Automatic teller machine site selection method, device, computer equipment and storage medium

Abstract

The present application relates to an ATM site selection method, device, computer equipment, storage medium and computer program product. The method can be used in the field of big data technology, including: obtaining a set of logistics points in the same area, the logistics point set includes multiple logistics points, and each logistics point includes logistics location information and logistics cargo volume; based on the logistics location information of each logistics point, clustering and merging the logistics points at least once to obtain multiple scattered points; obtaining the scattered location information and scattered cargo volume corresponding to each scattered point; determining the target location information of the ATM according to the scattered location information and scattered cargo volume corresponding to each of the multiple scattered points. The use of this method can more reasonably deploy ATMs and improve the accuracy of ATM site selection.

Description

Technical Field

[0001] The present application relates to the field of big data technology, and in particular to an ATM site selection method, apparatus, computer equipment, storage medium and computer program product. Background Art

[0002] With the development of urbanization, the site selection technology of ATMs has become more comprehensive, scientific and mature. In the process of ATM site selection, four aspects are specifically considered, namely: population factors, geographical transportation, property factors and competitive environment. Among them, population factors are an important factor affecting the site selection of ATMs. Population factors mainly include total population, population composition, population density, education level, flow of people, etc. Without considering other factors, it is obvious that the savings stock status and utilization rate of ATMs in places with high population density should be prioritized over places with low population density.

[0003] Traditional ATM site selection generally uses population density-related algorithms to calculate the population density of the area and select the ATM site based on the population density.

[0004] However, the traditional ATM site selection method needs to be calculated based on the flow of people. If the obtained flow of people data is not accurate enough, the obtained population density data is also not accurate enough, which leads to unreasonable layout of the ATM location. Summary of the invention

[0005] Based on this, it is necessary to provide an ATM site selection method, device, computer equipment, computer-readable storage medium and computer program product that can more reasonably deploy ATMs in response to the above technical problems.

[0006] In a first aspect, the present application provides a method for selecting an ATM site. The method comprises:

[0007] Obtain a set of logistics points in the same area, wherein the set of logistics points includes multiple logistics points, and each logistics point includes logistics location information and logistics cargo volume;

[0008] Based on the logistics location information of each logistics point, clustering and merging the logistics points at least once to obtain multiple scattered points;

[0009] Obtain the dispersed location information and dispersed cargo quantity corresponding to each dispersed point;

[0010] The target location information of the automatic teller machine is determined according to the dispersed location information and the dispersed cargo quantity corresponding to each dispersed point in the plurality of dispersed points.

[0011] In one of the embodiments, the logistics points are clustered and merged at least once based on the logistics location information of each logistics point to obtain multiple scattered points, including: calculating the distance between any two logistics points in the logistics point set, merging the two logistics points corresponding to the minimum distance and the minimum distance being less than a distance threshold to obtain a new logistics point; updating the logistics point set according to the new logistics point, and returning to the step of calculating the distance between any two logistics points in the logistics point set to continue executing until the clustering stop condition is reached; taking each logistics point in the latest logistics point set obtained by the final clustering as a scattered point to obtain multiple scattered points.

[0012] In one of the embodiments, two logistics points having a minimum distance and corresponding to a minimum distance less than a distance threshold are merged to obtain a new logistics point, including: determining new logistics location information based on logistics location information of the two logistics points having a minimum distance and corresponding to the minimum distance less than the distance threshold; determining new logistics cargo quantity based on logistics cargo quantity of the two logistics points having a minimum distance and corresponding to the minimum distance less than the distance threshold; and determining a new logistics point based on the new logistics location information and the new logistics cargo quantity.

[0013] In one of the embodiments, updating the logistics point set according to the new logistics point includes: adding the new logistics point to the logistics point set, and removing the two logistics points to be merged from the logistics point set, so as to achieve the update of the logistics point set.

[0014] In one of the embodiments, determining the target location information of the automatic teller machine based on the dispersed location information and the dispersed cargo quantity corresponding to each of the multiple dispersed points includes: multiplying the dispersed location information of each dispersed point with the corresponding dispersed cargo quantity to obtain a product result; comparing a first sum of the multiplication results corresponding to all the dispersed points with a second sum of the dispersed cargo quantities corresponding to all the dispersed points to obtain a comparison value; and determining the target location information of the automatic teller machine based on the comparison value.

[0015] In one of the embodiments, each logistics point also includes a cargo type, and the method further includes: determining the age distribution of the population in a region based on the cargo type; and adjusting the target location information of the ATM based on the age distribution of the population in the region.

[0016] In a second aspect, the present application also provides an ATM site selection device. The device comprises:

[0017] An acquisition module is used to acquire a set of logistics points in the same area, wherein the set of logistics points includes multiple logistics points, and each logistics point includes logistics location information and logistics cargo volume;

[0018] A clustering module is used to perform at least one clustering and merging process on the logistics points based on the logistics location information of each logistics point to obtain multiple scattered points; and obtain the scattered location information and the scattered cargo quantity corresponding to each scattered point;

[0019] The determination module is used to determine the target location information of the automatic teller machine according to the dispersed location information and the dispersed cargo quantity corresponding to each dispersed point in the plurality of dispersed points.

