A method, system, intelligent terminal and storage medium for selecting a site for a public service facility

Abstract

The present application relates to a method, system, intelligent terminal and storage medium for site selection of public service facilities, and relates to the field of big data service technology. The method includes: dividing a block into a number of nodes according to the community block boundary; setting the node attributes of the node according to the population attributes of the node; calculating the first actual travel time from the public service facility to the node, and the second actual travel time from the node to the public service facility; constructing an adjacency matrix according to the first actual travel time and the second actual travel time to obtain a traffic accessibility matrix; combining the first actual travel time, performing a weighted operation on the node attributes to obtain a bearing pressure vector of the public service facility; calculating the product of the traffic accessibility matrix and the diagonal matrix of the bearing pressure vector to obtain a coverage matrix of the public server facility; and searching for the target node in the node according to the coverage matrix. The present application has the effect of providing a more accurate site selection of public service facilities.

Description

Technical Field

[0001] The present application relates to the field of big data service technology, and in particular to a method, system, intelligent terminal and storage medium for site selection of public service facilities. Background Art

[0002] Related technologies divide the block into several sub-blocks one by one through grids of equal size. Calculate the travel time from each sub-block to the public service facility and obtain the total population in each sub-block. Calculate the product of the travel time and the total population and use it as the traffic accessibility from the sub-block to the public service facility. Select the sub-block corresponding to the minimum traffic accessibility in the traffic accessibility as the sub-block where new public service facilities need to be built.

[0003] Regarding the above-mentioned related technologies, the irregularity of population clusters and the two-way accessibility between blocks are not taken into consideration, resulting in inaccurate site selection of public service facilities. Summary of the invention

[0004] In order to provide more accurate site selection for public service facilities, the present application provides a method, system, intelligent terminal and storage medium for site selection for public service facilities.

[0005] In the first aspect, the present application provides a method for selecting a site for a public service facility, using the following technical solution:

[0006] A method for selecting a site for a public service facility, comprising:

[0007] Divide the block into several nodes according to the community block boundaries;

[0008] According to the population attributes of the node, set the node attributes of the node;

[0009] Calculate a first actual travel time from a public service facility to a node, and a second actual travel time from a node to a public service facility;

[0010] Construct an adjacency matrix according to the first actual travel time and the second actual travel time to obtain a traffic accessibility matrix;

[0011] Combined with the first actual travel time, weighted operations are performed on node attributes to obtain the bearing pressure vector of the public service facility;

[0012] Calculate the product of the traffic accessibility matrix and the diagonal matrix of the load-bearing pressure vector to obtain the coverage matrix of the public server facilities. The coverage matrix is ​​used to record the distribution of the coverage corresponding to the node;

[0013] According to the coverage matrix, the target node is found among the nodes, and the community block corresponding to the target node is used to establish new public service facilities.

[0014] By adopting the above technical solution, the blocks are divided according to the community block boundaries, a number of nodes are obtained, and the first actual travel time and the second time travel time are calculated. The traffic accessibility matrix is ​​generated by the first actual travel time and the second time travel time, and the node attributes are weighted in combination with the first actual travel time to obtain the bearing pressure vector of the public service facility. The coverage matrix is ​​obtained through the traffic accessibility matrix and the bearing pressure vector. The coverage matrix is ​​used to determine which sub-blocks need to build new public service facilities. The division of blocks is carried out according to the community block boundaries, and the division of blocks is more accurate, which is conducive to obtaining more accurate block information and helping to accurately select nodes where new public service facilities need to be built.

[0015] Moreover, the coverage matrix is ​​obtained by integrating the traffic accessibility matrix and the carrying pressure vector, so that the coverage matrix can better reflect the relationship between nodes and public service facilities, which helps to select more accurate target nodes for the construction of public service facilities.

[0016] Optionally, the block is divided into several sub-blocks according to the community block boundaries;

[0017] According to the population distribution inside the sub-block, clustering operation is performed on the sub-block to obtain temporary nodes;

[0018] According to the population attributes, public transportation facilities and road conditions corresponding to the temporary nodes, the estimated travel time from the temporary nodes to the public service facilities is predicted;

[0019] According to the estimated travel time and the community area of ​​the temporary nodes, clustering operation is performed on the temporary nodes to obtain nodes.

[0020] By adopting the above technical solution, after using the community block boundary to divide the block into several sub-blocks, the population distribution is used to cluster the sub-blocks to obtain temporary nodes, and then the estimated travel time from the temporary nodes to the public service facilities is predicted according to the population attributes, public transportation facilities and road conditions corresponding to the temporary nodes, and clustering operations are performed again. The accuracy of node division can be effectively improved.

[0021] Optionally, count the total resident population and total floating population within the sub-block;

[0022] According to the total length of residence of the total floating population within the preset time, the total floating population is classified to obtain the total permanent floating population and the total temporary floating population;

[0023] According to the total permanent population and the total permanent floating population, clustering operations are performed on the sub-blocks to obtain the permanent population clustering results;

[0024] According to the total temporary floating population, clustering operation is performed on the sub-blocks to obtain the clustering results of the temporary population;

[0025] Take the union of the permanent population clustering results and the temporary population clustering results to obtain temporary nodes.

[0026] By adopting the above technical solution, the floating population is divided into permanent floating population and temporary floating population according to the total length of residence of the population, and the permanent population clustering results are determined based on the total permanent population and the total permanent floating population, and the temporary population clustering results are determined based on the total temporary floating population. Then, the temporary nodes are obtained by the union of the permanent population clustering results and the temporary population clustering results. The division of temporary nodes is more accurate, which is conducive to obtaining reasonable sub-blocks, and is convenient for subsequent analysis of the coverage of public service facilities in different sub-blocks, so as to obtain reasonable target nodes.

