grained grid j; P km is the preference degree of group m to k type public sports facilities; G(d kij , d ki0 ) is a Gaussian decreasing function; d kij is the service distance of the public sports facility ki to the fine-grained grid j, and d ki0 is the maximum service distance of the public sports facility ki.

[0029] As an improvement of the above scheme, the first service capacity of the public sports facility allocated to each fine-grained grid is calculated according to the total demand coefficient, including:

[0030] Through The first service capacity S kij of the public sports facility ki allocated to the fine-grained grid j is calculated; wherein S ki is the service capacity of the public sports facility ki; N kij is the total demand coefficient N kij of the fine-grained grid j to the public sports facility ki.

[0031] As an improvement of the above scheme, the second service capacity of the public sports facilities allocated to each age group in each fine-grained grid is calculated according to the first service capacity as a service capacity value, including:

[0032] By calculating the second service capacity S of the public sports facilities ki allocated to the group m in the fine-grained grid j kijm , as a service capacity value; wherein S kij is the first service capacity of the public sports facilities ki allocated to the fine-grained grid j; R jm represents the number of the group m in the fine-grained grid j; P km represents the preference degree of the group m to the k type of public sports facilities.

[0033] As an improvement of the above scheme, the second service capacity of the public sports facilities allocated to each age group in each fine-grained grid is calculated according to the first service capacity as a service capacity value, including:

[0034] By calculating the per capita service capacity of the k type of public sports facilities to the group m in the administrative region H;

[0035] By AS Hm =∑ k AS Hkm calculating the total service capacity of all public sports facilities to the group m in the administrative region H;

[0036] By calculating the friendliness of all public sports facilities to the group m in the administrative region H;

[0037] By calculating the per capita service capacity of the k type of public sports facilities to all groups in the administrative region H;

[0038] By calculating the supply-demand matching degree of the k type of public sports facilities to all groups in the administrative region H;

[0039] Wherein S Hkm is the total service capacity of the k type of public sports facilities to the group m in the administrative region H; R Hm is the total number of the group m in the administrative region H; S Hk is the total service capacity of the k type of public sports facilities to all groups in the administrative region H; R H is the total population of the administrative region H; R j is the population number of the fine-grained grid j; S kij is the first service capacity; R All is the total population number of the region to be evaluated; S All-ktotal service capacity of the k-type public sports facilities in the to-be-evaluated region; AS All-k per capita service capacity of the k-type public sports facilities in the to-be-evaluated region.

[0040] The embodiment of the present application further provides a site selection system of public sports facilities, which comprises:

[0041] a data acquisition module, configured to acquire basic data of a to-be-evaluated region; the basic data comprises public sports facility data, city road network data, city population distribution data and city administrative division data;

[0042] a model construction module, configured to construct a city grid model according to the basic data; fine-grained grids of the city grid model are divided based on the city population distribution data, and coarse-grained grids are divided based on the city administrative division data;

[0043] a service capacity value calculation module, configured to distribute service capacity of public sports facilities to each fine-grained grid in the city grid model, and calculate service capacity values of different categories of public sports facilities for each age group in each administrative region; the service capacity is obtained according to a use area of the public sports facilities;

[0044] an index calculation module, configured to calculate a friendliness of all public sports facilities for each age group and a supply-demand matching degree of different categories of public sports facilities for all groups in each administrative region according to the service capacity values;

[0045] an optimization strategy generation module, configured to generate an optimization strategy according to the friendliness and the supply-demand matching degree; the optimization strategy is obtained by simulating changes in layout and scale of the public sports facilities in the city grid model;

[0046] a site selection module, configured to optimize site selection of public sports facilities in the to-be-evaluated region according to the optimization strategy.

[0047] The embodiment of the present application further provides a computer readable storage medium, comprising a stored computer program, wherein the computer readable storage medium controls a device where the computer readable storage medium is located to execute a site selection method of public sports facilities according to any one of the above when the computer program runs.

