Method, system and equipment for identifying boundary of digital living circle in central urban area and medium

Abstract

The invention discloses a central urban area digital life circle boundary identification method, system and device and a medium, and the method comprises the steps: obtaining the distribution data of various digital facilities in a research area, calculating the coverage rate of various digital facilities, and taking the coverage rate as a life service digital level evaluation index; obtaining population culture degree data and mobile phone signal base station distribution data in the research area, and calculating a life service digital potential index in the research area; determining the head word of each index, matching a plurality of related words for each head word through corpus retrieval, and counting the word frequency of each related word in the official file; according to the word frequency of each related word in the official file, determining the weight sorting of each index through a high-dimensional sorting weight method; and obtaining a digital life circle boundary identification result through dual linear programming calculation according to each index and the weight sequence of each index. According to the invention, the pertinence and rationality of urban digital construction planning decision making can be improved.

Description

Technical Field

[0001] The present invention relates to a method, system, computer equipment and storage medium for identifying the boundary of a central urban digital living circle, and belongs to the cross-field of urban planning and urban geography. Background Art

[0002] The life circle is "a basic unit that meets the various needs of urban and rural residents throughout their life cycle, including work and life, and is also a way of leading a future-oriented, composite, shared, healthy and low-carbon lifestyle". In recent years, the Internet, big data, artificial intelligence, blockchain and other technologies have developed rapidly, and digital technologies have been increasingly widely used in the practice of urban development and social governance. While guiding the orderly construction of community life circles, urban planning should also take into account the impact and changes brought about by digital technology, pay attention to the needs of urban construction from the perspective of digital life, use multi-source data to identify the boundaries of the digital life circle in the central urban area, and provide reference for the planning layout and decision-making of the digital life circle.

[0003] The existing methods for dividing living circles mainly include three categories: (1) GPS positioning method, (2) Alpha-shape method, and (3) grid network method. These three methods are mostly based on GPS trajectory data of residents' activities and corresponding activity log data. Nowadays, the online service industry based on digital virtual platforms is becoming increasingly developed, and the dependence of residents' daily behavior activities on fixed places and offline facilities has decreased, and the life behaviors generated by relying on online platforms have increased significantly. The composition of residents' living circles is changing, and the boundaries of traditional living circles are being blurred and expanded by digital services. However, in the current research on living circle boundary identification methods, digital facilities and digital life services are less considered. Summary of the invention

[0004] In view of this, the present invention provides a method, system, computer equipment and storage medium for identifying the boundaries of a digital living circle in a central urban area. An index system is constructed based on the coverage rate of digital facilities to evaluate the digitalization level of life services, which is used as a basis for delineating the core circle of the digital living circle. An index is constructed based on the cultural level of the population and the coverage rate of mobile phone signal base stations to evaluate the digitalization potential of life services, which is used as a basis for delineating the extended circle of the digital living circle. Official documents related to the construction of the digital living circle are collected for text mining, and a high-dimensional sorting weight method is used to weight each indicator to avoid the subjectivity of the evaluation and improve the scientificity. At the same time, the comprehensive evaluation is closely linked to the urban development policy, thereby enhancing the reference value of the evaluation results.

[0005] The first object of the present invention is to provide a method for identifying the boundary of a central urban digital living circle.

[0006] The second object of the present invention is to provide a system for identifying the boundaries of a central urban digital living circle.

[0007] A third object of the present invention is to provide a computer device.

[0008] A fourth object of the present invention is to provide a storage medium.

[0009] The first object of the present invention can be achieved by adopting the following technical solutions:

[0010] A method for identifying the boundary of a central urban digital living circle, the method comprising:

[0011] Obtain the distribution data of various digital facilities in the study area and calculate the coverage rate of various digital facilities as an evaluation indicator of the digital level of life services;

[0012] Obtain data on the educational level of the population and the distribution of mobile phone signal base stations in the study area, and calculate the potential indicators for digitalization of life services in the study area;

[0013] Determine the core word of each indicator, match a number of related words to each core word through corpus search, and count the frequency of each related word in official documents;

[0014] According to the frequency of each relevant word in the official documents, the weight ranking of each indicator is determined through the high-dimensional ranking weight method;

[0015] According to various indicators and their weight ranking, the digital life circle boundary identification results are obtained through dual linear programming calculation.

[0016] Furthermore, the weight ranking of each indicator is determined by a high-dimensional ranking weight method according to the word frequency of each relevant word in the official document, specifically including:

[0017] Calculate the total frequency of related words corresponding to each indicator core word, divide it by the number of related words to eliminate the influence of the number of related words, and get the average frequency of the indicator related words;

[0018] Sort the average values ​​of word frequency in reverse order from high to low to obtain the weight ranking of each indicator.