[0027] Optionally, obtain the total population, permanent population, permanent floating population, and temporary floating population within the node;

[0028] The first weight is calculated based on the permanent population, permanent floating population and total population;

[0029] The second weight is calculated based on the temporary floating population and the total population;

[0030] The first population density, first age structure, first occupation distribution and first travel mode of the permanent population and permanent floating population in the area where the statistical node is located;

[0031] According to the first age structure, the first occupation distribution and the first travel mode of the personnel, the first population density is updated to obtain a first attribute value;

[0032] The second population density, second age structure, second occupation distribution and second travel mode of the temporary floating population in the area where the statistical node is located;

[0033] According to the second age structure, the second occupation distribution and the second travel mode of the second personnel, the second population density is updated to obtain a second attribute value;

[0034] The first attribute value and the second attribute value are weighted by taking the first weight as the weight of the first attribute value and the second weight as the weight of the second attribute value, and weighted calculation is performed on the first attribute value and the second attribute value to obtain the population attribute.

[0035] By adopting the above technical solution, when calculating population attributes, temporary floating population, permanent floating population and permanent population are calculated separately, so that the population attributes can better represent the attributes of the node, which is convenient for subsequent analysis of the coverage of public service facilities to different sub-blocks, so as to obtain reasonable target nodes.

[0036] Optionally, count the total population and temporary floating population in the node;

[0037] When the number of temporary floating population accounts for a greater than preset proportion of the total population, the public transportation travel time and self-driving travel time from the public service facility to the node are counted; the public transportation travel time and self-driving travel time are weighted according to the preset weight value to obtain the first actual travel time;

[0038] When the number of temporary floating population to the total population is less than the preset proportion, the travel modes corresponding to the total permanent population and the total permanent floating population in the node are counted; the travel time corresponding to the travel mode is calculated; the travel time is weighted according to the proportion of the population of the travel mode corresponding to the travel time in the total permanent population, and the first actual travel time is obtained.

[0039] By adopting the above technical solution, the first actual travel time is calculated in different ways according to the proportion of the temporary floating population in the total population. The first actual travel time can better represent the population characteristics within the block, which is conducive to analyzing the coverage of public service facilities in different sub-blocks, so as to obtain reasonable target nodes.

[0040] Optionally, the total population is classified according to the type of public service facilities to obtain the effective population;

[0041] Normalizing the first actual travel time to obtain a bearing pressure weight value;

[0042] According to the bearing pressure weight value, the effective population is weighted and the bearing pressure vector is obtained.

[0043] By adopting the above technical solution, the total population is classified according to the type of public service facilities to obtain the effective population. The effective population can better represent the bearing pressure vector. The coverage of public service facilities to different sub-blocks is analyzed to obtain reasonable target nodes.

[0044] Optionally, count the permanent population, permanent floating population, and temporary floating population within the node;

[0045] The permanent population and the permanent floating population are classified according to the types of public service facilities to obtain the first effective population number;

[0046] Classify the temporary floating population according to the types of public service facilities to obtain the number of effective temporary population;

[0047] When public service facilities are the target type, the conversion ratio is generated according to the proportion of temporary floating population to the total population;

[0048] The second effective population is obtained by multiplying the conversion ratio by the effective temporary population.

[0049] The effective population is obtained according to the sum of the first effective population and the second effective population.

[0050] By adopting the above technical solution, the effective temporary population is converted according to the proportion of temporary floating population in the total population, and a more reasonable effective population is obtained. Therefore, the effective population can better represent the population characteristics in the block, which is conducive to obtaining a reasonable target node.

[0051] In the second aspect, the present application provides a public service facility site selection system, which adopts the following technical solution:

[0052] A public service facility site selection system, comprising:

[0053] The acquisition module is used to obtain the community block boundaries, blocks, population attributes, population distribution, total permanent population and total floating population;

[0054] A memory for storing a program of any one of the above public service facility site selection methods;

[0055] The program in the processor and the memory can be loaded and executed by the processor to implement any of the above-mentioned methods for selecting a site for a public service facility.

[0056] In a third aspect, the present application provides a smart terminal, which adopts the following technical solution:

[0057] An intelligent terminal comprises a memory and a processor, wherein the memory stores a computer program which can be loaded by the processor and execute any one of the above methods.

[0058] In a fourth aspect, the present application provides a computer storage medium capable of storing a corresponding program, which has the characteristic of facilitating the provision of more accurate site selection for public service facilities, and adopts the following technical solution:

[0059] A computer-readable storage medium stores a computer program that can be loaded by a processor and execute any of the above-mentioned public service facility site selection methods.

[0060] In summary, the present application includes at least one of the following beneficial technical effects:

[0061] The blocks are divided according to the community block boundaries to obtain several nodes, and the first actual travel time and the second time travel time are calculated. The traffic accessibility matrix is ​​generated by the first actual travel time and the second time travel time, and the node attributes are weighted in combination with the first actual travel time to obtain the bearing pressure vector of the public service facility. The coverage matrix is ​​obtained through the traffic accessibility matrix and the bearing pressure vector. The coverage matrix is ​​used to determine which sub-blocks need to build new public service facilities. The division of blocks is carried out according to the community block boundaries, and the division of blocks is more accurate, which is conducive to obtaining more accurate block information and helping to accurately select nodes that need to build new public service facilities;

[0062] The coverage matrix is ​​obtained by integrating the traffic accessibility matrix and the carrying pressure vector, so that the coverage matrix can better reflect the relationship between nodes and public service facilities, which helps to select more accurate target nodes to build public service facilities;

[0063] After using the community block boundary to divide the block into several sub-blocks, the population distribution is used to cluster the sub-blocks to obtain temporary nodes, and then the estimated travel time from the temporary nodes to the public service facilities is predicted according to the population attributes, public transportation facilities and road conditions corresponding to the temporary nodes, and clustering is performed again. This can effectively improve the accuracy of node division. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 It is a flow chart of a method for site selection of a public service facility disclosed in an embodiment of the present application.

[0065] Figure 2 It is a flow chart of a node division method based on the site selection of public service facilities disclosed in an embodiment of the present application.