[0048] Compared with the prior art, the site selection method, system and storage medium of the public sports facility provided by the application can obtain basic data of an area to be evaluated, wherein the basic data comprises public sports facility data, city road network data, city population distribution data and city administrative division data; a city grid model is constructed according to the basic data; a fine-grained grid of the city grid model is divided based on the city population distribution data, and a coarse-grained grid is divided based on the city administrative division data; in the city grid model, the service capacity of the public sports facility is distributed to each fine-grained grid, and the service capacity value of different categories of public sports facilities to each age group in each administrative region is calculated; the service capacity is obtained according to the use area of the public sports facility; the friendliness of all public sports facilities to each age group and the supply-demand matching degree of different categories of public sports facilities to all groups in each administrative region are calculated according to the service capacity value; an optimization strategy is generated according to the friendliness and the supply-demand matching degree; the optimization strategy is obtained by simulating the change of the layout and size of the public sports facility in the city grid model; and the site selection of the public sports facility in the area to be evaluated is optimized according to the optimization strategy. By adopting the embodiment of the application, the rapid change of the current city population structure can be adapted, and a more efficient, detailed and scientific site selection decision scheme for the layout and size optimization of the city public sports facility is provided. BRIEF DESCRIPTION OF DRAWINGS

[0049] Figure 1 is a step flow schematic diagram of a site selection method of a public sports facility provided by an embodiment of the application;

[0050] Figure 2 is a structural schematic diagram of a site selection system of a public sports facility provided by an embodiment of the application. DETAILED DESCRIPTION

[0051] The technical solutions in the embodiments of the application will be clearly and completely described in the embodiments of the application in combination with the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, rather than all the embodiments of the application. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative work fall within the protection scope of the application.

[0052] In the description and claims of the specification, it is to be understood that the terms first, second, etc. are used only for the purpose of description and are not to be construed as indicating or implying relative importance or an indicated number of features. They are also not necessarily used to describe a sequence or an order, unless explicitly stated otherwise. The terms are interchangeable under appropriate circumstances. Thus, a feature described as "first" can be construed as "second" or "third", depending on the circumstances. The features described as "first", "second", etc. can explicitly or implicitly include at least one of the features.

[0053] Further, in the description of the present application, "a plurality of" means two or more, unless otherwise specified. The association relationship of "and / or" describes the association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B can represent the three cases of A existing alone, A and B existing together, and B existing alone. The character " / " generally represents an "or" relationship between the associated objects before and after it.

[0054] Please refer to Figure 1 The embodiment of the present application provides a step flow diagram of a public sports facility site selection method. In the embodiment, the public sports facility site selection method is specifically executed through steps S1 to S6.

[0055] S1, acquiring basic data of an evaluation area; the basic data includes public sports facility data, city road network data, city population distribution data and city administrative division data.

[0056] In some embodiments, the city road network data, the city population distribution data and the city administrative division data in the basic data are collected in an open source data platform. When the existing public sports facilities are reselected, the public sports facility data is the data of the existing public sports facilities in the evaluation area, which can also be collected through the open source data platform; when the evaluation area is planned for public sports facilities, the public sports facility data is the data in the public sports facility planning scheme.

[0057] In some embodiments, after the basic data is collected, a spatial correction algorithm is used to match the coordinates of the basic data with the elevation data, and unify the data format of the basic data.

[0058] S2, constructing a city grid model according to the basic data; the fine-grained grid of the city grid model is divided based on the city population distribution data, and the coarse-grained grid is divided based on the city administrative division data.

[0059] By constructing the city grid model with multiple granularities, the basic data can be analyzed from different scales. It should be noted that in the embodiment of the present application, the fine-grained grid is divided based on the city population distribution data, and the division of the fine-grained grid can be according to a preset size or according to the characteristics of the population distribution.

[0060] S3, in the city grid model, the service capacity of the public sports facilities is allocated to each fine-grained grid, and the service capacity value of different categories of public sports facilities to each age group in each administrative area is calculated; the service capacity is obtained according to the use area of the public sports facilities.