[0019] Furthermore, the digital life circle boundary recognition result is obtained by dual linear programming calculation according to various indicators and their weight ranking, which specifically includes:

[0020] According to the evaluation indicators of the digital level of life services and the weight ranking, the dual linear programming formula is substituted to calculate the digital level of life services and identify the core circle of the digital life circle;

[0021] According to the digital potential indicators of life services and the weight ranking, substitute them into the dual linear programming formula to calculate the digital potential of life services and identify the expansion circle of the digital life circle.

[0022] Furthermore, the dual linear programming formula is as follows:

[0023]

[0024]

[0025] in, represents the life service digitalization level index or life service digitalization potential index of object i determined by k indicators, represents the optimal value of the weighted score of each dimension, Indicates the worst value of the weighted scores of each dimension, n p Indicates indicator data with weight ranking p.

[0026] Furthermore, the calculation of the coverage of various digital facilities specifically includes:

[0027] Divide the vector map plane of the study area into grids to form a number of grids of equal size with serial numbers;

[0028] The distribution data of various digital facilities are screened and further processed. In each grid, the coverage rate of various digital facilities is calculated respectively, so that the facility distribution data can form the digital level index of life services, as shown in the following formula:

[0029]

[0030] Among them, Fac i,a represents the coverage rate of facility i on a grid a, N a represents the number of facilities on grid a, N i represents the total number of facility i in the study area.

[0031] Furthermore, the calculation of the potential indicators of digitalization of life services in the research area specifically includes:

[0032] Starting from the boundary of the research area, a certain radius is extended outward, and the buffer distance is consistent with the maximum service radius of digital facilities in the indicator system, which serves as the extended research area for defining the extended circle of the digital life circle;

[0033] Divide the newly added buffer area in the expanded study area into multiple grids and number them;

[0034] The data on population education level and mobile phone base station distribution are screened and further processed to calculate the potential indicators for digitalization of life services in each grid.

[0035] Furthermore, the indicators of the potential for digitalization of life services include the coverage rate of the population with a secondary school education or above and the coverage rate of mobile phone signal base stations;

[0036] The data on population education level and mobile phone signal base station distribution are screened and further processed to calculate the potential indicators of digitalization of life services in each grid, including:

[0037] According to the population education level SDK data, the distribution location and total number of people with a high school education or above in the expanded study area are obtained, and connected to each grid to obtain the number of people with a high school education or above in each grid;

[0038] Divide the number of people with a secondary school education or above in a single grid by the total number of people with a secondary school education or above to calculate the coverage rate of the population with a secondary school education or above in each grid, as follows:

[0039]

[0040] Among them, Edu a represents the population coverage rate of middle school education or above in a certain grid a, M a M represents the number of people with a secondary school education or above on grid a. i It represents the total number of people with a secondary school education or above in the extended study area;

[0041] According to the base station distribution location information in the mobile phone signal base station data, the distribution location and total number of mobile phone signal base stations in the expanded study area are obtained, and connected to each grid to obtain the number of mobile phone signal base stations distributed in each grid;

[0042] Calculate the mobile phone signal base station coverage index on each grid as follows:

[0043]

[0044] Among them, CT a Indicates the coverage rate of mobile phone signal base stations on a certain grid a, m a Indicates the number of mobile phone signal base stations on grid a, m i Represents the total number of mobile phone signal base stations in the extended study area.

[0045] The second object of the present invention can be achieved by adopting the following technical solutions:

[0046] A central urban digital life circle boundary recognition system, the system comprising:

[0047] The first calculation module is used to obtain the distribution data of various digital facilities in the study area and calculate the coverage rate of various digital facilities as an evaluation index of the digital level of life services;

[0048] The second calculation module is used to obtain the data on the educational level of the population and the distribution data of mobile phone signal base stations in the study area, and calculate the potential indicators of digitalization of life services in the study area;

[0049] The statistical module is used to determine the core word of each indicator, match a number of related words to each core word through corpus search, and count the frequency of each related word in official documents;

[0050] A determination module is used to determine the weight ranking of each indicator based on the frequency of each related word in the official document through a high-dimensional ranking weight method;

[0051] The identification module is used to obtain the digital life circle boundary identification result through dual linear programming calculation according to various indicators and their weight sorting.

[0052] The third object of the present invention can be achieved by adopting the following technical solutions:

[0053] A computer device comprises a processor and a memory for storing a program executable by the processor. When the processor executes the program stored in the memory, the method for identifying the boundary of a central urban digital living circle is implemented.