[0066] Figure 3 It is a flow chart of a node division method based on the site selection of public service facilities disclosed in an embodiment of the present application.

[0067] Figure 4 It is a flow chart of a node division method based on the site selection of public service facilities disclosed in an embodiment of the present application.

[0068] Figure 5 It is a flow chart of a method for calculating travel time based on site selection of public service facilities disclosed in an embodiment of the present application.

[0069] Figure 6 It is a flow chart of a method for calculating bearing pressure based on site selection of public service facilities disclosed in an embodiment of the present application.

[0070] Figure 7It is a flowchart of a method for calculating the effective population quantity based on the site selection of public service facilities disclosed in an embodiment of the present application.

[0071] Figure 8 It is a schematic diagram of a public service facility site selection system disclosed in an embodiment of the present application. DETAILED DESCRIPTION

[0072] In order to make the purpose, technical solutions and advantages of this application more clear, the following Figure 1-8 It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0073] The present application embodiment discloses a method for selecting a site for a public service facility. Figure 1 , methods for site selection of public service facilities include:

[0074] Step S11: Divide the block into several nodes according to the community block boundaries.

[0075] The community block boundary refers to the boundary of the community block on the map, and the community block includes a residential area, an office building, an apartment, a lodging area, etc. Optionally, the community block boundary is divided according to the community name.

[0076] In some other implementations, when the area of ​​a block is larger than a preset area, the block is divided into a number of nodes according to the boundaries of buildings within the block.

[0077] In the present application, the number of index quantities reaches at least two.

[0078] Step S12: Setting the node attributes of the node according to the population attributes of the node.

[0079] Population attributes include at least one of population density, population size, age structure, travel mode, occupational distribution and household registration.

[0080] For example, a value is assigned according to the population attribute and used as the node attribute of the node. For example, if the population attribute is population density, the value corresponding to the population density is used as the node attribute of the node.

[0081] Furthermore, when the population attribute includes at least two of the above contents, the population attribute of the node is weighted to obtain the weighted sum of the attributes; the weighted sum of the attributes is set as the node attribute of the node. For example, taking the population attribute including the household registration of personnel and population density as an example, the value is assigned according to the type of household registration of personnel to obtain the assigned value; the assigned value and population density are weighted to obtain the weighted sum of the attributes, and it is used as the node attribute.

[0082] Step S13: Calculate a first actual travel time from a public service facility to a node, and a second actual travel time from a node to a public service facility.

[0083] Public service facilities include cultural facilities, sports facilities, educational facilities, entertainment facilities, administrative facilities, community service facilities, health facilities and transportation facilities.

[0084] The first actual travel time refers to the actual travel time required for people living in the node to travel from public service facilities to the node.

[0085] The second actual travel time refers to the actual travel time required for people living in the node to travel from the node to public service facilities.

[0086] It should be noted that in actual scenarios, the first actual communication time and the second travel time are not necessarily the same. For example, there is a one-way street on the road from the node to the public service facility. Residents can go directly from the node to the public service facility via the one-way street, but cannot go back from the public service facility to the node via the one-way street.

[0087] The first actual travel time and the second actual travel time can be obtained based on different transportation modes. For example, the travel modes of people in the node are counted; the actual travel time corresponding to different travel modes of people is calculated; the actual travel time is weighted according to the proportion of the number of people corresponding to the travel mode of the people in the total number of people, and the first actual travel time and the second actual travel time are obtained.

[0088] Step S14: construct an adjacency matrix according to the first actual travel time and the second actual travel time to obtain a traffic accessibility matrix.

[0089] The elements of the traffic accessibility matrix include the first actual travel time and the second actual travel time. The elements in the traffic accessibility matrix are represented by It means that if i corresponds to a public service facility and j corresponds to a node, then represents the first actual travel time from public service facility i to node j; if i corresponds to a node and j corresponds to a public service facility, then represents the second actual travel time from node i to public service facility j; in other cases, The value of is 0.

[0090] For example, the public service facility includes A, the nodes include M and N, and the first actual travel time from the public service facility A to the node M is , the first actual travel time from public service facility A to node N is , the second actual travel time from node M to public service facility A is , the first actual travel time from node N to public service facility A is . Then the adjacency matrix P is

[0091] .

[0092] Step S15: Perform a weighted operation on the node attributes in combination with the first actual travel time to obtain the bearing pressure vector of the public service facility.

[0093] The weight value obtained by the first actual travel time is negatively correlated with the first actual travel time. In this step, the first actual travel time may also be replaced by the second actual travel time, or may be replaced by the average of the first actual travel time and the second actual travel time.

[0094] In this step, the node attributes of several nodes are weighted in combination with the first actual travel time, so that the node attributes with a smaller first actual travel time obtain a larger weight, and the node attributes with a larger first actual travel time obtain a smaller weight. This is equivalent to a higher weight for easily accessible nodes and a lower weight for more difficult to reach nodes.

[0095] Exemplarily, the bearing pressure vector is recorded as Q=[q1, q2, ..., qx], wherein the element qx in the bearing pressure vector represents the bearing pressure of the public service facility x.

[0096] Step S16: Calculate the product of the traffic accessibility matrix and the diagonal matrix of the bearing pressure vector to obtain the coverage matrix of the public server facilities. The coverage matrix is ​​used to record the distribution of the coverage corresponding to the node.

[0097] The elements in the coverage matrix R are recorded as , when j represents a public service facility and i represents a node, Represents the coverage of public service facility j to node i.

[0098] Step S17: According to the coverage matrix, the target node is searched among the nodes, and the community block corresponding to the target node is used to establish a new public service facility.

[0099] Optionally, the coverage in the coverage matrix is ​​classified according to the type of public service facilities to obtain a coverage set, each coverage set including the coverage of a certain type of public service facilities on the node. The coverage in the coverage set is classified according to the node, and the coverage with the same node is divided into the same category to obtain a coverage combination. If each coverage in the coverage set is less than the preset coverage, it means that the current public service facility does not cover the corresponding node sufficiently, so the node corresponding to the target coverage is determined as the target node.