[0061] According to the embodiment, the service capacity value of the public sports facilities can be calculated from three dimensions of administrative region, category of public sports facilities and age group, so as to adapt to the rapid change of urban population structure and consider the differentiated needs of different age groups for different categories of public sports facilities.

[0062] S4, according to the service capacity value, the friendliness of all public sports facilities in each administrative region to each age group and the supply-demand matching degree of different categories of public sports facilities to all groups are calculated.

[0063] It should be noted that by calculating the friendliness of all public sports facilities in each administrative region to each age group, the layout and scale of public sports facilities can be adjusted for different age groups; by calculating the supply-demand matching degree of different categories of public sports facilities in each administrative region to all groups, the matching of the category of public service facilities and the age structure of the internal population of the administrative region can be obtained, so as to further optimize the category of public sports facilities.

[0064] S5, according to the friendliness and the supply-demand matching degree, an optimization strategy is generated; the optimization strategy is obtained by simulating the change of the layout and scale of public sports facilities in the city grid model.

[0065] In some embodiments, the optimization strategy includes two aspects: one is to determine whether the service capacity for a certain group needs to be improved or a certain category of public sports facilities needs to be added / replaced according to the friendliness and the supply-demand matching degree, to obtain an optimization direction, so that the layout of public sports facilities is more reasonable; the other is to adjust the layout and scale of public sports facilities in the city grid model according to the optimization direction, and iteratively calculate the friendliness and the supply-demand matching degree until the requirements are met.

[0066] S6, according to the optimization strategy, the public sports facility site selection of the to-be-evaluated region is optimized.

[0067] In the above scheme, considering the differentiated needs of different age groups for public sports facilities and the matching of the category of public sports facilities and the age structure of the population, the optimization strategy proposed therefrom can adapt to the rapid change of the current urban population structure and provide a more efficient, detailed and scientific site selection decision scheme for the layout and scale optimization of urban public sports facilities.

[0068] As a preferred embodiment, step S2, according to the basic data, a city grid model is constructed, specifically including:

[0069] The public sports facility data is converted into point elements; the point elements include facility level, facility category and use area;

[0070] convert the urban population distribution data into first surface elements; the first surface elements are fine-grained grids including total population and age group information;

[0071] convert the urban road network data into line elements; the line elements include urban road network information;

[0072] convert the urban administrative division data into second surface elements; the second surface elements are coarse-grained grids including administrative region boundary information;

[0073] construct a city network model according to the point elements, the first surface elements, the line elements, and the second surface elements.

[0074] As a preferred embodiment, step S3, in the city grid model, the service capacity of public sports facilities is allocated to each fine-grained grid, and the service capacity value of different categories of public sports facilities for each age group in each administrative region is calculated, which is specifically implemented through steps S31 to S34:

[0075] S31, in the city grid model, the maximum travel time of each fine-grained grid and each public sports facility is calculated to obtain the service range of the public sports facility.

[0076] Preferably, step S31 specifically includes:

[0077] In the city grid model, each fine-grained grid and each public sports facility is traversed, and the travel time is calculated according to the urban road network data;

[0078] The fine-grained grid with a travel time not greater than a preset maximum travel time threshold of the public sports facility is screened as the service range of the public sports facility.

[0079] In some embodiments, the public sports facilities are divided into regional planning level, town level, and community level, and when obtaining the service range of the public sports facility, referring to Table 1, the fine-grained grid with a travel time not greater than a preset maximum travel time threshold of the public sports facility is screened through analysis of the city road network data model.

[0080] Table 1 Maximum travel time threshold table of public sports facilities of different levels

[0081] Level of public sports facilities Transportation mode Maximum travel time threshold (minutes) Regional planning level Public transportation 40 Township level Cycling 20 Residential committee level Walking 10

[0082] S32, calculate the service distance of each fine-grained grid and each public sports facility, and combine the service range to obtain the total demand coefficient of the public sports facility.