[0054] The fourth object of the present invention can be achieved by adopting the following technical solutions:

[0055] A storage medium stores a program, and when the program is executed by a processor, the method for identifying the boundary of a central urban digital living circle is implemented.

[0056] The present invention has the following beneficial effects compared with the prior art:

[0057] The present invention utilizes multi-source data to construct a comprehensive evaluation index of the digitalization level and digitalization potential of life services, realizes the boundary identification of the digital life circle of the central urban area, and helps to improve the pertinence and rationality of urban digital construction planning decisions; compared with the existing technology, the present invention has a more objective vision and stronger operability, and also provides a new idea for the definition of the digital life circle. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying creative work.

[0059] Figure 1 This is a simplified flow chart of the method for identifying the boundary of the central urban digital living circle according to Embodiment 1 of the present invention.

[0060] Figure 2 This is a detailed flow chart of the method for identifying the boundary of the central urban digital living circle according to Embodiment 1 of the present invention.

[0061] Figure 3a to Figure 3d This is a schematic diagram of the coverage of four types of digital facilities in Example 1 of the present invention.

[0062] Figure 4 This is a schematic diagram of the expanded study area of ​​Example 1 of the present invention.

[0063] Figure 5 This is a schematic diagram of the coverage rate of the population with a secondary school education or above according to Example 1 of the present invention.

[0064] Figure 6 This is a schematic diagram of the coverage rate of mobile phone signal base stations in Example 1 of the present invention.

[0065] Figure 7 This is a schematic diagram of the life service digitalization level index according to Example 1 of the present invention.

[0066] Figure 8 This is a schematic diagram of the life service digitalization potential index according to Example 1 of the present invention.

[0067] Fig. 9 This is a schematic diagram of the result of delineating a digital life circle according to Embodiment 1 of the present invention.

[0068] Fig.10 This is a structural block diagram of a central urban digital living circle boundary identification system according to Embodiment 2 of the present invention.

[0069] Fig.11 This is a structural block diagram of a computer device according to Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0070] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0071] Embodiment 1:

[0072] This embodiment takes Yuexiu District of Guangzhou as an example, provides a method for identifying the boundaries of a digital life circle in a central urban area based on multi-source data, constructs an evaluation index system for the digital level and digital potential of life services, extracts the core words of the indicators based on official documents on the construction of digital life circles, and counts the word frequencies. A high-dimensional sorting weight method is used to obtain weights, and a comprehensive evaluation is performed on the digital level and digital potential of life services in the study area to achieve boundary identification of the digital life circle. Figure 1 and Figure 2 As shown, the method comprises the following steps:

[0073] S201. Obtain the distribution data of various digital facilities in the study area and calculate the coverage rate of various digital facilities as an evaluation indicator of the digital level of life services.

[0074] Furthermore, step S201 specifically includes:

[0075] S2011. Obtain the distribution data of various digital facilities in the study area.

[0076] In this embodiment, the types of digital facilities in Yuexiu District are counted, and based on the digitization status of the facilities, four types of digital facilities are selected: shared wifi, shared bicycles, online group purchase pick-up points, and smart health service stations; the distribution data of digital facilities in Yuexiu District is collected, including the POI data of shared wifi, shared bicycles, online group purchase pick-up points, and smart health service stations, and the obtained POI data is imported into the ArcGIS platform to define a unified geographic coordinate system GCS_WGS_1984.

[0077] S2012. Calculate the coverage of four types of digital facilities.

[0078] The study area is divided into several grids of equal size, and the collected sample data are screened and further processed to calculate the digital facility coverage index within each grid, so that the facility distribution data can form an indicator of the digital level of life services.

[0079] Furthermore, step S2012 specifically includes:

[0080] S20121. Divide the vector map plane of the study area into grids to form a number of grids of equal size with serial numbers.

[0081] In this embodiment, the fishing net tool of ArcGIS is used to divide Yuexiu District into 200m×200m grids, and each grid is labeled with a serial number so that each grid is a calculation unit.

[0082] S20122. Screen and further process the distribution data of various digital facilities. Calculate the coverage rate of various digital facilities in each grid, so that the facility distribution data can form indicators of the digital level of life services.

[0083] In this embodiment, the facility distribution data includes POI data of shared wifi, shared bicycles, online group purchase pick-up points, and smart health service stations. The resulting indicators of the digital level of life services are the shared wifi coverage index, the shared bicycle coverage index, the online group purchase pick-up point coverage index, and the smart health service station coverage index.