[0020] In a third aspect, the present application further provides a computer device. The computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the following steps when executing the computer program:

[0021] Obtain a set of logistics points in the same area, wherein the set of logistics points includes multiple logistics points, and each logistics point includes logistics location information and logistics cargo volume;

[0022] Based on the logistics location information of each logistics point, clustering and merging the logistics points at least once to obtain multiple scattered points;

[0023] Obtain the dispersed location information and dispersed cargo quantity corresponding to each dispersed point;

[0024] The target location information of the automatic teller machine is determined according to the dispersed location information and the dispersed cargo quantity corresponding to each dispersed point in the plurality of dispersed points.

[0025] In a fourth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0026] Obtain a set of logistics points in the same area, wherein the set of logistics points includes multiple logistics points, and each logistics point includes logistics location information and logistics cargo volume;

[0027] Based on the logistics location information of each logistics point, clustering and merging the logistics points at least once to obtain multiple scattered points;

[0028] Obtain the dispersed location information and dispersed cargo quantity corresponding to each dispersed point;

[0029] The target location information of the automatic teller machine is determined according to the dispersed location information and the dispersed cargo quantity corresponding to each dispersed point in the plurality of dispersed points.

[0030] In a fifth aspect, the present application further provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0031] Obtain a set of logistics points in the same area, wherein the set of logistics points includes multiple logistics points, and each logistics point includes logistics location information and logistics cargo volume;

[0032] Based on the logistics location information of each logistics point, clustering and merging the logistics points at least once to obtain multiple scattered points;

[0033] Obtain the dispersed location information and dispersed cargo quantity corresponding to each dispersed point;

[0034] The target location information of the automatic teller machine is determined according to the dispersed location information and the dispersed cargo quantity corresponding to each dispersed point in the plurality of dispersed points.

[0035] The above-mentioned ATM site selection method, device, computer equipment, storage medium and computer program product, combined with the current development status of my country's express logistics industry, maps the distribution of logistics points in a certain area to the population density distribution of the area, and performs clustering and merging processing on the logistics points in the area based on the logistics location information of the logistics points. The location information and cargo volume of the logistics points after clustering and merging are used to calculate the center of gravity method, and the location of the ATM is determined according to the distribution of population density in the area in combination with the center of gravity method of the logistics system. Compared with the traditional algorithm that considers population density when selecting the site for ATMs, and relying on the traditional population flow estimation method, the use of this application can more reasonably deploy ATMs and improve the accuracy of ATM site selection. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 An application environment diagram of an ATM site selection method in one embodiment;

[0037] Figure 2 A schematic diagram of a flow chart of an ATM site selection method in one embodiment;

[0038] Figure 3 is a schematic diagram of a process of a clustering step in an embodiment;

[0039] Figure 4 A schematic diagram of a logistics point set in one embodiment;

[0040] Figure 5 A schematic diagram of a corresponding table of a logistics point set in one embodiment;

[0041] Figure 6 A schematic diagram of the distance between any two logistics points in a logistics point set in one embodiment;

[0042] Figure 7 It is a structural block diagram of an automatic teller machine site selection device in one embodiment;

[0043] Figure 8 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. 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.

[0045] The automatic teller machine site selection method provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other network servers. The terminal 102 can independently execute the automatic teller machine site selection method provided in the embodiment of the present application, and the terminal 102 and the server 104 can also collaboratively execute the automatic teller machine site selection method provided in the embodiment of the present application.

[0046] When terminal 102 executes the ATM site selection method alone, terminal 102 obtains a set of logistics points in the same area, which includes multiple logistics points, and each logistics point includes logistics location information and logistics cargo volume; based on the logistics location information of each logistics point, the logistics points are clustered and merged at least once to obtain multiple scattered points; the scattered location information and scattered cargo volume corresponding to each scattered point are obtained; and the target location information of the ATM is determined according to the scattered location information and scattered cargo volume corresponding to each of the multiple scattered points.

[0047] When the terminal 102 and the server 104 cooperate to execute the ATM site selection method, the terminal 102 obtains a set of logistics points in the same area, which includes multiple logistics points, and each logistics point includes logistics location information and logistics cargo volume, and sends the logistics point set to the server 104. The server 104 performs at least one clustering and merging process on the logistics points based on the logistics location information of each logistics point to obtain multiple scattered points; obtains the scattered location information and scattered cargo volume corresponding to each scattered point; and determines the target location information of the ATM according to the scattered location information and scattered cargo volume corresponding to each of the multiple scattered points.

[0048] The terminal 102 may be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, IoT devices, and portable wearable devices. The IoT devices may be smart speakers, smart TVs, smart air conditioners, smart car-mounted devices, etc. The portable wearable devices may be smart watches, smart bracelets, head-mounted devices, etc. The server 104 may be implemented as an independent server or a server cluster consisting of multiple servers.

[0049] It should be noted that the embodiments of the present application belong to the field of big data technology, and specifically involve the center of gravity method technology. The center of gravity method is a simulation method that regards the demand points and resource points in the logistics system as a logistics system distributed within a certain plane, and the demand and resource quantities of each point are respectively regarded as the weight of the object. The center of gravity of the object system is used as the optimal setting point of the logistics network point, and the location of the logistics network point is determined by using the method of finding the center of gravity of the object system.

[0050] Population density is an important factor affecting the site selection of ATMs. In addition to relying on population surveys in the area, the logistics volume of the site selection area can better reflect the population density and population structure of the area to a certain extent. Relying on the huge driving force of e-commerce, my country's express delivery industry has developed rapidly and has now become the country with the largest parcel handling volume in the world. The logistics points established by express delivery companies can well reflect the population density and population distribution of a specific area.