[0083] Preferably, step S32 specifically includes:

[0084] According to the urban road network data, the service distance of each fine-grained grid to each public sports facility is calculated.

[0085] By N kij =G(d kij ,d ki0 )∑ m R jm P km , The total demand coefficient N kij of the fine-grained grid j to the public sports facility ki is calculated; wherein m is the label of different age groups; r jm is the number of group m in the fine-grained grid j; P km is the preference degree of group m to k type public sports facility; G(d kij ,d ki0 ) is a Gaussian decreasing function; d kij is the service distance of the public sports facility ki to the fine-grained grid j, and d ki0 is the maximum service distance of the public sports facility ki.

[0086] In some embodiments, when the preference degree of different groups to each type of public sports facility is obtained, referring to Table 2, the preference degree of group m to k type public sports facility can be directly read from Table 2.

[0087] Table 2 Preference degree of each age group to each type of public sports facility

[0088]

[0089] S33, according to the total demand coefficient, the first service capacity of the public sports facility allocated to each fine-grained grid is calculated.

[0090] Further, as a preferred embodiment, step S33 is specifically:

[0091] By the first service capacity S kij of the public sports facility ki allocated to the fine-grained grid j is calculated; wherein S ki is the service capacity of the public sports facility ki; N kij is the total demand coefficient N kij of the fine-grained grid j to the public sports facility ki.

[0092] S34, according to the first service capacity, the second service capacity of the public sports facility allocated to each age group in each fine-grained grid is calculated as the service capacity value.

[0093] In some preferred embodiments, step S34 is specifically:

[0094] By calculating the second service capacity S of the public sports facility ki to the group m in the fine-grained grid j kijm , as the service capacity value; wherein, S kij is the first service capacity of the public sports facility ki to the fine-grained grid j; R jm represents the number of the group m in the fine-grained grid j; P km represents the preference degree of the group m to the k type of public sports facility.

[0095] Further, as a preferred embodiment, step S4, according to the service capacity value, calculates the friendliness of all public sports facilities in each administrative district to each age group and the supply-demand matching degree of different types of public sports facilities to all groups, specifically:

[0096] By calculating the per capita service capacity of the k type of public sports facility to the group m in the administrative district H;

[0097] By AS Hm =∑ k AS Hkm calculating the total service capacity of all public sports facilities to the group m in the administrative district H;

[0098] By calculating the friendliness of all public sports facilities to the group m in the administrative district H;

[0099] By calculating the per capita service capacity of the k type of public sports facility to all groups in the administrative district H;

[0100] By calculating the supply-demand matching degree of the k type of public sports facility to all groups in the administrative district H;

[0101] wherein, S Hkm is the total service capacity of the k type of public sports facility to the group m in the administrative district H; R Hm is the total number of the group m in the administrative district H; S Hk is the total service capacity of the k type of public sports facility to all groups in the administrative district H; R H is the total population of the administrative district H; R j is the population number of the fine-grained grid j; S kij is the first service capacity; R All is the total population number of the region to be evaluated; S All-k is the total service capacity of the k type of public sports facility in the region to be evaluated; AS All-k is the per capita service capacity of the k type of public sports facility in the region to be evaluated.

[0102] In some embodiments, when O Hm is equal to 1, it indicates that the friendliness of all public sports facilities in the administrative region H to the group m is at the average level in the region to be evaluated; when O Hm is less than 1, it indicates that the friendliness of all public sports facilities in the administrative region H to the group m is lower than the average level in the region to be evaluated, and the optimization strategy includes "suggesting to increase the group m-friendly facilities"; when O Hm is greater than 1, it indicates that the friendliness of all public sports facilities in the administrative region H to the group m is higher than the average level in the region to be evaluated, and the optimization strategy includes "suggesting to build a group m-friendly community / block".