[0084] Furthermore, step S20122 specifically includes:

[0085] S201221. Based on the distribution locations of various types of facilities in Guangzhou in the facility distribution data, the facility distribution locations and the total number of various types of facilities in the study area were obtained. The spatial connection tool of ArcGIS was used to connect them to each grid to obtain the geographical location and quantity of various types of facilities distributed in each grid.

[0086] S201222. In each grid, calculate the coverage rate of these four types of digital facilities respectively, so that the facility distribution data can form the digital level index of life services, as shown in the following formula:

[0087]

[0088] Among them, Fac i,a represents the coverage rate of facility i on a grid a, N a represents the number of facilities on grid a, N i represents the total number of facilities i in the study area; according to this formula, grid analysis is performed with the help of ArcGIS platform to obtain the coverage of four types of digital facilities, such as Figure 3a to Figure 3d shown.

[0089] S202. Obtain data on the educational level of the population and the distribution of mobile phone signal base stations in the study area, and calculate the potential indicators for digitalization of life services in the study area.

[0090] This embodiment starts from the boundary of Yuexiu District and expands a certain radius outward. The buffer distance is consistent with the maximum service radius of digital facilities in the indicator system as the extended research area for defining the extended circle of the digital life circle. Figure 4 As shown in the figure, the newly added buffer area in the expanded study area is also divided into 200m×200m grids and assigned serial numbers. The collected data on population education level and mobile phone signal base station distribution data are screened and further processed to calculate the digitalization potential indicators of life services in each grid.

[0091] Furthermore, the digitalization potential indicators of life services in the study area are calculated, including:

[0092] S2021. Starting from the boundary of the research area, expand outward by a certain radius. The buffer distance should be consistent with the maximum service radius of digital facilities within the indicator system, which serves as the extended research area for defining the extended circle of the digital living circle.

[0093] In this embodiment, the buffer tool of ArcGIS is used, with the vector boundary of Yuexiu District as the starting boundary and a buffer of 2000m outward, and the resulting buffer is used as the extended research area for defining the extended circle of the digital living circle.

[0094] S2022. Divide the newly added buffer area in the expanded study area into multiple grids and number them.

[0095] In this embodiment, the fishing net tool of ArcGIS is used to divide the buffer area newly added to the extended study area on the basis of Yuexiu District into 200m×200m grids, and each grid is labeled with a serial number so that each grid is a calculation unit.

[0096] S2023. Screen and further process the data on population literacy and mobile phone base station distribution to calculate the potential indicators for digitalization of life services in each grid.

[0097] In this embodiment, the population education level data is the population education level SDK data (including the number of permanent residents in several statistical units and their education level information), the mobile phone signal base station distribution data is the mobile phone signal base station POI data, and the life service digitalization potential indicators include the population coverage rate of high school education and above and the mobile phone signal base station coverage rate.

[0098] Furthermore, step S2023 specifically includes:

[0099] S20231. Based on the population education level SDK data, obtain the distribution location and total number of people with a secondary school education or above in the expanded study area, connect to each grid, and obtain the number of people with a secondary school education or above in each grid.

[0100] S20232. Divide the number of people with a secondary school education or above in a single grid by the total number of people with a secondary school education or above to calculate the coverage rate of the population with a secondary school education or above in each grid, such as Figure 5 As shown in the following formula:

[0101]

[0102] Among them, Edu a represents the population coverage rate of middle school education or above in a certain grid a, M aM represents the number of people with a secondary school education or above on grid a. i It represents the total number of people with a secondary school education or above in the extended study area;

[0103] S20233. According to the base station distribution location information in the mobile phone signal base station data, the distribution location and total number information of the mobile phone signal base stations in the expanded study area are obtained, and connected to each grid to obtain the number of mobile phone signal base stations distributed in each grid.

[0104] S20234. Calculate the coverage rate of mobile phone signal base stations on each grid, such as Figure 6 As shown in the following formula:

[0105]

[0106] Among them, CT a Indicates the coverage rate of mobile phone signal base stations on a certain grid a, m a Indicates the number of mobile phone signal base stations on grid a, m i Represents the total number of mobile phone signal base stations in the extended study area.

[0107] S203, determining the central word of each indicator, matching a number of related words for each central word through corpus search, and counting the frequency of each related word in official documents.

[0108] In this embodiment, the core word of each indicator is determined, and an online analysis tool for related words is used to mine high-frequency related words of the core word of each indicator. After further screening the mining results, several related words are sorted out for each indicator, and official documents related to the digital life circle are collected, and the word frequency of each related word in the official documents is counted.