[0051] The embodiment of the present application takes the logistics points in a specific area as resource points in the logistics system, the locations of ATMs as demand points in the logistics system, and the quantity of goods at the logistics points as the resource quantity of the resource points. The center of gravity simulation method in the logistics system is used to overlap the coordinates according to the geographical location of each logistics point in the map, establish a linear function of distance and quantity of goods, and use the method of finding the center of gravity of the object system to determine the location of the ATM.

[0052] It should be understood that the words "first", "second", "third", "fourth" and similar words used in the embodiments of the present application do not indicate any order, quantity or importance, but are only used to distinguish different components. Unless the context clearly indicates otherwise, the singular form of "a", "an" or "the" and similar words do not indicate a quantity limitation, but indicate the presence of at least one.

[0053] In one embodiment, Figure 2 As shown, a method for selecting an ATM site is provided, and the method is applied to Figure 1 Taking the terminal in as an example, the method includes the following steps:

[0054] Step 202, obtaining a set of logistics points in the same area, wherein the set of logistics points includes multiple logistics points, and each logistics point includes logistics location information and logistics cargo quantity.

[0055] Among them, the logistics point set is a set of multiple logistics points. Logistics points, also known as logistics outlets or express outlets, are nodes of the logistics network, mainly referring to storage and transportation warehouses, circulation warehouses, transit warehouses, etc., which are places for the storage and transportation and distribution of large quantities of materials. Once the warehouse is established, it will carry out storage and transportation business for enterprises and individuals in the entire region, and many enterprises and individuals will store and transport their materials here: transported here from all over the country, or transported out from here.

[0056] The logistics point is established by the logistics company. Each logistics point includes the name of the logistics point, logistics location information and logistics cargo volume. The name of the logistics point refers to the logistics company to which the logistics point belongs and the specific address of the logistics point, such as the first express company (A Road Store) and the second express company (B Road Business Hall). The logistics location information refers to the position of the logistics point in the two-dimensional plane map, that is, the appropriate coordinate system is established based on the two-dimensional plane map, and the horizontal and vertical coordinates of the logistics point in the two-dimensional plane map determined by the coordinate system. The logistics cargo volume refers to the number of materials transported to or from the logistics point, in pieces.

[0057] Specifically, the terminal obtains a set of logistics points in the same area, and counts the logistics point name, logistics location information and logistics cargo volume of each logistics point in the logistics point set.

[0058] Step 204: Based on the logistics location information of each logistics point, the logistics points are clustered and merged at least once to obtain multiple scattered points.

[0059] Among them, cluster merging refers to merging two or more logistics points with similar characteristics into a new type, that is, a new logistics point. Dispersed points refer to logistics points in the logistics point set after cluster merging.

[0060] Specifically, according to actual needs, based on the logistics location information of each logistics point, the terminal can perform at least one clustering and merging process on the logistics points in the logistics point set to obtain multiple scattered points. When the terminal performs one clustering and merging process on the logistics points in the logistics point set, a new logistics point is obtained. At this time, the scattered point is composed of a new logistics point and the logistics points that have not been clustered and merged; when the terminal performs two or more clustering and merging processes on the logistics points in the logistics point set, two or more new logistics points are obtained. At this time, the scattered point can be composed of two or more new logistics points and the logistics points that have not been clustered and merged, or all of them can be composed of multiple new logistics points.

[0061] Step 206, obtaining the dispersed location information and dispersed cargo quantity corresponding to each dispersed point.

[0062] The dispersed location information refers to the location of the dispersed point in the two-dimensional plane map, including the horizontal coordinate (x coordinate) and the vertical coordinate (y coordinate) of the dispersed point. The dispersed cargo volume refers to the quantity of materials transported to or from the dispersed point, in pieces.

[0063] Specifically, after obtaining multiple scattered points, the terminal obtains the scattered location information and the scattered cargo quantity corresponding to each scattered point.

[0064] Step 208: determining the target location information of the ATM according to the dispersed location information and the dispersed cargo quantity corresponding to each dispersed point in the plurality of dispersed points.

[0065] The target location information refers to the location of the ATM in the two-dimensional plane map, including the horizontal coordinate and the vertical coordinate of the ATM.

[0066] Specifically, the terminal determines the target location information of the ATM based on the centroid method of the logistics system and according to the dispersed location information and dispersed cargo quantities corresponding to each of the multiple dispersed points.

[0067] The above-mentioned ATM site selection method, combined with the current development status of my country's express logistics industry, maps the distribution of logistics points in a certain area to the population density distribution in the area, and combines the center of gravity method of the logistics system to determine the location of the ATM according to the distribution of population density in the area. And in order to better achieve the purpose of calculating the location of the ATM according to the population density distribution, the embodiment of the present application performs clustering and merging processing on the logistics points in the area under certain conditions based on the logistics location information of the logistics points, and uses the location information and cargo volume of the logistics points after clustering and merging to perform center of gravity calculation to determine the target location information of the ATM. Compared with the traditional algorithm that considers population density when selecting the site for the ATM, and relying on the traditional population flow estimation method, the ATM site selection method of this method can arrange the ATMs more scientifically, reasonably, and evenly, and improve the accuracy of the site selection of the ATMs.