[0100] In summary, the blocks are divided according to the community block boundaries to obtain several nodes, and the first actual travel time and the second time travel time are calculated. The traffic accessibility matrix is ​​generated by the first actual travel time and the second time travel time, and the node attributes are weighted in combination with the first actual travel time to obtain the bearing pressure vector of the public service facility. The coverage matrix is ​​obtained through the traffic accessibility matrix and the bearing pressure vector. The coverage matrix is ​​used to determine which sub-blocks need to build new public service facilities. The division of blocks is carried out according to the community block boundaries, and the division of blocks is more accurate, which is conducive to obtaining more accurate block information and helping to accurately select nodes where new public service facilities need to be built.

[0101] Moreover, the coverage matrix is ​​obtained by integrating the traffic accessibility matrix and the carrying pressure vector, so that the coverage matrix can better reflect the relationship between nodes and public service facilities, which helps to select more accurate target nodes for the construction of public service facilities.

[0102] In the following embodiments, when dividing a block into several nodes, different people in the same block have different travel characteristics, which will lead to different travel times. Therefore, it is necessary to optimize the block division based on the characteristics of the people. Therefore, the embodiment of the present application discloses a node division method based on the site selection of public service facilities. Figure 2 , the method comprising:

[0103] Step S201: Divide the block into a number of sub-blocks according to the community block boundaries.

[0104] The community block boundary refers to the boundary of the community block on the map, and the community block includes a residential area, an office building, an apartment, a lodging area, etc. Optionally, the community block boundary is divided according to the community name.

[0105] Step S202: performing clustering operations on the sub-blocks according to the population distribution inside the sub-blocks to obtain temporary nodes.

[0106] Optionally, population distribution is used to indicate the spatial distribution of population.

[0107] Clustering operations include K-means clustering, density-based clustering, spatial autocorrelation analysis, etc.

[0108] In an optional example, the position of the target person in the sub-block is randomly selected, and the persons whose distance from the target person is less than the classification distance are classified into the same group of classification results; the target person is randomly selected from the remaining persons in the sub-block, and the operation of classifying the persons whose distance from the target person is less than the classification distance into the same group of classification results is repeated to obtain the population clustering result. The distribution of the population clustering result on the map is fitted to obtain a temporary node.

[0109] Step S203: predicting the estimated travel time from the temporary node to the public service facility based on the population attributes, public transportation facilities and road conditions corresponding to the temporary node.

[0110] Population attributes include at least one of population density, population size, age structure, travel mode, occupational distribution and household registration.

[0111] Optionally, the travel mode of personnel is predicted based on the population attributes and public transportation facilities corresponding to the temporary node. The estimated travel time from the temporary node to the public service facility is predicted based on the travel mode of personnel and road conditions.

[0112] Furthermore, the movement route from the temporary node to the public service facility is predicted based on the travel mode of the personnel and the geographical location of the temporary node. The estimated travel time is obtained based on the movement route and the travel mode of the personnel. For example, if the travel mode of the personnel is public transportation, the public transportation facility closest to the temporary node is determined based on the geographical location of the temporary node; the movement route is determined based on the geographical location of the aforementioned public transportation facility and the geographical location of the public service facility.

[0113] Furthermore, in the case where the mode of travel is self-driving, the movement route from the temporary node to the public service facility is predicted based on the mode of travel and road conditions. For example, several alternative movement routes from the temporary node to the public service facility are obtained; the travel time of the alternative movement video is predicted based on the road conditions; and the alternative movement route corresponding to the minimum travel time is taken as the movement route used in this step.

[0114] Step S204: performing clustering operations on temporary nodes according to the estimated travel time and the community area of ​​the temporary nodes to obtain nodes.

[0115] Exemplarily, temporary nodes are classified according to estimated travel times to obtain a first temporary node combination, so that the estimated travel times corresponding to the temporary nodes in the first temporary node combination are within the same time interval; the first temporary node combination is classified according to community areas to obtain a second temporary node combination, so that the distance between each temporary node in the second temporary node combination is less than a distance threshold; the temporary nodes in each second temporary node combination are merged to obtain the nodes required by this embodiment.

[0116] In summary, after using the community block boundary to divide the block into several sub-blocks, the population distribution is used to cluster the sub-blocks to obtain temporary nodes, and then the estimated travel time from the temporary nodes to the public service facilities is predicted according to the population attributes, public transportation facilities and road conditions corresponding to the temporary nodes, and clustering is performed again. This can effectively improve the accuracy of node division.

[0117] In the following embodiments, when there is population mobility, problems may arise when dividing temporary nodes, causing a large gap between the population attributes in the temporary nodes and the actual situation. Therefore, the present application embodiment discloses a node division method based on the site selection of public service facilities. Figure 3 , the method comprising:

[0118] Step S301: Count the total permanent population and total floating population within the sub-block.

[0119] The total permanent population refers to the total number of people whose actual location is consistent with their registered residence.

[0120] The total floating population refers to the total number of people whose actual location is inconsistent with their registered residence.

[0121] Optionally, the total permanent population and total floating population within the sub-block are obtained through the relevant demographic server.

[0122] Step S302: Classify the total floating population according to the total residence time of the total floating population within the preset time period to obtain the total permanent floating population and the total temporary floating population.

[0123] The preset duration is a preset constant, for example, 3 months, 6 months or 1 year.

[0124] For example, the floating population whose total residence time within the preset time is greater than the classification time threshold is confirmed as the total permanent floating population; the floating population whose total residence time within the preset time is less than the classification time threshold is confirmed as the total temporary floating population. For example, if the classification time threshold is 8 months, and the total residence time of person A reaches 10 months within 1 year, then person A is classified as the total permanent floating population. If the total residence time of person B reaches 6 months within 1 year, then person B is classified as the total temporary floating population.

