Method, device and equipment for determining village and town development mode based on POI data

Abstract

The invention provides a method, device and equipment for determining a village and town development mode based on POI data, and the method comprises the steps: obtaining initial POI index data in a target region in real time, the target region comprises a plurality of villages and town, and each village and town correspondingly comprises a plurality of types of initial POI index data; according to the attribute information of the initial POI index data, determining target POI index data and evaluation dimension indexes corresponding to each village and town in the target area; according to the target POI index data, determining a comprehensive development index and a coupling coordination index of each village and town in the target area under the corresponding evaluation dimension index; and determining a target development mode corresponding to each village and town in the target area according to the comprehensive development index and the coupling coordination degree index. According to the scheme, the efficiency and precision of rural POI data management and analysis are improved, the rural development mode is accurately judged, and scientific support and basis are provided for sustainable development of rural areas.

Description

Technical Field

[0001] The present invention relates to the field of data information processing technology, and in particular to a method, device and equipment for determining a village and town development model based on POI data. Background Art

[0002] Currently, existing methods for collecting POI (Point of Interest) data in villages and towns primarily include third-party API calls, web crawler technology, collaborative data sharing, and manual on-site collection. POI data analysis techniques primarily involve traditional statistical analysis, spatial analysis, machine learning, and artificial intelligence methods. Although these technologies are relatively mature in urban areas, they still face significant limitations in rural areas: villages and towns have a wide geographical area, relatively limited data acquisition channels, weak infrastructure, and a low level of digital development. These factors lead to prominent issues in POI data collection, such as incomplete information, delayed updates, and low data accuracy. Furthermore, POI data provided by different map service providers differ in classification standards, information detail, and coordinate systems, posing challenges to data standardization and fusion analysis.

[0003] In practical applications, existing POI data processing technologies commonly suffer from challenges such as difficulty in deduplication, complex classification and consolidation, inefficient data fusion, prone to errors and omissions in manual operations, high processing costs, and a lack of a real-time interactive visualization analysis platform. Furthermore, the data analysis stage faces bottlenecks such as a single, inadequate evaluation model, and difficulty in effectively identifying differentiated development models for villages and towns. A technical system integrating intelligent data collection, integration, processing, and multi-dimensional comprehensive analysis is urgently needed to address these issues. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a method, device and equipment for determining the village and town development model based on POI data, so as to realize the automation, intelligence and efficiency of the whole process from data collection, data processing to in-depth data analysis, and provide scientific and reliable data support and decision-making basis for the sustainable development of village and town areas.

[0005] To solve the above technical problems, an embodiment of the present invention provides a method for determining a village and town development model based on POI data, comprising:

[0006] Acquire initial POI indicator data in a target area in real time, where the target area includes multiple villages and towns, and each village and town corresponds to multiple different types of initial POI indicator data;

[0007] Determining target POI index data and evaluation dimension indicators corresponding to each village and town in the target area based on the attribute information of the initial POI index data;

[0008] Determine the comprehensive development index and coupling coordination index of each village and town in the target area under the evaluation dimension indicators based on the target POI indicator data;

[0009] The target development model corresponding to each village and town in the target area is determined according to the comprehensive development index and the coupling coordination index.

[0010] In one embodiment, the target POI index data and evaluation dimension indicators corresponding to each village or town in the target area are determined based on the attribute information of the initial POI index data, including:

[0011] Matching the initial POI indicator data to each village and town in the target area according to the address information and spatial coordinate information of the initial POI indicator data to determine target POI indicator data corresponding to each village and town;

[0012] Based on the name information and data type information of the target POI indicator data corresponding to each village and town, the evaluation dimension indicators of each village and town are determined, and the evaluation dimension indicators include different types of target POI indicator data.

[0013] In one embodiment, based on the target POI index data, determining the comprehensive development index and coupling coordination index of each village and town in the target area under the evaluation dimension indicators includes:

[0014] Constructing a grey correlation system for the villages and towns in the target area, where all target POI indicator data for each village and town corresponds to a grey correlation system;

[0015] Determine the dimensional development index of each village and town in the target area under the corresponding evaluation dimension indicator based on the grey correlation system and the target POI index data;

[0016] According to the dimensional development index under the corresponding evaluation dimension and the preset coupling coordination model, the comprehensive development index and coupling coordination index of each village and town in the target area are determined.