[0068] In one embodiment, Figure 3 As shown, based on the logistics location information of each logistics point, the logistics point is clustered and merged at least once to obtain multiple scattered points, including:

[0069] Step 302, calculate the distance between any two logistics points in the logistics point set, merge the two logistics points with the minimum distance and the minimum distance less than the distance threshold, and obtain a new logistics point.

[0070] Among them, the distance between two logistics points is calculated using the Euclidean distance calculation formula. Euclidean distance, also known as Euclidean metric, is a commonly used distance definition, which refers to the real distance between two points in m-dimensional space, or the natural length of a vector (that is, the distance from the point to the origin). The Euclidean distance in two-dimensional and three-dimensional space is the actual distance between two points. The calculation formula of Euclidean distance is:

[0071]

[0072] Where ρ is the distance between two logistics points, a i is the x-coordinate of the ith logistics point, b i is the y coordinate of the i-th logistics point, and p is a positive integer greater than 1. When p is 2, ρ represents the distance between two logistics points in two-dimensional space; when p is 3, ρ represents the distance between two logistics points in three-dimensional space.

[0073] The distance threshold refers to the upper limit of the distance between two logistics points. When the distance between two logistics points in the logistics point set is less than the distance threshold, it means that the two logistics points may be of the same type and can be merged to obtain a new logistics point, thereby replacing the two logistics points. The size of the distance threshold can be set according to actual needs. The larger the setting, the more times the terminal needs to perform clustering and merging processing on multiple logistics points in the logistics point set.

[0074] Specifically, the terminal calculates the distance between any two logistics points in the logistics point set, obtains the minimum distance, and determines whether the minimum distance is less than the distance threshold. If so, the two logistics points corresponding to the minimum distance are merged to obtain a new logistics point.

[0075] Step 304, update the logistics point set according to the new logistics point, and return to the step of calculating the distance between any two logistics points in the logistics point set to continue executing until the clustering stop condition is reached.

[0076] The clustering stop condition refers to the distance between any two logistics points in the updated logistics point set being no less than the distance threshold.

[0077] Specifically, the terminal updates the logistics point set according to the new logistics point; for the updated logistics point set, the terminal returns to the above step 302 to calculate the distance between any two logistics points in the logistics point set, and continues to execute step 302 until the minimum distance between two logistics points in the logistics point set calculated according to step 302 is not less than the distance threshold, then stops merging the two logistics points to obtain the latest logistics point set.

[0078] Step 306, each logistics point in the latest logistics point set finally obtained by clustering is regarded as a scattered point, so as to obtain a plurality of scattered points.

[0079] Among them, the scattered points refer to the logistics points in the logistics point set after clustering and merging.

[0080] Specifically, the terminal uses each logistics point in the latest logistics point set obtained by the final clustering as a scattered point according to the latest logistics point set obtained by the final clustering, thereby obtaining multiple scattered points.

[0081] In this embodiment, by merging logistics points whose distances are less than a distance threshold into a new logistics point and clustering logistics points of similar types in the same area, the purpose of better estimating the placement location of the ATM according to the population density distribution can be achieved.

[0082] In one embodiment, two logistics points with a minimum distance and a minimum distance less than a distance threshold are merged to obtain a new logistics point, including: determining new logistics location information based on the logistics location information of the two logistics points with a minimum distance and a minimum distance less than the distance threshold; determining new logistics cargo quantity based on the logistics cargo quantity of the two logistics points with a minimum distance and a minimum distance less than the distance threshold; determining a new logistics point based on the new logistics location information and the new logistics cargo quantity.

[0083] The logistics location information of the logistics point includes the horizontal coordinate and the vertical coordinate of the logistics point, and the new logistics location information includes the horizontal coordinate and the vertical coordinate of the new logistics point. The new logistics cargo volume refers to the logistics cargo volume of the new logistics point.

[0084] Specifically, the terminal respectively calculates the average values ​​of the horizontal and vertical coordinates of the two logistics points corresponding to the minimum distance and the minimum distance being less than the distance threshold; the average value of the horizontal coordinates of the two logistics points is used as the horizontal coordinate of the new logistics point, and the average value of the vertical coordinates of the two logistics points is used as the vertical coordinate of the new logistics point.

[0085] The terminal calculates the average value of the logistics cargo volume of the two logistics points with the minimum distance and the minimum distance is less than the distance threshold, and takes the average value of the logistics cargo volume of the two logistics points as the logistics cargo volume of the new logistics point. For each new logistics point, the terminal determines a new logistics point based on the abscissa of the new logistics point, the ordinate of the new logistics point and the logistics cargo volume of the new logistics point.

[0086] In this embodiment, the purpose of merging two logistics points into a new logistics point can be achieved by taking the average of the horizontal coordinates, vertical coordinates and logistics cargo quantities of the two logistics points to be merged as the logistics location information and logistics cargo quantity of the new logistics point.

[0087] In one embodiment, updating the logistics point set according to the new logistics point includes: adding the new logistics point to the logistics point set, and removing the two logistics points to be merged from the logistics point set, so as to update the logistics point set.

[0088] In this embodiment, a new logistics point is used to replace the two logistics points to be merged to achieve the update of the logistics point set, and then the location of the ATM is calculated using the location information and cargo quantity of each logistics point in the latest logistics point set obtained by the final clustering, which can achieve the purpose of better estimating the placement location of the ATM based on the population density distribution.