[0125] Step S303: Perform clustering operations on the sub-blocks according to the total permanent population and the total permanent floating population to obtain permanent population clustering results.

[0126] The permanent population clustering result refers to the clustering area of ​​the total permanent population and the total permanent floating population in the sub-block. The permanent population clustering result includes at least two groups. Exemplarily, the permanent population clustering result is obtained by clustering the spatial distribution of the total permanent population and the total permanent floating population.

[0127] Optionally, based on the total permanent population and the total permanent floating population, clustering operations performed on the sub-blocks include K-means clustering, density-based clustering operations, spatial autocorrelation analysis, etc.

[0128] Step S304: performing clustering operations on the sub-blocks according to the total temporary floating population to obtain temporary population clustering results.

[0129] The temporary population clustering result refers to the clustering area of ​​the total temporary floating population in the sub-block. The temporary population clustering result includes at least two groups. Exemplarily, the temporary population clustering result is obtained by clustering the spatial distribution of the total temporary floating population.

[0130] Optionally, based on the total temporary floating population, clustering operations performed on the sub-blocks include K-means clustering, density-based clustering, spatial autocorrelation analysis, etc.

[0131] Step S305: Make a union of the permanent population clustering results and the temporary population clustering results to obtain a temporary node.

[0132] Exemplarily, the target permanent population clustering result in the permanent population clustering result and the target temporary population clustering result in the temporary population clustering result are taken; when there is an overlapping area between the target permanent population clustering result and the target temporary population clustering result, the area of ​​the overlapping area is calculated; if the ratio of the area of ​​the overlapping area to the area of ​​the target permanent population clustering result is greater than a first preset ratio, and the ratio of the area of ​​the overlapping area to the area of ​​the target temporary population clustering result is greater than a second preset ratio, then the target permanent population clustering result and the target temporary population clustering result need to be merged to obtain a temporary node. If the ratio of the area of ​​the overlapping area to the area of ​​the target permanent population clustering result is less than the first preset ratio, or the ratio of the area of ​​the overlapping area to the area of ​​the target temporary population clustering result is less than the second preset ratio, then the target permanent population clustering result and the target temporary population clustering result need to be kept separate, so that the target permanent population clustering result and the target temporary population clustering result form their own temporary nodes.

[0133] In summary, the floating population is divided into permanent floating population and temporary floating population according to the total length of residence of the population, and the clustering results of the permanent population are determined based on the total permanent population and the total permanent floating population, and the clustering results of the temporary population are determined based on the total temporary floating population. The temporary nodes are then obtained by the union of the clustering results of the permanent population and the clustering results of the temporary population. The division of temporary nodes is more accurate, which is conducive to obtaining reasonable sub-blocks, and is convenient for subsequent analysis of the coverage of public service facilities in different sub-blocks, so as to obtain reasonable target nodes.

[0134] In the following embodiments, temporary residents and permanent residents usually have a large gap in travel mode and public facility needs. If the two are not distinguished when calculating population attributes, the population attributes will not be able to well represent the population characteristics within the node, resulting in a large deviation in the final result. The embodiment of the present application discloses a node division method based on the site selection of public service facilities. Figure 4 , the method comprising:

[0135] Step S401: Obtain the total population, permanent population, permanent floating population and temporary floating population in the node.

[0136] Optionally, the total population, permanent population, permanent floating population and temporary floating population in the node are obtained through a related demographic server.

[0137] In some specific examples, temporary migrant population includes tourists, people on business trips, temporary factory workers, etc.

[0138] Step S402: Calculate a first weight based on the permanent population, the permanent floating population and the total population.

[0139] Exemplarily, the sum of the permanent population and the permanent floating population is calculated; then the ratio of the aforementioned sum to the total population is calculated to obtain the first weight.

[0140] Step S403: Calculate a second weight based on the temporary floating population and the total population.

[0141] Exemplarily, the ratio of the temporary floating population to the total population is calculated to obtain the second weight.

[0142] Step S404: Count the first population density, the first age structure, the first occupation distribution and the first travel mode of the permanent population and the permanent floating population in the area where the node is located.

[0143] For example, the first population density, the first age structure, the first occupational distribution and the first travel mode of personnel can be obtained by conducting a census of the permanent population and the permanent floating population in the area where the node is located, or by a sample survey.

[0144] Step S405: According to the first age structure, the first occupation distribution and the first travel mode of the personnel, the first population density is updated to obtain a first attribute value.

[0145] Exemplarily, according to the first age structure, a first proportion of the number of people of effective age to the total population is obtained. The product of the first population density and the first proportion is calculated, and the first population density is updated to obtain a first attribute value. The effective age is related to the type of public service facility. For example, when the public service facility is a youth activity center, the effective age is 1 to 24 years old.

[0146] Exemplarily, according to the first occupation distribution, the second proportion of the number of people in valid occupations to the total population is obtained. The product of the first population density and the second proportion is calculated, and the first population density is updated to obtain the first attribute value. Among them, the valid occupation is related to the type of public service facilities. For example, if the public service center is a special technical education school, the valid occupation is related to the subject taught in the special technical education school.

[0147] Exemplarily, based on the travel mode of the first person, the types of travel modes and the number of people corresponding to the types of travel modes are counted; the mapping values ​​corresponding to the types of travel modes are searched in a preset mapping table; the ratios of the numbers of people corresponding to different types of travel modes in the total population are calculated; the mapping values ​​are weighted according to the aforementioned ratios to obtain a third ratio; the product of the first population density and the third ratio is calculated, the first population density is updated, and the first attribute value is obtained.

[0148] Step S406: Count the second population density, the second age structure, the second occupation distribution and the second travel mode of the temporary floating population in the area where the node is located.

[0149] For example, the second population density, the second age structure, the second occupational distribution and the second travel mode of personnel may be obtained by conducting a census of the temporary floating population in the area where the node is located, or by a sample survey.