[0017] In one embodiment, based on the grey correlation system and the target POI index data, determining the dimensional development index of each village and town in the target area under the corresponding evaluation dimension index includes:

[0018] Based on a preset weight algorithm, determine the target weight of each type of target POI indicator data in the target POI indicator data of each village and town;

[0019] Based on the target POI index data of each village and town, determine the grey correlation coefficient of the grey correlation system corresponding to each village and town;

[0020] According to the target weight and grey correlation coefficient under the corresponding evaluation dimension, the dimensional development index of each village and town under the corresponding evaluation dimension is determined.

[0021] In one embodiment, based on a preset weighting algorithm, the target weight of each type of target POI index data in the target POI index data of each village or town under the corresponding evaluation dimension index is determined, including:

[0022] Determine the proportion of each type of target POI indicator data in all target POI indicator data of all villages and towns;

[0023] The target weight of each type of target POI indicator data is determined according to the proportion value and the preset weight algorithm.

[0024] In one embodiment, based on the target POI index data of each village or town, the grey correlation coefficient of the grey correlation system corresponding to each village or town is determined, including:

[0025] Determining a reference sequence corresponding to the target POI indicator data within the target area based on the target POI indicator data of each village and town within the target area;

[0026] Based on the comparison sequence corresponding to the target POI index data of each village and town and the reference sequence, the grey correlation coefficient of the grey correlation degree system corresponding to each village and town is determined.

[0027] In one embodiment, determining a target development model corresponding to each village or town in the target area based on the comprehensive development index and the coupling coordination index includes:

[0028] When the comprehensive development index is greater than or equal to a first preset threshold, and the coupling coordination index is greater than or equal to a second preset threshold, determining that the current village or town in the target area is a comprehensive development type;

[0029] When the comprehensive development index is greater than or equal to a first preset threshold and the coupling coordination index is less than a second preset threshold, the current village or town in the target area is determined to be a characteristic advantage type;

[0030] When the comprehensive development index is greater than or equal to a third preset threshold and the comprehensive development index is less than the first preset threshold, determining that the current village or town in the target area is a potential to be tapped type;

[0031] When the comprehensive development index is greater than or equal to a fourth preset threshold, the comprehensive development index is less than the third preset threshold, and the coupling coordination index is greater than or equal to a second preset threshold, it is determined that the current village or town in the target area is a slow-developing type;

[0032] When the comprehensive development index is greater than or equal to a fourth preset threshold, the comprehensive development index is less than the third preset threshold, and the coupling coordination index is less than the second preset threshold, the current village or town in the target area is determined to be a transformation development type;

[0033] When the comprehensive development index is less than a fourth preset threshold, the current village or town in the target area is determined to be a backward development type, and the first preset threshold>the third preset threshold>the fourth preset threshold>the second preset threshold.

[0034] An embodiment of the present invention further provides a device for determining a village and town development model based on POI data, comprising:

[0035] An acquisition module is used to acquire initial POI indicator data in a target area in real time, where the target area includes multiple villages and towns, and each village and town corresponds to multiple different types of initial POI indicator data;

[0036] A processing module is used to determine the target POI index data and evaluation dimension indicators corresponding to each village and town in the target area based on the attribute information of the initial POI index data; determine the comprehensive development index and coupling coordination index of each village and town in the target area under the evaluation dimension indicators based on the target POI index data; and determine the target development model corresponding to each village and town in the target area based on the comprehensive development index and the coupling coordination index.

[0037] An embodiment of the present invention further provides a computing device, comprising:

[0038] a memory for storing one or more programs;

[0039] One or more processors are used to execute the one or more programs to implement the method described above.

[0040] An embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a program, and when the program is executed by a processor, the method described above is implemented.