[0109] Furthermore, step S203 specifically includes:

[0110] S2031. Determine the core words of each indicator.

[0111] In this embodiment, the indicator core word is determined. According to the linguistic definition, the core word is "a word that carries the main meaning in a sentence or phrase", which can be a noun, a verb or an adjective. Specifically, the core word of the indicator "shared wifi coverage rate" is "shared wifi", and the core word of the indicator "population coverage rate of secondary school education and above" is "education level".

[0112] S2032. Use the online analysis tool for related words to mine high-frequency related words of the central words of each indicator.

[0113] In this embodiment, by means of the online word mining website - 5118 platform, the high-frequency related words of the central words of each index are mined. Enter the central words of each index in the "Keyword Comprehensive Query" section on the home page, click the query button, and after jumping to the comprehensive result interface, change the "Keyword Comprehensive Query" setting to "Mine Related Words", so as to screen out the related words corresponding to the index.

[0114] S2033. Further screen the mining results, and sort out several related words for each index.

[0115] In this embodiment, first, screen out the related words that directly contain the central word, such as "city shared bicycles", to avoid duplication; then, considering the writing characteristics of the official texts to be analyzed subsequently, in the obtained list of high-frequency related words, screen out the words that contain non-written, networked, and inexpressible words in official expressions, such as "Bikego" and "Bicycle Coming", etc., and sort out several related words for each central word.

[0116] S2034. Collect the official documents related to the digital life circle, and count the word frequencies of each related word in the official documents.

[0117] In this embodiment, the official documents related to the digital life circle collected include industry standards, national standards, local standards, and policy documents; use the online text analysis tool Voyant Tools, import the collected official documents, and count the frequencies of the related words of each index in the official documents.

[0118] S204. According to the word frequencies of each related word in the official documents, determine the weight ranking of each index through the high-dimensional sorting weight method.

[0119] Further, this step S204 specifically includes:

[0120] S2041. Calculate the total frequency of the related words corresponding to the central word of each index, and divide it by the number of related word items to eliminate the influence of the number of related words, and obtain the average value of the word frequencies of the index-related words.

[0121] S2042. Sort the average values of the word frequencies in descending order from high to low to obtain the weight ranking of each index.

[0122] In this embodiment, sort the average values of the word frequencies in descending order from high to low, that is, the higher the word frequency, the lower the serial number, and obtain the weight ranking of each index. The four indexes of the digital level and the two indexes of the digital potential are sorted as shown in Table 1 and Table 2 respectively;

[0123] Table 1

[0124]

[0125] Table 2

[0126]

[0127] In the weighting process, the importance of different indicators is determined according to the frequency of mention in official documents. The importance of different indicators is only ranked instead of being directly assigned weights. This greatly reduces the complexity and uncertainty of indicator weighting and avoids the subjectivity of manual ranking. At the same time, it closely links the comprehensive evaluation with urban development policies and enhances the reference value of the evaluation results.

[0128] S205. According to various indicators and their weight rankings, a digital life circle boundary recognition result is obtained through dual linear programming calculation.

[0129] Furthermore, step S205 specifically includes:

[0130] S2051. Based on the evaluation indicators of the digital level of life services and the weight ranking, substitute them into the dual linear programming formula, calculate the digital level of life services, and identify the core circle of the digital life circle.

[0131] S2052. Substitute the digital potential indicators of life services and the weight ranking into the dual linear programming formula to calculate the digital potential of life services and identify the expansion circle of the digital life circle.

[0132] In this embodiment, the derivation process of the even linear programming formula is as follows:

[0133] For the values ​​of k indicators of related word frequency from large to small, n1, n2, ..., n k , the corresponding index weight ranking is w1≥w2≥…≥w k In order to calculate the comprehensive index (the index of the level of digitalization of living services or the index of the potential for digitalization of living services) First, the optimal comprehensive index under this weight ranking is defined as The worst comprehensive index is They represent the highest possible score and the lowest possible score of the comprehensive index under a given weight ranking, namely:

[0134]

[0135] Among them, w p Indicates the weight of the indicator with weight ranking p, n p It represents the value of the indicator with weight ranking p, and k is the number of indicators.