[0103] In some embodiments, when Q Hk is equal to 1, it indicates that the supply-demand matching degree of the k type of public sports facilities to all groups in the administrative region H is at the average level in the region to be evaluated; when Q Hk is less than 1, it indicates that the supply-demand matching degree of the k type of public sports facilities to all groups in the administrative region H is lower than the average level in the region to be evaluated, and the optimization strategy includes "suggesting to increase the supply of the k type of public sports facilities in the administrative region H"; when Q Hk is greater than 1, it indicates that the supply-demand matching degree of the k type of public sports facilities to all groups in the administrative region H is higher than the average level in the region to be evaluated, and the optimization strategy includes "suggesting to replace the k type of public sports facilities in the administrative region H with other public sports facilities below the average level".

[0104] By using the public sports facility site selection method provided in the embodiments of the present application, the differentiated needs of different age groups for public sports facilities and the matching of the types of public sports facilities and the population age are considered, and the optimization strategy proposed thereby can adapt to the rapid changes in the current urban population structure, and provide a more efficient, detailed and scientific site selection decision scheme for the layout and scale optimization of urban public sports facilities.

[0105] Referring to Figure 2 , the embodiments of the present application provide a structural schematic diagram of a public sports facility site selection system. The public sports facility site selection system comprises a data acquisition module 11, a model construction module 12, a service capacity value calculation module 13, an index calculation module 14 and an optimization strategy generation module 15, wherein:

[0106] The data acquisition module 11 is used to acquire the basic data of the region to be evaluated; the basic data comprises public sports facility data, urban road network data, urban population distribution data and urban administrative division data;

[0107] The model construction module 12 is configured to construct a city grid model according to the basic data; the fine-grained grid of the city grid model is divided based on the city population distribution data, and the coarse-grained grid is divided based on the city administrative division data;

[0108] The service capacity value calculation module 13 is configured to assign the service capacity of the public sports facilities to each fine-grained grid in the city grid model, and calculate the service capacity values of different categories of public sports facilities for each age group in each administrative region; the service capacity is obtained according to the use area of the public sports facilities;

[0109] The index calculation module 14 is configured to calculate the friendliness of all public sports facilities for each age group and the supply-demand matching degree of different categories of public sports facilities for all groups in each administrative region according to the service capacity values;

[0110] The optimization strategy generation module 15 is configured to generate an optimization strategy according to the friendliness and the supply-demand matching degree; the optimization strategy is obtained by simulating the change of the layout and scale of the public sports facilities in the city grid model;

[0111] The site selection module 16 is configured to optimize the site selection of the public sports facilities in the to-be-evaluated region according to the optimization strategy.

[0112] As a preferred implementation, the model construction module 12 is specifically configured to:

[0113] convert the public sports facility data into point elements; the point elements include facility levels, facility categories and use areas;

[0114] convert the city population distribution data into first surface elements; the first surface elements are fine-grained grids including total population and age group information;

[0115] convert the city road network data into line elements; the line elements include city road network information;

[0116] convert the city administrative division data into second surface elements; the second surface elements are coarse-grained grids including administrative region boundary information;

[0117] construct the city network model according to the point elements, the first surface elements, the line elements and the second surface elements.

[0118] As a preferred implementation, the service capacity value calculation module 13 is specifically configured to:

[0119] calculate the maximum travel time of each fine-grained grid and each public sports facility in the city grid model, and obtain the service range of the public sports facilities;

[0120] The service distance between each fine-grained grid and each public sports facility is calculated, and the total demand coefficient of the public sports facility is obtained by combining the service range;

[0121] According to the total demand coefficient, the first service capacity of the public sports facility allocated to each fine-grained grid is calculated;

[0122] According to the first service capacity, the second service capacity of the public sports facility allocated to each age group in each fine-grained grid is calculated as the service capacity value.