[0150] Step S407: Update the second population density according to the second age structure, the second occupation distribution and the second travel mode of the personnel to obtain a second attribute value.

[0151] Exemplarily, according to the second age structure, a fourth proportion of the number of people of effective age to the total population is obtained. The product of the second population density and the first proportion is calculated, and the first population density is updated to obtain a second attribute value. The effective age is related to the type of public service facilities.

[0152] Exemplarily, according to the second occupation distribution, the fifth proportion of the number of people with valid occupations in the total population is obtained. The product of the second population density and the fifth proportion is calculated, and the second population density is updated to obtain the second attribute value. Among them, the valid occupation is related to the type of public service facilities.

[0153] Exemplarily, based on the travel mode of the second person, the types of travel modes and the number of people corresponding to the types of travel modes are counted; the mapping values ​​corresponding to the types of travel modes are searched in a preset mapping table; the ratios of the numbers of people corresponding to different types of travel modes in the total population are calculated; the mapping values ​​are weighted according to the aforementioned ratios to obtain a sixth ratio; the product of the second population density and the sixth ratio is calculated, the second population density is updated, and the second attribute value is obtained.

[0154] Furthermore, since the needs of temporary floating population for public service facilities are different from those of permanent population, correction parameters are set according to the types of public service facilities, and the product of the correction parameters and the second attribute value is calculated to update the second attribute value so that the second attribute value is closer to the portrait of temporary floating population.

[0155] Step S408: With the first weight being the weight of the first attribute value and the second weight being the weight of the second attribute value, weighted calculation is performed on the first attribute value and the second attribute value to obtain a population attribute.

[0156] Exemplarily, if the first weight is α, the first attribute value is m, the second weight is β, and the second attribute value is n, then the population attribute is α*m+β*n.

[0157] Optionally, after obtaining the node, a population type mark is added to the node according to the ratio of the total temporary floating population in the node to the total population, and the population type marks include a mark for the dominance of permanent residents, a mark for the dominance of temporary residents, and a mark for mixed residents.

[0158] For example, when the ratio of the total temporary floating population to the total population in a node is greater than the first classification threshold, a temporary-dominated marker is added to the node; when the ratio of the total temporary floating population to the total population in a node is less than the first classification threshold and greater than the second classification threshold, a permanent-dominated marker is added to the node; when the ratio of the total temporary floating population to the total population in a node is less than the second classification threshold, a mixed-personnel marker is added to the node. Among them, the first classification threshold is greater than the second classification threshold, and the specific values ​​of the two can be adjusted according to actual conditions. Furthermore, a population type marker can be added as a population attribute.

[0159] In summary, when calculating population attributes, temporary floating population, permanent floating population and permanent population are calculated separately, so that the population attributes can better represent the attributes of the node, which is convenient for the subsequent analysis of the coverage of public service facilities in different sub-blocks, so as to obtain reasonable target nodes.

[0160] In the following embodiments, the proportion of temporary floating population will affect the local demand for public service facilities. Therefore, the present application embodiment discloses a method for calculating the travel time based on the site selection of public service facilities. Figure 5 , the method comprising:

[0161] Step S501: Count the total population and the number of temporary floating population in the node.

[0162] Optionally, the total population and the number of temporary floating population in the node are obtained through a related demographic server.

[0163] Step S502: When the number of temporary floating population accounts for a greater than a preset proportion of the total population, the public transportation travel time and self-driving travel time from the public service facility to the node are counted.

[0164] When the number of temporary floating population is greater than the preset proportion of the total population, local public service facilities will mainly serve the temporary floating population. Therefore, due to the characteristics of the temporary floating population, their travel is mainly by public transportation, supplemented by self-driving.

[0165] The preset ratio is a preset fixed value. The specific value of the preset ratio can be adjusted according to actual needs.

[0166] Exemplarily, if there are at least two public transportation lines from the public service facility to the node, the average number of passengers carried by the at least two public transportation lines in the same period is counted. The travel time of the at least two public transportation lines is counted. The average number of passengers carried by the at least two public transportation lines is normalized to obtain the weight values ​​corresponding to the at least two public transportation lines. The travel time of the at least two public transportation lines is weightedly calculated according to the aforementioned weight values ​​to obtain the public transportation travel time.

[0167] Exemplarily, if there are at least two self-driving routes from the public service facility to the node, the average traffic volume of the at least two self-driving routes in the same period is counted. The travel time of the at least two self-driving routes is counted. The average traffic volume corresponding to the at least two self-driving routes is normalized to obtain the weight values ​​corresponding to the at least two self-driving routes. The travel time of the at least two self-driving routes is weightedly calculated according to the aforementioned weight values ​​to obtain the self-driving travel time.

[0168] Step S503: performing weighted calculation on the public transportation travel time and the self-driving travel time according to a preset weight value to obtain a first actual travel time.

[0169] The preset weight value is a preset constant, and the specific value of the preset weight value can be adjusted according to actual needs. For example, the preset weight corresponding to the public transportation travel time is 70%, and the preset weight corresponding to the self-driving travel time is 30%.

[0170] In some other embodiments, the preset weight value is determined based on the number of people who own vehicles among the temporary floating population. For example, if the temporary floating population is 1,000 people, of which 200 own vehicles, the preset weight corresponding to the public transportation travel time is 80%, and the preset weight corresponding to the self-driving travel time is 20%.

[0171] Step S504: When the proportion of temporary floating population to the total population is less than a preset ratio, the travel modes of the total permanent population and the total permanent floating population in the node are counted.

[0172] The total permanent population includes the permanent population and the permanent floating population.

[0173] People’s travel modes include public transportation and self-driving.

[0174] Step S505: Calculate the travel time corresponding to the personnel's travel mode.

[0175] For the calculation method of the travel time corresponding to the travel mode of the personnel, please refer to step S502, which will not be repeated here.