[0136] In order to solve the problem of unknown specific values ​​of weights and ensure that the sum of all weights is 1, the weights are first standardized and a new variable v is introduced p To indicate the relative size of the weight, the new variable will replace the weight sort w pIt is used to solve the optimal comprehensive index and the worst comprehensive index, which are converted by the following formula:

[0137]

[0138] Formula (7) can be further equivalent to:

[0139]

[0140] The converted weight w p is the new variable v p The accumulation of , through the conversion of this step to achieve the standardized expression of weight, substituting formula (8) into formula (4) and formula (6), the original problem can be converted into the following form:

[0141]

[0142] To further simplify the formula, we introduce the variable Substituting into formula (9), we get the following form:

[0143]

[0144] Formula (10) can be regarded as the left group of the asymmetric dual formula (11), and the right group of the formula is its dual problem. According to the duality theory of linear programming, the maximum linear programming problem of formula (10) can be converted into the minimum linear programming problem:

[0145]

[0146] Where b is a constant. According to formula (11), the dual problem of formula (10) is:

[0147]

[0148] The solution can be directly determined from the form and constraints of formula (12). According to the duality theory, the solution is also the solution of formula (10), so we can get:

[0149]

[0150] Similarly, another dual linear programming problem can be constructed to solve That is, the minimum possible value of the comprehensive index under a given weight ranking, and the derivation results are as follows:

[0151]

[0152] Finally, through the optimal comprehensive index and the worst comprehensive index Get the comprehensive index The specific formula is as follows:

[0153]

[0154] in, represents the life service digitalization level index or life service digitalization potential index of object i determined by k indicators, It represents the optimal value of the weighted scores of each dimension, that is, the highest possible score of the comprehensive index under a given weight ranking. It represents the worst value of the weighted scores of each dimension, that is, the lowest possible score of the comprehensive index under a given weight ranking.

[0155] Specifically, when the digital facility coverage index index of grid x is as shown in Table 1, it is as follows:

[0156]

[0157] The digital level of its life services

[0158] When the index of the life service digitalization potential index of grid x is as shown in Table 2, it is as follows:

[0159]

[0160] The potential of digital life services

[0161] The calculation results of the digitalization level and digitalization potential of life services are as follows: Figure 7 and Figure 8 shown.

[0162] This embodiment is based on the calculation results of the digitalization level of life services, and is divided into 5 levels from low to high using the natural break point method. The research area is correspondingly divided into low-level, medium-low level, medium level, medium-high level and high level areas. Among them, areas with medium and above levels of digitalization of life services constitute the core circle of the digital life circle.

[0163] This embodiment is based on the calculation results of the digitalization potential of life services, and is divided into five levels from low to high using the natural breakpoint method. The research area is correspondingly divided into low potential, medium-low potential, medium potential, medium-high potential and high potential areas. Among them, areas with medium and above digitalization potential of life services constitute the extended circle of the digital life circle.

[0164] This embodiment uses the above method to identify the boundary of the Yuexiu District digital life circle. The results are as follows: Fig. 9As shown in the figure, the coverage of the core circle does not reach most of the marginal areas, indicating that the level of digitalization of life services is relatively low in the administrative boundary areas of Yuexiu District. The traditional identification of the boundaries of living circles mostly uses the boundaries of communities as analysis units, and the division results are difficult to reflect the differences within the community. This embodiment uses a fishing net to divide the study area, revealing that there are differences in the digitalization levels of different areas within the same calculation unit, providing more targeted and reasonable support for the planning and decision-making of digital construction.

[0165] It should be noted that although the method operations of the above embodiments are described in a specific order, this does not require or imply that these operations must be performed in this specific order, or that all the operations shown must be performed to achieve the desired results. On the contrary, the steps depicted can be performed in a different order. Additionally or alternatively, some steps can be omitted, multiple steps can be combined into one step, and / or one step can be decomposed into multiple steps.

[0166] Embodiment 2:

[0167] like Fig.10 As shown, this embodiment provides a central urban digital life circle boundary recognition system, which includes a first calculation module 1001, a second calculation module 1002, a statistics module 1003, a determination module 1004 and an identification module 1005. The specific functions of each module are as follows:

[0168] The first calculation module 1001 is used to obtain the distribution data of various digital facilities in the study area and calculate the coverage rate of various digital facilities as an evaluation index of the digital level of life services;

[0169] The second calculation module 1002 is used to obtain the population education level data and mobile phone signal base station distribution data in the study area, and calculate the life service digitalization potential index in the study area;

[0170] The statistical module 1003 is used to determine the core word of each indicator, match a number of related words for each core word through corpus search, and count the frequency of each related word in the official document;

[0171] A determination module 1004 is used to determine the weight ranking of each indicator according to the frequency of each related word in the official document through a high-dimensional ranking weight method;

[0172] The identification module 1005 is used to obtain the digital life circle boundary identification result through dual linear programming calculation according to various indicators and the weight ranking of various indicators.

[0173] It should be noted that the system provided in this embodiment is only illustrated by the division of the above-mentioned functional modules. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure can be divided into different functional modules to complete all or part of the functions described above.