[0089] In one embodiment, the target location information of the ATM is determined based on the dispersed location information and the dispersed cargo quantity corresponding to each of the multiple dispersed points, including: multiplying the dispersed location information of each dispersed point with the corresponding dispersed cargo quantity to obtain a product result; comparing a first sum of the product results corresponding to all the dispersed points with a second sum of the dispersed cargo quantities corresponding to all the dispersed points to obtain a comparison value; and determining the target location information of the ATM based on the comparison value.

[0090] The scattered position information includes the horizontal coordinates and vertical coordinates of the scattered points. Accordingly, the first sum includes the sum of the product results of the horizontal coordinates of all scattered points and the corresponding scattered cargo quantities, and the sum of the product results of the vertical coordinates of all scattered points and the corresponding scattered cargo quantities. The second sum refers to the sum of the scattered cargo quantities of all scattered points. The comparison value includes the first comparison value and the second comparison value, and the target position information of the ATM includes the target horizontal coordinate and the target vertical coordinate of the ATM, the first comparison value corresponds to the target horizontal coordinate of the ATM, and the second comparison value corresponds to the target vertical coordinate of the ATM.

[0091] Specifically, the terminal multiplies the horizontal coordinate of each scattered point by the scattered cargo quantity of the scattered point to obtain a product result; compares the sum of the product results corresponding to all scattered points with the second sum of the scattered cargo quantities corresponding to all scattered points to obtain a first comparison value; and determines the target horizontal coordinate of the ATM according to the first comparison value.

[0092] The terminal multiplies the ordinate of each scattered point by the scattered cargo quantity of the scattered point to obtain a product result; compares the sum of the product results corresponding to all the scattered points with the second sum of the scattered cargo quantities corresponding to all the scattered points to obtain a second comparison value; and determines the target ordinate of the ATM according to the second comparison value.

[0093] In one embodiment, the terminal calculates multiple scattered points according to the centroid method, and determines the target horizontal coordinate and target vertical coordinate of the ATM according to the horizontal coordinate, vertical coordinate and the scattered cargo quantity corresponding to each of the multiple scattered points.

[0094] The calculation formula of the center of gravity method is:

[0095]

[0096]

[0097] In the formula, C x is the target horizontal coordinate of the ATM, C y is the target ordinate of the ATM, D ix is the horizontal coordinate of the ith scattered point, D iy is the ordinate of the ith scattered point, V i is the amount of dispersed cargo transported to or from the i-th dispersed point.

[0098] In this embodiment, by mapping the distribution of logistics points in the same area to the population density distribution in the area, combined with the center of gravity method of the logistics system, the distribution of population density in the area is calculated. This is not dependent on traditional population flow estimation methods, and can achieve a more reasonable layout of ATMs and improve the accuracy of ATM site selection.

[0099] In one embodiment, each logistics point also includes a cargo type, and the ATM site selection method further includes: determining the age distribution of the population in the area based on the cargo type; and adjusting the target location information of the ATM based on the age distribution of the population in the area.

[0100] Among them, the type of goods refers to the type of goods, including daily necessities, clothing, fresh food, electronic products, pet food, letters, etc. The source of the goods type information can be obtained from the express company. The population age distribution includes under 18 years old, 18-30 years old, 31-40 years old, 41-50 years old, and over 50 years old. The population age distribution can also be other classification standards, which are not limited in this embodiment.

[0101] Specifically, for each logistics point, the terminal counts the logistics cargo volume according to the cargo type, and obtains the statistical results of the cargo type, which include the top three commodities in terms of logistics cargo volume and the proportion of the logistics cargo volume of each commodity in the total logistics cargo volume. Based on the statistical results of the cargo type, the age distribution of the population in the region is determined. Furthermore, based on the age distribution of the population in the region, the terminal adjusts the target location information of the ATM so that the target location of the ATM is more in line with the usage preferences of the target population in the region.

[0102] For example, the statistical result of the type of goods is that the top three commodities in terms of logistics cargo volume are clothing, electronic products, and pet food, and the logistics cargo volume of these three commodities accounts for 30%, 35%, and 10% of the total logistics cargo volume, respectively. Then, it can be preliminarily determined that the population age distribution in the area is mainly under 18 years old, 18-30 years old, and 31-40 years old. Furthermore, according to the fact that the population in the area is mainly under 18 years old, 18-30 years old, and 31-40 years old, the target location information of the ATM is adjusted so that the target location of the ATM is more in line with the usage preferences of the target population aged 18-40 in the area. For example, since the target population aged 18-40 is mainly college students, office workers, and housewives, the target location of the ATM is set in a central area close to schools, shopping malls, parks, etc., which is more in line with the consumption habits of the target population, so that they can deposit and withdraw money through the ATM at any time.

[0103] In this embodiment, by obtaining the cargo type of each logistics point, the population age distribution of the area is determined based on the cargo type; based on the population age distribution of the area, the target location information of the ATM is adjusted, so that the site selection point of the ATM in the area can be better estimated.

[0104] In another embodiment, Figure 4-6 As shown, a method for selecting a site for an automatic teller machine is provided, comprising:

[0105] 1. The terminal selects a certain area and obtains all logistics points in the area, such as Figure 4 As shown, there are 10 logistics points, which are represented by labels P1, P2, ..., P10 respectively. The figure shows the position distribution relationship of all logistics points in the two-dimensional coordinate system, and also shows the logistics cargo volume of each logistics point.