[0176] Step S506: Perform weighted calculation on the travel time according to the proportion of the population of the travel mode corresponding to the travel time in the total permanent population to obtain a first actual travel time.

[0177] In another aspect of this embodiment, the second actual travel time can also be calculated and obtained by referring to the steps of this embodiment.

[0178] In summary, according to the proportion of temporary floating population in the total population, different methods are used to calculate the first actual travel time. The first actual travel time can better represent the population characteristics within the block, which is conducive to analyzing the coverage of public service facilities in different sub-blocks, so as to obtain reasonable target nodes.

[0179] In the following embodiments, due to the differences in public service facilities, different people in the node have different needs for public service facilities, so it is necessary to consider the number of people in the node who have a real need for public service facilities. Therefore, the embodiment of the present application discloses a method for calculating the bearing pressure based on the site selection of public service facilities. Figure 6 , the method comprising:

[0180] Step S601: Classify the total population according to the types of public service facilities to obtain the effective population.

[0181] For example, when the type of the public service facility is an educational facility, the effective population in the total population is determined according to the type of education provided by the educational facility. For example, when the public service facility is a primary school, the population aged 6 to 13 is counted as the effective population.

[0182] For example, when the type of public service facility is an entertainment facility, the effective population in the total population is determined according to the type of people served by the entertainment facility. For example, when the public service facility is an elderly activity center, the number of people over 60 years old is counted as the effective population.

[0183] Exemplarily, when the type of public service facility is a sanitary facility, the total population number is taken as the effective population number.

[0184] Step S602: normalize the first actual travel time to obtain a weight value of the load-bearing pressure.

[0185] Exemplarily, the first actual travel time is mapped to a range of [0, 1] through linear transformation to obtain a load-bearing pressure weight value.

[0186] Step S603: Perform weighted calculation on the effective population according to the bearing pressure weight value to obtain a bearing pressure vector.

[0187] Calculate the product of the effective population and the bearing pressure weight corresponding to the effective population; calculate the sum of the aforementioned products to obtain the bearing pressure of a single public service facility; fill the bearing pressure of each public service facility into the vector to obtain the bearing pressure vector.

[0188] In summary, the total population is classified according to the type of public service facilities to obtain the effective population. The effective population can better represent the bearing pressure vector. The coverage of public service facilities to different sub-blocks is analyzed to obtain reasonable target nodes.

[0189] In the following embodiments, when calculating the effective population, since the needs of temporary floating population are different from those of permanent population, the two need to be discussed separately. The present application embodiment discloses a method for calculating the effective population based on the site selection of public service facilities. Figure 7 , the method comprising:

[0190] Step S701: Count the permanent population, permanent floating population and temporary floating population in the node.

[0191] Optionally, the permanent population, permanent floating population and temporary floating population in the node are obtained through a related demographic server.

[0192] Step S702: Classify the permanent population and the permanent floating population according to the type of public service facilities to obtain a first effective population size.

[0193] The method of classifying the permanent population and the permanent floating population according to the type of public service facilities can be referred to Figure 6 Step S601 of the illustrated embodiment.

[0194] Step S703: Classify the temporary floating population according to the types of public service facilities to obtain the number of effective temporary residents.

[0195] The method of classifying temporary floating population according to the type of public service facilities can be referred to Figure 6 Step S601 of the illustrated embodiment.

[0196] Step S704: When public service facilities are the target type, a conversion ratio is generated according to the proportion of temporary floating population to the total population.

[0197] The target type is a preset public service facility type. For example, the target types of public service facilities include youth activity centers, elderly activity centers, community service centers, public nursing homes, etc. The target type refers to the type of public service facility whose utilization rate of temporary floating population is less than the utilization threshold. Further, the conversion ratio is updated according to the utilization rate of the target type of public service facilities by temporary floating population. For example, the product of the conversion ratio and the utilization rate is calculated to update the conversion ratio.

[0198] Exemplarily, the ratio of the temporary floating population to the total population is calculated to obtain the conversion ratio.

[0199] Step S705: Obtain the second effective population according to the product of the conversion ratio and the effective temporary population.

[0200] The second effective population is obtained by multiplying the conversion ratio by the effective temporary population.

[0201] Step S706: Obtain the effective population according to the sum of the first effective population and the second effective population.

[0202] The effective population in the block can be obtained by adding the first effective population and the second effective population.

[0203] In summary, the effective temporary population is converted according to the proportion of temporary floating population in the total population to obtain a more reasonable effective population. Therefore, the effective population can better represent the population characteristics within the block, which is conducive to obtaining a reasonable target node.

[0204] Based on the same inventive concept, the embodiment of the present application provides a public service facility site selection system, including:

[0205] The acquisition module 801 is used to obtain the community block boundary, block, population attributes, population distribution, total permanent population and total floating population;

[0206] Memory 802, used to store a program of any of the above public service facility site selection methods;

[0207] Processor 803, the program in the memory can be loaded and executed by the processor to implement any of the above-mentioned public service facility site selection methods.

[0208] In summary, the blocks are divided according to the community block boundaries to obtain several nodes, and the first actual travel time and the second time travel time are calculated. The traffic accessibility matrix is ​​generated by the first actual travel time and the second time travel time, and the node attributes are weighted in combination with the first actual travel time to obtain the bearing pressure vector of the public service facility. The coverage matrix is ​​obtained through the traffic accessibility matrix and the bearing pressure vector. The coverage matrix is ​​used to determine which sub-blocks need to build new public service facilities. The division of blocks is carried out according to the community block boundaries, and the division of blocks is more accurate, which is conducive to obtaining more accurate block information and helping to accurately select nodes where new public service facilities need to be built.

[0209] Moreover, the coverage matrix is ​​obtained by integrating the traffic accessibility matrix and the carrying pressure vector, so that the coverage matrix can better reflect the relationship between nodes and public service facilities, which helps to select more accurate target nodes for the construction of public service facilities.