[0174] Embodiment 3:

[0175] This embodiment provides a computer device, such as Fig.11 As shown, it includes a processor 1102, a memory, an input device 1103, a display device 1104 and a network interface 1105 connected through a system bus 1101. The processor is used to provide computing and control capabilities. The memory includes a non-volatile storage medium 1306 and an internal memory 1107. The non-volatile storage medium 1106 stores an operating system, a computer program and a database. The internal memory 1107 provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. When the processor 1102 executes the computer program stored in the memory, the method for identifying the boundary of the central urban digital living circle of the above-mentioned embodiment 1 is implemented as follows:

[0176] Obtain the distribution data of various digital facilities in the study area, calculate the coverage rate of various digital facilities, and use them as evaluation indicators for the digital level of life services; obtain the data on the cultural level of the population and the distribution data of mobile phone signal base stations in the study area, and calculate the digital potential indicators of life services in the study area; determine the central word of each indicator, and match a number of related words for each central word through corpus retrieval, and count the frequency of each related word in official documents; determine the weight ranking of each indicator based on the frequency of each related word in official documents through high-dimensional sorting weight method; obtain the boundary identification results of the digital life circle through dual linear programming calculation based on each indicator and its weight ranking.

[0177] Embodiment 4:

[0178] This embodiment provides a storage medium, which is a computer-readable storage medium, storing a computer program. When the computer program is executed by a processor, the method for identifying the boundary of the central urban digital living circle of the above embodiment 1 is implemented as follows:

[0179] Obtain the distribution data of various digital facilities in the study area, calculate the coverage rate of various digital facilities, and use them as evaluation indicators for the digital level of life services; obtain the data on the cultural level of the population and the distribution data of mobile phone signal base stations in the study area, and calculate the digital potential indicators of life services in the study area; determine the central word of each indicator, and match a number of related words for each central word through corpus retrieval, and count the frequency of each related word in official documents; determine the weight ranking of each indicator based on the frequency of each related word in official documents through high-dimensional sorting weight method; obtain the boundary identification results of the digital life circle through dual linear programming calculation based on each indicator and its weight ranking.

[0180] It should be noted that the computer-readable storage medium of the present embodiment may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0181] In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device, or device. In this embodiment, the computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal medium may also be any computer-readable storage medium other than a computer-readable storage medium, which may send, propagate, or transmit a program used by or in combination with an instruction execution system, device, or device. The computer program contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0182] The computer readable storage medium can be written in one or more programming languages ​​or a combination thereof to execute the computer program of the present embodiment, and the programming language includes an object-oriented programming language, such as Java, Python, C++, and also includes a conventional procedural programming language, such as C language or a similar programming language. The program can be executed entirely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on a remote computer, or completely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (e.g., using an Internet service provider to connect through the Internet).

[0183] In summary, the present invention utilizes multi-source data to construct a comprehensive evaluation index of the digitalization level and digitalization potential of life services, realizes the boundary identification of the digital life circle of the central urban area, and helps to improve the pertinence and rationality of urban digital construction planning decisions; compared with the existing technology, the present invention has a more objective vision and stronger operability, and also provides a new idea for the definition of the digital life circle.

[0184] The above description is only a preferred embodiment of the present invention. It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and the present invention can be implemented in other specific forms without departing from the spirit or basic features of the present invention. Therefore, no matter from which point of view, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is defined by the appended claims rather than the above description, and it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims are included in the present invention.

Claims

1. A method for identifying the boundary of a central urban digital living circle, characterized in that: The method comprises: Obtain the distribution data of various digital facilities in the study area and calculate the coverage rate of various digital facilities as an evaluation indicator of the digital level of life services; Obtain data on the educational level of the population and the distribution of mobile phone signal base stations in the study area, and calculate the potential indicators for digitalization of life services in the study area; Determine the core word of each indicator, match a number of related words to each core word through corpus search, and count the frequency of each related word in official documents; According to the frequency of each relevant word in the official documents, the weight ranking of each indicator is determined through the high-dimensional ranking weight method; According to various indicators and their weight ranking, the digital life circle boundary identification results are obtained through dual linear programming calculation.

2. The method for identifying the boundary of a central urban digital living circle according to claim 1, characterized in that: The weight ranking of each indicator is determined according to the frequency of each related word in the official document through a high-dimensional ranking weight method, specifically including: Calculate the total frequency of related words corresponding to each indicator core word, divide it by the number of related words to eliminate the influence of the number of related words, and get the average frequency of the indicator related words; Sort the average values ​​of word frequency in reverse order from high to low to obtain the weight ranking of each indicator.