[0106] The terminal then organizes all logistics points according to the number, logistics point name, logistics location information and logistics cargo volume into the following Figure 5 Table shown. Reference Figure 5 ,Take logistics point P1 as an example, the logistics point name of logistics point P1 is the First Express Company (A Road Store), the logistics location information, that is, the horizontal and vertical coordinates are: 121.606177 and 31.265774 respectively, and the logistics cargo volume is 500 pieces.

[0107] 2. According to the center of gravity method, use formulas (1) and (2) to calculate:

[0108]

[0109]

[0110] In the formula, C x is the x-coordinate of the center of gravity of the logistics, C y is the y coordinate of the center of gravity of the logistics, D ix is the x-coordinate of the ith logistics point, D iy is the y coordinate of the i-th logistics point, V i is the amount of goods transported to or from the i-th logistics point.

[0111] The terminal calculates the logistics center of gravity of the above 10 logistics points according to formulas (1) and (2), and obtains the x-coordinate and y-coordinate of the logistics center of gravity as 121.6006706 and 31.26282513 respectively, that is, the position of the logistics center of gravity in the two-dimensional plane map is close to the logistics point P2; and determines the logistics center of gravity as the site selection point of the ATM.

[0112] In this area, the ATM is set up near the logistics point P2, which is in line with the population density distribution in the area. Compared with the traditional algorithm that considers population density when selecting the site for ATMs, this method combines the current development status of my country's express logistics industry, maps the distribution of express logistics points to the population density distribution of the distribution area, and calculates the distribution of population density in the area by combining the center of gravity method of the logistics system, which does not rely on the traditional population flow estimation method.

[0113] 3. When there are many logistics points in a certain area, cluster analysis method can be used to merge logistics points of similar types into one category.

[0114] For example, for logistics points P1 and P2, according to the calculation formula of Euclidean distance:

[0115]

[0116] Calculate the distance between logistics points P1 and P2, where ρ is the distance between the two logistics points, a i is the x-coordinate of the ith logistics point, b i is the y coordinate of the i-th logistics point, and p is a positive integer greater than 1.

[0117] Taking p as 2, the distance ρ(P1, P2) between logistics points P1 and P2 is 0.005254314.

[0118] Using the same method, the distance between any two logistics points among all 10 logistics points is calculated in sequence, and the following is obtained: Figure 6As shown in the table. It can be seen from the table that the distance between logistics points P10 and P7 is the smallest, and logistics points P10 and P7 are merged into a new logistics point, recorded as CL11. The abscissa and ordinate of the new logistics point CL11 are the average of the abscissa and ordinate of logistics points P10 and P7, respectively, and its cargo volume is the average of the cargo volume of logistics points P10 and P7.

[0119] According to the above method, the distances between the new logistics point and other logistics points are calculated in turn, and the two logistics points with the smallest distance are merged into a new logistics point until the minimum distance is less than the distance threshold, that is, a satisfactory clustering result is obtained, and clustering is stopped. The clustering result is multiple scattered points representing the population distribution in the current area.

[0120] 4. Take the multiple scattered points as dependent variables, and use formulas (1) and (2) to calculate according to the centroid method, and finally calculate the location of the ATM.

[0121] This method clusters the logistics points in a certain area under certain conditions, and uses the centroid method to calculate the logistics points obtained by clustering, which can better estimate the placement of ATMs based on population density distribution.

[0122] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0123] Based on the same inventive concept, the embodiment of the present application also provides an ATM site selection device for implementing the ATM site selection method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations of one or more ATM site selection device embodiments provided below can refer to the limitations of the ATM site selection method above, and will not be repeated here.

[0124] In one embodiment, Figure 7 As shown, an ATM site selection device 700 is provided, comprising: an acquisition module 702, a clustering module 704 and a determination module 706, wherein:

[0125] The acquisition module 702 is used to acquire a set of logistics points in the same area. The logistics point set includes multiple logistics points, and each logistics point includes logistics location information and logistics cargo quantity.

[0126] The clustering module 704 is used to perform at least one clustering and merging process on the logistics points based on the logistics location information of each logistics point to obtain multiple scattered points; and obtain the scattered location information and scattered cargo quantity corresponding to each scattered point.

[0127] The determination module 706 is used to determine the target location information of the automatic teller machine according to the dispersed location information and the dispersed cargo quantity corresponding to each dispersed point in the plurality of dispersed points.

[0128] In one embodiment, the clustering module 704 is also used to calculate the distance between any two logistics points in the logistics point set, merge the two logistics points with the minimum distance and the minimum distance less than the distance threshold to obtain a new logistics point; update the logistics point set according to the new logistics point, and return to the step of calculating the distance between any two logistics points in the logistics point set to continue executing until the clustering stop condition is reached; each logistics point in the latest logistics point set obtained by the final clustering is regarded as a scattered point to obtain multiple scattered points.

[0129] In one embodiment, the clustering module 704 is also used to determine new logistics location information based on the logistics location information of two logistics points corresponding to the minimum distance and the minimum distance being less than the distance threshold; determine new logistics cargo quantity based on the logistics cargo quantity of two logistics points corresponding to the minimum distance and the minimum distance being less than the distance threshold; determine a new logistics point based on the new logistics location information and the new logistics cargo quantity.

[0130] In one embodiment, the clustering module 704 is further used to add a new logistics point into the logistics point set, and remove two logistics points to be merged from the logistics point set, so as to update the logistics point set.