[0041] The above solution of the present invention includes at least the following beneficial effects:

[0042] The above-mentioned solution of the present invention provides a method, device and equipment for determining the development model of villages and towns based on POI data, which obtains the initial POI index data in the target area in real time, wherein the target area contains multiple villages and towns, and each village and town corresponds to a plurality of different types of initial POI index data; according to the attribute information of the initial POI index data, the target POI index data and evaluation dimension index corresponding to each village and town in the target area are determined; according to the target POI index data, the comprehensive development index and coupling coordination index of each village and town in the target area under the evaluation dimension index are determined; according to the comprehensive development index and the coupling coordination index, the target development model corresponding to each village and town in the target area is determined. The solution provided by the above-mentioned embodiment of the present invention realizes the automation, intelligence and efficiency of the whole process from data collection, data processing to in-depth data analysis, provides scientific and reliable data support and decision-making basis for the sustainable development of rural areas, and effectively promotes the informatization, refinement and intelligent management process of villages and towns. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 This is a flow chart of a method for determining a village and town development model based on POI data provided by an embodiment of the present invention;

[0044] Figure 2 This is a schematic block diagram of a module block of a device for determining a village and town development model based on POI data provided by an embodiment of the present invention;

[0045] Figure 3 is a schematic block diagram of an electronic device provided by an embodiment of the present invention;

[0046] Figure 4 is a schematic block diagram of a computing device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0047] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0048] In the following description, for the purpose of illustrating the various disclosed embodiments, certain specific details are set forth in order to provide a thorough understanding of the various disclosed embodiments. However, those skilled in the relevant art will recognize that the embodiments may be practiced without one or more of these specific details. In other cases, well-known devices, structures, and techniques associated with this application may not be shown or described in detail to avoid unnecessarily obscuring the description of the embodiments.

[0049] Reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment. Thus, the appearances of "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment.

[0050] like Figure 1 As shown, an embodiment of the present invention provides a method for determining a village and town development model based on POI data, comprising:

[0051] Step 11: Acquire initial POI indicator data in the target area in real time. The target area includes multiple villages and towns, and each village and town corresponds to multiple different types of initial POI indicator data.

[0052] Step 12: Determine the target POI index data and evaluation dimension indicators corresponding to each village and town in the target area based on the attribute information of the initial POI index data;

[0053] Step 13: Determine the comprehensive development index and coupling coordination index of each village and town in the target area under the evaluation dimension indicators based on the target POI indicator data;

[0054] Step 14: Determine the target development model for each village and town in the target area based on the comprehensive development index and the coupling coordination index.

[0055] In this embodiment, the initial POI indicator data can be POI data in map software such as Amap, which is crawled by the server through the Internet. POI data can be specifically understood as point data containing name information, address information, spatial coordinate information, and type information. Here, after the initial POI indicator data is collected, the initial POI indicator data can be preliminarily cleaned to remove null values, obvious outliers, format errors or incomplete data, duplicate and redundant data entries, so as to ensure the data quality of subsequent analysis. Preferably, the initial POI indicator data can be identified and processed by combining multiple matching rules with fuzzy matching algorithms in the preliminarily cleaning process to ensure the accuracy and uniqueness of the data.

[0056] Furthermore, based on the attribute information of the initially cleaned POI indicator data, the POI indicator data can be matched to each village and town to determine the target POI indicator data and evaluation dimension indicators corresponding to each village and town. Here, each village and town can correspond to multiple evaluation dimension indicators, and each evaluation dimension indicator can contain multiple types of target POI indicator data. Each evaluation dimension indicator counts the number of target POI indicator data separately, forming an accurate and objective data matrix, laying the foundation for the subsequent calculation of the comprehensive development index and coupling coordination index.

[0057] Here, the evaluation dimension indicators of each village and town may include but are not limited to economic dimension indicators, social dimension indicators, resource dimension indicators, transportation dimension indicators, and organizational management dimension indicators. In this embodiment and the following embodiments, these five evaluation dimension indicators are used as examples for explanation. However, it should be noted that when no corresponding target POI indicator data is collected under any evaluation dimension indicator of any village and town, the evaluation dimension indicator corresponding to the village and town is missing, but this does not affect the evaluation of the development model of the village and town by other evaluation dimension indicators.