3. The method for identifying the boundary of a central urban digital living circle according to claim 1, characterized in that: According to the various indicators and the weight ranking of the various indicators, the digital life circle boundary identification result is obtained through dual linear programming calculation, which specifically includes: According to the evaluation indicators of the digital level of life services and the weight ranking, the dual linear programming formula is substituted to calculate the digital level of life services and identify the core circle of the digital life circle; According to the digital potential indicators of life services and the weight ranking, substitute them into the dual linear programming formula to calculate the digital potential of life services and identify the expansion circle of the digital life circle.

4. The method for identifying the boundary of the central urban digital living circle according to claim 3 is characterized in that: The dual linear programming formula is as follows: in, represents the life service digitalization level index or life service digitalization potential index of object i determined by k indicators, represents the optimal value of the weighted score of each dimension, It represents the worst value of the weighted scores of each dimension. Indicates the indicator data with weight ranking p.

5. The method for identifying the boundary of the central urban digital living circle according to claim 1, characterized in that: The calculation of the coverage of various digital facilities specifically includes: Divide the vector map plane of the study area into grids to form a number of grids of equal size with serial numbers; The distribution data of various digital facilities are screened and further processed. In each grid, the coverage rate of various digital facilities is calculated respectively, so that the facility distribution data can form the digital level index of life services, as shown in the following formula: in, Indicates that facility i is in a certain grid The coverage rate on Representation Grid The number of facilities on represents the total number of facility i in the study area.

6. The method for identifying the boundary of a central urban digital living circle according to claim 1, characterized in that: The indicators of digitalization potential of life services in the calculation research area include: Starting from the boundary of the research area, a certain radius is extended outward, and the buffer distance is consistent with the maximum service radius of digital facilities in the indicator system, which serves as the extended research area for defining the extended circle of the digital life circle; Divide the newly added buffer area in the expanded study area into multiple grids and number them; The data on population education level and mobile phone base station distribution are screened and further processed to calculate the potential indicators for digitalization of life services in each grid.

7. The method for identifying the boundary of the central urban digital living circle according to claim 6, characterized in that: The indicators of digitalization potential of life services include the coverage rate of the population with secondary school education and above and the coverage rate of mobile phone signal base stations; The data on population education level and mobile phone signal base station distribution are screened and further processed to calculate the potential indicators of digitalization of life services in each grid, including: According to the population education level SDK data, the distribution location and total number of people with a high school education or above in the expanded study area are obtained, and connected to each grid to obtain the number of people with a high school education or above in each grid; Divide the number of people with a secondary school education or above in a single grid by the total number of people with a secondary school education or above to calculate the coverage rate of the population with a secondary school education or above in each grid, as follows: in, It represents the coverage rate of the population with a high school education or above in a certain grid a. It represents the number of people with a high school education or above on grid a. It represents the total number of people with a secondary school education or above in the extended study area; According to the base station distribution location information in the mobile phone signal base station data, the distribution location and total number of mobile phone signal base stations in the expanded study area are obtained, and connected to each grid to obtain the number of mobile phone signal base stations distributed in each grid; Calculate the mobile phone signal base station coverage index on each grid as follows: in, Indicates the coverage rate of mobile phone signal base stations on a certain grid a, represents the number of mobile phone signal base stations on grid a, Represents the total number of mobile phone signal base stations in the extended study area.

8. A central urban digital life circle boundary recognition system, characterized in that: The system comprises: The first calculation module is used to obtain the distribution data of various digital facilities in the study area and calculate the coverage rate of various digital facilities as an evaluation index of the digital level of life services; The second calculation module is used to obtain the data on the educational level of the population and the distribution data of mobile phone signal base stations in the study area, and calculate the potential indicators of digitalization of life services in the study area; The statistical module is used to determine the core word of each indicator, match a number of related words to each core word through corpus search, and count the frequency of each related word in official documents; A determination module is used to determine the weight ranking of each indicator based on the frequency of each related word in the official document through a high-dimensional ranking weight method; The identification module is used to obtain the digital life circle boundary identification result through dual linear programming calculation according to various indicators and their weight sorting.

9. A computer device comprising a processor and a memory for storing a program executable by the processor, characterized in that: When the processor executes the program stored in the memory, the method for identifying the boundary of the central urban digital living circle according to any one of claims 1 to 7 is implemented.

10. A storage medium storing a program, characterized in that: When the program is executed by a processor, the method for identifying the boundary of a central urban digital living circle as described in any one of claims 1 to 7 is implemented.

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