[0131] In one embodiment, the determination module 706 is also used to perform a product operation on the scattered position information of each scattered point and the corresponding scattered cargo quantity to obtain a product result; compare the first sum of the product results corresponding to all the scattered points with the second sum of the scattered cargo quantities corresponding to all the scattered points to obtain a comparison value; and determine the target position information of the ATM according to the comparison value.

[0132] In one embodiment, each logistics point also includes a cargo type, and the ATM site selection device 700 also includes an adjustment module, which is used to determine the population age distribution of the area based on the cargo type; and adjust the target location information of the ATM based on the population age distribution of the area.

[0133] Each module in the above-mentioned ATM site selection device can be implemented in whole or in part by software, hardware or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each module.

[0134] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 8 As shown. The computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, an automatic teller machine site selection method is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a key, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0135] Those skilled in the art will understand that Figure 8 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0136] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the following steps when executing the computer program: obtaining a set of logistics points in the same area, wherein the set of logistics points includes multiple logistics points, and each logistics point includes logistics location information and logistics cargo quantity; performing clustering and merging processing on the logistics points at least once based on the logistics location information of each logistics point to obtain multiple scattered points; obtaining the scattered location information and the scattered cargo quantity corresponding to each scattered point; and determining the target location information of the automatic teller machine according to the scattered location information and the scattered cargo quantity corresponding to each of the multiple scattered points.

[0137] In one embodiment, the processor also implements the following steps when executing the computer program: calculating the distance between any two logistics points in the logistics point set, merging the two logistics points corresponding to the minimum distance and the minimum distance being less than the distance threshold to obtain a new logistics point; updating the logistics point set according to the new logistics point, and returning to the step of calculating the distance between any two logistics points in the logistics point set to continue executing until the clustering stop condition is reached; treating each logistics point in the latest logistics point set obtained by the final clustering as a scattered point to obtain multiple scattered points.

[0138] In one embodiment, when the processor executes the computer program, it also implements the following steps: determine new logistics location information based on the logistics location information of two logistics points corresponding to the minimum distance and the minimum distance being less than a distance threshold; determine new logistics cargo quantity based on the logistics cargo quantity of two logistics points corresponding to the minimum distance and the minimum distance being less than a distance threshold; determine a new logistics point based on the new logistics location information and the new logistics cargo quantity.

[0139] In one embodiment, when the processor executes the computer program, the following steps are also implemented: adding a new logistics point to the logistics point set, and removing the two logistics points to be merged from the logistics point set, so as to update the logistics point set.

[0140] In one embodiment, when the processor executes the computer program, the following steps are also implemented: multiplying the scattered position information of each scattered point with the corresponding scattered cargo quantity to obtain a product result; comparing a first sum of the product results corresponding to all the scattered points with a second sum of the scattered cargo quantities corresponding to all the scattered points to obtain a comparison value; and determining the target position information of the ATM according to the comparison value.

[0141] In one embodiment, each logistics point also includes a cargo type, and the processor also implements the following steps when executing the computer program: based on the cargo type, determining the age distribution of the population in the area; based on the age distribution of the population in the area, adjusting the target location information of the ATM.

[0142] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented: obtaining a set of logistics points in the same area, the logistics point set includes multiple logistics points, and each logistics point includes logistics location information and logistics cargo quantity; clustering and merging the logistics points at least once based on the logistics location information of each logistics point to obtain multiple scattered points; obtaining the scattered location information and scattered cargo quantity corresponding to each scattered point; determining the target location information of the automatic teller machine according to the scattered location information and scattered cargo quantity corresponding to each of the multiple scattered points.

[0143] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: calculating the distance between any two logistics points in the logistics point set, merging the two logistics points corresponding to the minimum distance and the minimum distance being less than the distance threshold to obtain a new logistics point; updating the logistics point set according to the new logistics point, and returning to the step of calculating the distance between any two logistics points in the logistics point set to continue executing until the clustering stop condition is reached; treating each logistics point in the latest logistics point set obtained by the final clustering as a scattered point to obtain multiple scattered points.

[0144] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: determining new logistics location information based on the logistics location information of two logistics points corresponding to the minimum distance and the minimum distance being less than a distance threshold; determining new logistics cargo quantity based on the logistics cargo quantity of two logistics points corresponding to the minimum distance and the minimum distance being less than a distance threshold; determining a new logistics point based on the new logistics location information and the new logistics cargo quantity.

[0145] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: adding a new logistics point to the logistics point set, and removing the two logistics points to be merged from the logistics point set, so as to update the logistics point set.

[0146] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: multiplying the scattered position information of each scattered point with the corresponding scattered cargo quantity to obtain a product result; comparing the first sum of the product results corresponding to all the scattered points with the second sum of the scattered cargo quantities corresponding to all the scattered points to obtain a comparison value; and determining the target position information of the ATM according to the comparison value.

[0147] In one embodiment, each logistics point also includes a cargo type, and the computer program, when executed by a processor, also implements the following steps: determining the age distribution of the population in the area based on the cargo type; and adjusting the target location information of the ATM based on the age distribution of the population in the area.

[0148] In one embodiment, a computer program product is provided, including a computer program, which implements the following steps when executed by a processor: obtaining a set of logistics points in the same area, the logistics point set including multiple logistics points, and each logistics point including logistics location information and logistics cargo quantity; performing at least one clustering and merging process on the logistics points based on the logistics location information of each logistics point to obtain multiple scattered points; obtaining the scattered location information and the scattered cargo quantity corresponding to each scattered point; and determining the target location information of the automatic teller machine according to the scattered location information and the scattered cargo quantity corresponding to each of the multiple scattered points.