[0058] Furthermore, the target POI indicator data of each village and town under each evaluation dimension indicator are processed to determine the corresponding comprehensive development index and coupling coordination index of each village and town in the target area under the evaluation dimension indicator; multiple evaluation dimension indicators form an evaluation system for village and town development models to accurately reveal the coordinated development level and key influencing factors of villages and towns in multiple dimensions, thereby overcoming the limitations of traditional single model analysis methods, accurately reflecting the multidimensional characteristics of village and town development, and realizing a comprehensive, objective and in-depth quantitative analysis of the village and town development level, thereby providing scientific and reliable data support and decision-making basis for the sustainable development of village and town areas, effectively promoting the informatization, refinement and intelligent management of villages and towns, and having significant application value and promotion prospects.

[0059] In an optional embodiment of the present invention, the above step 12 may include:

[0060] Step 121 , matching the initial POI indicator data to each village or town in the target area based on the address information and spatial coordinate information of the initial POI indicator data to determine the target POI indicator data corresponding to each village or town;

[0061] Step 122 : Based on the name information and data type information of the target POI index data corresponding to each village or town, an evaluation dimension index for each village or town is determined, where the evaluation dimension index includes different types of target POI index data.

[0062] In this embodiment, a multi-level spatial data classification and aggregation technology can be applied. First, the POI indicator data after preliminary cleaning is classified into corresponding village and town areas based on the spatial analysis algorithm (coordinate system conversion) and spatial matching rules (fuzzy matching algorithm) to determine the target POI indicator data for each village and town. Secondly, within each village and town area, detailed classification and statistics are further performed according to the name information and data type information of the target POI indicator data to classify the target POI indicator data of each village and town into different evaluation dimension indicators to form highly structured spatial data. Preferably, the target POI indicator data can be unified into a standardized structured database or data table to ensure the consistency and integrity of data storage, thereby enhancing the usability of the data and improving the efficiency of subsequent data analysis. Here, the POI indicator data after preliminary cleaning is further processed by the spatial analysis algorithm and spatial matching rules, solving the problems of heterogeneous multi-source data and inconsistent spatial accuracy, and laying a standardized data foundation for subsequent analysis. Here, both the spatial analysis algorithm and the spatial matching rules can be implemented through existing coordinate system conversion and fuzzy matching algorithms.

[0063] In order to ensure the scientific nature and pertinence of the evaluation system, the POI index data can be specifically divided into the following five evaluation dimension indicators based on the characteristics of POI data of spatial geographic big data. Among them, the target POI index data included in the economic dimension indicators are: covering three types of data: companies and enterprises (170000), commercial residences (120000), and automobile sales (020000), to reflect the economic activity and commercial development level of villages and towns; the target POI index data included in the social dimension indicators are: automobile services (010000), automobile repairs (030000), motorcycle services (040000), financial and insurance services (160000), catering services (050000), shopping services (060000), life services (070000), sports and leisure services (080000), medical care services (090000), accommodation services (100000), science and technology and cultural services (140000), etc. 00) contains eleven data categories to accurately reflect the public services, residents' convenience, and social vitality of villages and towns. The resource dimension includes two target POI indicator data categories: scenic spots (110,000) and place name and address information (190,000) to reflect the resource endowment and regional cultural characteristics of villages and towns. The transportation dimension includes two target POI indicator data categories: transportation facilities and services (150,000) and road ancillary facilities (180,000) to reflect the convenience of transportation within and outside the village and town area and the level of infrastructure development. The organizational management dimension includes two target POI indicator data categories: government agencies and social groups (130,000) and public facilities (200,000) to reflect the administrative governance and public management capabilities of villages and towns. Here, the number of target POI indicator data for each evaluation dimension is counted to form an accurate and objective data matrix, laying the foundation for the subsequent calculation of the comprehensive development index and coupling coordination index.

[0064] Preferably, the POI (point of interest) index data of villages and towns in the target area can be obtained in real time by calling the web service interface of AutoNavi Maps based on the GCJ02 coordinate system and using automated crawling technology, as shown in Table 1.