[0210] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0211] An embodiment of the present application provides a computer-readable storage medium storing a computer program that can be loaded by a processor and execute a method for selecting a site for a public service facility.

[0212] Computer storage media include, for example, various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0213] Based on the same inventive concept, an embodiment of the present application provides an intelligent terminal, including a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and execute a method for selecting a site for a public service facility.

[0214] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0215] The above are all preferred embodiments of the present application, and are not intended to limit the protection scope of the present application. Any feature disclosed in this specification (including the abstract and drawings), unless otherwise stated, can be replaced by other equivalent or alternative features with similar purposes. That is, unless otherwise stated, each feature is only an example of a series of equivalent or similar features.

Claims

1. A method for selecting a site for a public service facility, characterized in that: The method comprises: Divide the block into a plurality of nodes according to the community block boundary; wherein the step of dividing the block into a plurality of nodes according to the community block boundary includes: dividing the block into a plurality of sub-blocks according to the community block boundary; performing clustering operations on the sub-blocks according to the population distribution inside the sub-blocks to obtain temporary nodes; predicting the estimated travel time from the temporary node to the public service facility according to the population attributes, public transportation facilities and road conditions corresponding to the temporary node; performing clustering operations on the temporary node according to the estimated travel time and the community area of ​​the temporary node to obtain the node; The step of performing clustering operations on the sub-blocks according to the population distribution inside the sub-blocks to obtain temporary nodes includes: counting the total permanent population and the total floating population inside the sub-blocks; classifying the total floating population according to the total residence time of the total floating population within a preset time to obtain the total permanent floating population and the total temporary floating population; performing clustering operations on the sub-blocks according to the total permanent population and the total permanent floating population to obtain the permanent population clustering results; performing clustering operations on the sub-blocks according to the total temporary floating population to obtain the temporary population clustering results; and obtaining the temporary node by taking the union of the permanent population clustering results and the temporary population clustering results; According to the population attributes of the node, setting the node attributes of the node, the node attributes including the population size and the travel mode of the people in the node; Calculate the first actual travel time from the public service facility to the node, and the second actual travel time from the node to the public service facility; wherein, the step of calculating the first actual travel time from the public service facility to the node includes: counting the total population and the number of temporary floating population in the node; when the number of temporary floating population accounts for more than a preset proportion of the total population, counting the public transportation travel time and the self-driving travel time from the public service facility to the node; performing weighted calculation on the public transportation travel time and the self-driving travel time according to a preset weight value to obtain the first actual travel time; when the number of temporary floating population accounts for less than the preset proportion of the total population, counting the travel modes of the total permanent population and the total permanent floating population in the node; calculating the travel time corresponding to the travel mode of the personnel; performing weighted calculation on the travel time according to the proportion of the population of the travel mode of the personnel corresponding to the travel time in the total permanent population, to obtain the first actual travel time; constructing an adjacency matrix according to the first actual travel time and the second actual travel time to obtain a traffic accessibility matrix; In combination with the first actual travel time, a weighted operation is performed on the node attributes to obtain the bearing pressure vector of the public service facility; wherein the step of performing a weighted operation on the node attributes in combination with the first actual travel time to obtain the bearing pressure vector of the public service facility includes: classifying the population according to the type of the public service facility to obtain the effective population; normalizing the first actual travel time to obtain a bearing pressure weight value; performing a weighted operation on the effective population according to the bearing pressure weight value to obtain the bearing pressure vector; Calculate the product of the traffic accessibility matrix and the diagonal matrix of the bearing pressure vector to obtain the coverage matrix of the public server facility, where the coverage matrix is ​​used to record the distribution of the coverage corresponding to the node; According to the coverage matrix, a target node is searched among the nodes, and the community block corresponding to the target node is used to establish a new public service facility.

2. The method for selecting a site for a public service facility according to claim 1, characterized in that: The method further comprises: Obtain the total population, permanent population, permanent floating population and temporary floating population within the node; Calculate a first weight based on the permanent population, the permanent floating population and the total population; Calculating a second weight according to the temporary floating population and the total population; Counting the first population density, the first age structure, the first occupation distribution and the first travel mode of the permanent population and the permanent floating population in the area where the node is located; According to the first age structure, the first occupation distribution and the first travel mode of the first personnel, the first population density is updated to obtain a first attribute value; Counting the second population density, the second age structure, the second occupation distribution and the second travel mode of the temporary floating population in the area where the node is located; updating the second population density according to the second age structure, the second occupation distribution and the second personnel travel mode to obtain a second attribute value; The first weight is used as the weight of the first attribute value, and the second weight is used as the weight of the second attribute value. The first attribute value and the second attribute value are weighted to obtain the population attribute.

3. The method for selecting a site for a public service facility according to claim 1, characterized in that: The step of classifying the population according to the type of the public service facilities to obtain the effective population includes: Count the permanent population, permanent floating population and temporary floating population within the node; Classifying the permanent population and the permanent floating population according to the types of the public service facilities to obtain a first effective population number; Classifying the temporary floating population according to the types of the public service facilities to obtain the number of effective temporary residents; When the public service facilities are the target type, a conversion ratio is generated according to the ratio of the temporary floating population to the total population; Obtaining a second effective population according to the product of the conversion ratio and the effective temporary population; The effective population is obtained according to the sum of the first effective population and the second effective population.

4. A public service facility site selection system, characterized in that: The system comprises: The acquisition module is used to obtain the community block boundaries, blocks, population attributes, population distribution, total permanent population and total floating population; A memory for storing a program of the method for selecting a site for a public service facility according to any one of claims 1 to 3; The program in the memory can be loaded and executed by the processor to implement the public service facility site selection method as described in any one of claims 1 to 3.

5. An intelligent terminal, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and execute the method according to any one of claims 1 to 3.

6. A computer-readable storage medium, characterized in that: A computer program is stored which can be loaded by a processor and execute the method according to any one of claims 1 to 3.

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