[0123] Further, preferably, in the city grid model, the maximum travel time between each fine-grained grid and each public sports facility is calculated to obtain the service range of the public sports facility, including:

[0124] In the city grid model, each fine-grained grid and each public sports facility is traversed, and the travel time is calculated according to the city road network data;

[0125] The fine-grained grid with a travel time not greater than the preset maximum travel time threshold of the public sports facility is screened as the service range of the public sports facility.

[0126] As a preferred embodiment, the total demand coefficient of the public sports facility is obtained by calculating the service distance between each fine-grained grid and each public sports facility, and combining the service range, including:

[0127] According to the city road network data, the service distance between each fine-grained grid and each public sports facility is calculated;

[0128] Through N kij =G(d kij ,d ki0 )∑ m R jm P km , The total demand coefficient N kij of fine-grained grid j for public sports facility ki is calculated; wherein m is the label of different age groups; R jm is the number of group m in fine-grained grid j; P km is the preference degree of group m to k type public sports facility; G(d kij , d ki0 ) is a Gaussian decreasing function; d kij is the service distance from public sports facility ki to fine-grained grid j, and d ki0 is the maximum service distance of public sports facility ki.

[0129] Preferably, calculating the first service capacity of the public sports facilities allocated to each fine-grained grid based on the total demand coefficient includes:

[0130] pass Calculate the first service capacity S of public sports facility ki assigned to fine-grained grid j. kij Among them, S ki The service capacity of public sports facilities (ki); N kij The total demand coefficient N for public sports facilities ki for fine-grained grid j. kij .

[0131] In a preferred embodiment, the index calculation module 14 is specifically used for:

[0132] pass Calculate the per capita service capacity of class k public sports facilities in administrative region H for group m;

[0133] Through AS Hm =∑ k AS Hkm Calculate the total service capacity of all public sports facilities in administrative region H for group m;

[0134] pass Calculate the friendliness of all public sports facilities in administrative region H to group m;

[0135] pass Calculate the per capita service capacity of public sports facilities of type k in administrative region H for all groups;

[0136] pass Calculate the degree of supply-demand matching for all groups of public sports facilities of type k in administrative region H;

[0137] Among them, S Hkm The total service capacity of Class k public sports facilities in administrative region H for group m; R Hm S represents the total number of people in group m within administrative region H; Hk The total service capacity of Class k public sports facilities in Administrative Region H for all groups; R H R represents the total population of administrative region H; j S represents the population of fine-grained grid j; kij For primary service capability; R All S represents the total population of the area to be assessed. All-k The total service capacity of Class K public sports facilities in the area to be evaluated; AS All-k This refers to the per capita service capacity of Class K public sports facilities in the area to be evaluated.

[0138] The site selection system of the public sports facility provided by the embodiment of the application considers the differentiated needs of different age groups for the public sports facility and the matching of the category of the public sports facility and the population age, so that the optimization strategy proposed can adapt to the rapid change of the current urban population structure, and provide a more efficient, detailed and scientific site selection decision scheme for the layout and scale optimization of the urban public sports facility.

[0139] The application can be in the form of a computer program product implemented on one or more storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing program code. The computer-readable storage medium includes permanent and non-permanent, removable and non-removable media, and can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to: phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device.

[0140] The above embodiments only express several implementation manners of the application, the description is more specific and detailed, but it cannot be understood as a limitation on the scope of the patent. It should be pointed out that for ordinary skilled in the art, without departing from the concept of the application, several modifications and improvements can be made, which belong to the protection scope of the application.