[0149] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: calculating the distance between any two logistics points in the logistics point set, merging the two logistics points corresponding to the minimum distance and the minimum distance being less than the distance threshold to obtain a new logistics point; updating the logistics point set according to the new logistics point, and returning to the step of calculating the distance between any two logistics points in the logistics point set to continue executing until the clustering stop condition is reached; treating each logistics point in the latest logistics point set obtained by the final clustering as a scattered point to obtain multiple scattered points.

[0150] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: determining new logistics location information based on the logistics location information of two logistics points corresponding to the minimum distance and the minimum distance being less than a distance threshold; determining new logistics cargo quantity based on the logistics cargo quantity of two logistics points corresponding to the minimum distance and the minimum distance being less than a distance threshold; determining a new logistics point based on the new logistics location information and the new logistics cargo quantity.

[0151] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: adding a new logistics point to the logistics point set, and removing the two logistics points to be merged from the logistics point set, so as to update the logistics point set.

[0152] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: multiplying the scattered position information of each scattered point with the corresponding scattered cargo quantity to obtain a product result; comparing the first sum of the product results corresponding to all the scattered points with the second sum of the scattered cargo quantities corresponding to all the scattered points to obtain a comparison value; and determining the target position information of the ATM according to the comparison value.

[0153] In one embodiment, each logistics point also includes a cargo type, and the computer program, when executed by a processor, also implements the following steps: determining the age distribution of the population in the area based on the cargo type; and adjusting the target location information of the ATM based on the age distribution of the population in the area.

[0154] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0155] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0156] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0157] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for selecting a site for an automated teller machine, characterized in that: The method comprises: Obtain a set of logistics points in the same area, wherein the set of logistics points includes multiple logistics points, and each logistics point includes logistics location information, logistics cargo volume, and cargo type; Calculate the distance between any two logistics points in the logistics point set, merge the two logistics points with the minimum distance and the minimum distance less than the distance threshold, and obtain a new logistics point; The logistics point set is updated according to the new logistics point, and the step of calculating the distance between any two logistics points in the logistics point set is returned to continue execution until the clustering stop condition is reached; Each logistics point in the latest logistics point set finally obtained by clustering is regarded as a scattered point, thereby obtaining multiple scattered points; Obtaining the dispersed position information and dispersed cargo quantity corresponding to each dispersed point; the dispersed point position information includes the horizontal coordinate and the vertical coordinate of the dispersed point; The product of the horizontal coordinate of each scattered point and the corresponding scattered cargo quantity is added to obtain a first sum; the product of the vertical coordinate of each scattered point and the corresponding scattered cargo quantity is added to obtain a third sum; Compare the first sum with the second sum of the dispersed cargo quantities corresponding to all dispersed points to obtain a first comparison value; compare the third sum with the second sum to obtain a second comparison value; determining target location information of the automatic teller machine according to the first comparison value and the second comparison value; Based on the cargo type, the age distribution of the population in the area is determined; based on the age distribution of the population in the area, the target location information of the ATM is adjusted.

2. The method according to claim 1, characterized in that The two logistics points corresponding to the minimum distance and the minimum distance being less than the distance threshold are merged to obtain a new logistics point, including: Determine new logistics location information according to the logistics location information of two logistics points corresponding to the minimum distance and the minimum distance being less than the distance threshold; Determine a new logistics cargo volume according to the logistics cargo volumes of two logistics points corresponding to the minimum distance and the minimum distance being less than the distance threshold; Based on the new logistics location information and the new logistics cargo quantity, a new logistics point is determined.

3. The method according to claim 1, characterized in that The updating of the logistics point set according to the new logistics point includes: The new logistics point is added to the logistics point set, and the two logistics points to be merged are removed from the logistics point set to update the logistics point set.

4. An automatic teller machine site selection device, characterized in that: The device comprises: An acquisition module is used to acquire a set of logistics points in the same area, wherein the set of logistics points includes multiple logistics points, and each logistics point includes logistics location information, logistics cargo quantity and cargo type; A clustering module is used to calculate the distance between any two logistics points in the logistics point set, merge the two logistics points with the minimum distance and the minimum distance less than the distance threshold to obtain a new logistics point; update the logistics point set according to the new logistics point, and return to the step of calculating the distance between any two logistics points in the logistics point set to continue executing until the clustering stop condition is reached; take each logistics point in the latest logistics point set obtained by the final clustering as a scattered point to obtain multiple scattered points; obtain the scattered position information and the scattered cargo volume corresponding to each scattered point; the scattered point position information includes the horizontal coordinate and the vertical coordinate of the scattered point; A determination module, configured to add the product of the abscissa of each scattered point and the corresponding scattered cargo quantity to obtain a first sum; and to add the product of the ordinate of each scattered point and the corresponding scattered cargo quantity to obtain a third sum; Compare the first sum with the second sum of the dispersed cargo quantities corresponding to all dispersed points to obtain a first comparison value; compare the third sum with the second sum to obtain a second comparison value; determining target location information of the automatic teller machine according to the first comparison value and the second comparison value; The adjustment module determines the age distribution of the population in the area based on the type of goods; and adjusts the target location information of the ATM based on the age distribution of the population in the area.

5. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 3 are implemented.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 3 are implemented.

7. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 3 are implemented.

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