Claims

1. A method for selecting the site of a public sports facility, characterized in that, include: Obtain basic data for the area to be evaluated; the basic data includes data on public sports facilities, urban road network, urban population distribution, and urban administrative divisions. Based on the aforementioned basic data, an urban grid model is constructed; the fine-grained grid of the urban grid model is divided based on the urban population distribution data, and the coarse-grained grid is divided based on the urban administrative division data. In the urban grid model, the service capacity of public sports facilities is allocated to each fine-grained grid, and the service capacity values ​​of different types of public sports facilities for different age groups in each administrative region are calculated; the service capacity is obtained based on the usable area of ​​the public sports facilities. Based on the service capacity values, calculate the friendliness of all public sports facilities in each administrative region to each age group and the supply-demand matching degree of different types of public sports facilities to all groups; An optimization strategy is generated based on the degree of friendliness and the degree of supply-demand matching; the optimization strategy is obtained by simulating changes in the layout and scale of public sports facilities in the urban grid model; Optimize the site selection of public sports facilities in the area to be evaluated based on the aforementioned optimization strategy; The calculation of the friendliness of all public sports facilities in each administrative region to different age groups and the supply-demand matching degree of different types of public sports facilities to all groups, based on the service capacity value, includes: pass Calculate the per capita service capacity of class k public sports facilities in administrative region H for group m; Through AS Hm =∑ k AS Hkm Calculate the total service capacity of all public sports facilities in administrative region H for group m; pass Calculate the friendliness of all public sports facilities in administrative region H to group m; pass Calculate the per capita service capacity of public sports facilities of type k in administrative region H for all groups; pass Calculate the degree of supply-demand matching for all groups of public sports facilities of type k in administrative region H; Among them, S Hkm The total service capacity of Class k public sports facilities in administrative region H for group m; R Hm S represents the total number of people in group m within administrative region H; kijm Assign service capacity values ​​to group m in fine-grained grid j for public sports facility ki; R jm S represents the number of population m in the fine-grained grid j; Hk The total service capacity of Class k public sports facilities in Administrative Region H for all groups; R H R represents the total population of administrative region H; j S represents the population of fine-grained grid j; kij For primary service capability; R All S represents the total population of the area to be assessed. All-k The total service capacity of Class K public sports facilities in the area to be evaluated; AS All-k This refers to the per capita service capacity of Class K public sports facilities in the area to be evaluated.

2. The method for selecting a site for a public sports facility as described in claim 1, characterized in that, The step of constructing a city grid model based on the basic data includes: The public sports facility data is converted into point features; the point features include facility level, facility category, and usable area. The urban population distribution data is converted into a first surface feature; the first surface feature is a fine-grained grid that includes information on the total number of people and age groups; The urban road network data is converted into line elements; the line elements include urban road network information. The urban administrative division data is converted into a second surface feature; the second surface feature is a coarse-grained grid that includes administrative region boundary information. A city network model is constructed based on the point features, the first surface features, the line features, and the second surface features.

3. The method for selecting a site for a public sports facility as described in claim 1, characterized in that, In the urban grid model, the service capacity of public sports facilities is allocated to each fine-grained grid, and the service capacity values ​​of different types of public sports facilities for different age groups within each administrative region are calculated, including: In the urban grid model, the maximum travel time between each fine-grained grid and each public sports facility is calculated to obtain the service range of the public sports facilities; Calculate the service distance between each fine-grained grid and each public sports facility, and combine this with the service range to obtain the total demand coefficient for public sports facilities; Based on the total demand coefficient, calculate the first service capacity of the public sports facilities allocated to each fine-grained grid; Based on the first service capacity, the second service capacity of the public sports facilities allocated to each age group in each fine-grained grid is calculated as the service capacity value.

4. The method for selecting a site for a public sports facility as described in claim 3, characterized in that, In the urban grid model, the maximum travel time between each fine-grained grid and each public sports facility is calculated to obtain the service area of ​​the public sports facilities, including: In the urban grid model, each fine-grained grid and each public sports facility is traversed, and the travel time is calculated based on the urban road network data; Fine-grained grids that are selected based on the travel time being no greater than the preset maximum travel time threshold of the public sports facility are used as the service area of ​​the public sports facility.

5. The method for selecting a site for a public sports facility as described in claim 3, characterized in that, The calculation of the service distance between each fine-grained grid and each public sports facility, combined with the service range, yields the total demand coefficient for public sports facilities, including: Based on the urban road network data, calculate the service distance between each fine-grained grid and each public sports facility; pass Calculate the total demand factor N for public sports facilities ki for fine-grained grid j. kij Where m represents the labels for different age groups; R jm P represents the number of population m in the fine-grained grid j; km G(d) represents the degree of preference of group m for class k public sports facilities; kij d ki0 ) is a Gaussian decreasing function; d kij For the service distance from public sports facility ki to fine-grained grid j, d ki0 The maximum service distance for public sports facilities (ki).

6. The method for selecting a site for a public sports facility as described in claim 5, characterized in that, The step of calculating the first service capacity of the public sports facilities allocated to each fine-grained grid based on the total demand coefficient includes: pass Calculate the first service capacity S of public sports facility ki assigned to fine-grained grid j. kij Among them, S ki The service capacity of public sports facilities (ki); N kij The total demand coefficient N for public sports facilities ki is given by the fine-grained grid j. kij .

7. The method for selecting a site for a public sports facility as described in claim 6, characterized in that, The step of calculating the second service capacity of the public sports facilities allocated to each age group in each fine-grained grid based on the first service capacity, as a service capacity value, includes: pass Calculate the second service capacity of public sports facilities ki assigned to group m in fine-grained grid j; where S kij Assign the first service capacity of public sports facilities ki to fine-grained grid j; R jm P represents the number of population m in the fine-grained grid j; km This indicates the degree of preference of group m for class k public sports facilities.

8. A site selection system for public sports facilities, characterized in that, include: The data acquisition module is used to acquire basic data of the area to be evaluated; the basic data includes public sports facility data, urban road network data, urban population distribution data, and urban administrative division data. The model building module is used to build a city grid model based on the basic data; the fine-grained grid of the city grid model is divided based on the city population distribution data, and the coarse-grained grid is divided based on the city administrative division data. The service capacity value calculation module is used to allocate the service capacity of public sports facilities to each fine-grained grid in the urban grid model, and calculate the service capacity value of different types of public sports facilities for different age groups in each administrative region; the service capacity is obtained based on the usable area of ​​the public sports facilities. The indicator calculation module is used to calculate, based on the service capacity value, the friendliness of all public sports facilities in each administrative region to groups of all ages and the supply and demand matching degree of different types of public sports facilities to all groups. An optimization strategy generation module is used to generate optimization strategies based on the friendliness level and the supply-demand matching degree; the optimization strategies are obtained by simulating changes in the layout and scale of public sports facilities in the urban grid model; The site selection module is used to optimize the site selection of public sports facilities in the area to be evaluated according to the optimization strategy. The indicator calculation module is specifically used for: pass Calculate the per capita service capacity of class k public sports facilities in administrative region H for group m; Through AS Hm =∑ k AS Hkm Calculate the total service capacity of all public sports facilities in administrative region H for group m; pass Calculate the friendliness of all public sports facilities in administrative region H to group m; pass Calculate the per capita service capacity of public sports facilities of type k in administrative region H for all groups; pass Calculate the degree of supply-demand matching for all groups of public sports facilities of type k in administrative region H; Among them, S Hkm The total service capacity of Class k public sports facilities in administrative region H for group m; R Hm S represents the total number of people in group m within administrative region H; kijm Assign service capacity values ​​to group m in fine-grained grid j for public sports facility ki; R jm S represents the number of population m in the fine-grained grid j; Hk The total service capacity of Class k public sports facilities in Administrative Region H for all groups; R H R represents the total population of administrative region H; j S represents the population of fine-grained grid j; kij For primary service capability; R All S represents the total population of the area to be assessed. All-k The total service capacity of Class K public sports facilities in the area to be evaluated; AS All-k This refers to the per capita service capacity of Class K public sports facilities in the area to be evaluated.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored computer program, wherein, when the computer program is executed, it controls the device on which the computer-readable storage medium is located to perform a site selection method for a public sports facility as described in any one of claims 1 to 7.

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