[0065] Table 1. Different types of POI indicator data and their corresponding codes

[0066]

[0067]

[0068] Since the absolute values ​​of various target POI index data of different villages and towns may vary greatly, in an optional embodiment of the present invention, the POI index data after preliminary cleaning can be dimensionlessly normalized by using the range normalization method; here, the original data of the j-th preliminary cleaned POI index data of the i-th village and town can be expressed as x i (j) (here, the j-th preliminary cleaned POI indicator data refers to the j-th type of POI indicator data);

[0069] For the benefit POI indicator data, its standardized processing can be expressed as:

[0070]

[0071] For cost-based POI indicator data, its standardization can be expressed as:

[0072]

[0073] Among them, x max (j) and x min (j) represents the maximum and minimum values ​​of the j-th POI index data of all villages and towns, and the standardized data x ij In the interval [0, 1], the data is standardized to ensure comparability and reliability.

[0074] In an optional embodiment of the present invention, the above step 13 may include:

[0075] Step 131 : constructing a grey correlation system of villages and towns within the target area. All target POI index data of each village and town correspond to one grey correlation system.

[0076] In the process of confirming the development model of village and town construction, village and town construction can be abstracted as a grey correlation system in which multiple factors influence each other (the multiple factors here can be regarded as different types of POI indicator data). This grey correlation system has obvious characteristics such as hierarchical complexity, structural relationship fuzziness, dynamic change randomness, and incompleteness and uncertainty of POI indicator data. Here, a comprehensive evaluation of the development model of villages and towns is conducted based on the grey correlation system to ensure the accuracy and reliability of the evaluation.

[0077] In an optional embodiment of the present invention, the above step 13 may further include:

[0078] Step 132: Determine the dimensional development index of each village or town in the target area under the corresponding evaluation dimension indicator based on the grey correlation system and the target POI index data;

[0079] Here, the comprehensive development index is used to objectively evaluate the overall performance level of villages and towns in terms of economy, society, resources, transportation, organizational management and other dimensions. The closer the comprehensive development index is to 1, the better the overall development of the village and town.

[0080] In an optional embodiment of the present invention, the above step 132 may specifically include:

[0081] Step 1321: Determine the target weight of each type of target POI index data in the target POI index data of each village or town based on a preset weight algorithm;

[0082] Step 1322: Determine the grey correlation coefficient of the grey correlation system corresponding to each village or town based on the target POI index data of each village or town;

[0083] In this embodiment, the preset weighting algorithm may be an entropy weighting method, which objectively modifies the proportion of each target POI indicator data according to the degree of variability of the target POI indicator data. The smaller the information entropy of the target POI indicator data, the greater its variability, the more information it can provide, and the greater its role in the comprehensive evaluation.

[0084] Furthermore, after determining the grey correlation coefficients between various target POI indicator data in the grey correlation system corresponding to each village and town, the target weights of each type of target POI indicator data are weighted based on the grey correlation coefficients of the various types of target POI indicator data to obtain the dimensional development index under the corresponding evaluation dimension indicator, thereby ensuring the accuracy and objectivity of the subsequent village and town development model determination.

[0085] In an optional embodiment of the present invention, the above step 1321 may include:

[0086] Step 13211, determining the proportion of each type of target POI indicator data in all target POI indicator data of all villages and towns;

[0087] Here, the standardized target POI index data is proportionally calculated to determine the proportion value P of the jth target POI index data of each village and town. ij for:

[0088]

[0089] Here, n represents the sample size, that is, the number of villages and towns in the target area.

[0090] Furthermore, the above step 1321 may further include:

[0091] Step 13212: Determine the target weight of each type of target POI indicator data based on the proportion value and the preset weight algorithm.

[0092] Here, according to the proportion of the j-th target POI index data of each village and town, P ij , the information entropy e of the j-th target POI index data can be determined j for:

[0093]

[0094] in,

[0095] Furthermore, according to the information entropy e of the j-th target POI index data j , we can determine the corresponding information utility d j for:

[0096] d j =1-e j ;

[0097] Furthermore, according to the information utility d of the j-th target POI indicator data j , the corresponding target weight w can be determined j for:

[0098]

[0099] Among them, w j =[0,1], and ∑w j =1, m represents the number of target POI indicator data.

[0100] In an optional embodiment of the present invention, the above step 1322 may include:

[0101] Step 13221: Determine a reference sequence corresponding to the target POI index data in the target area based on the target POI index data of each village or town in the target area;

[0102] Step 13222: Based on the comparison sequence and reference sequence corresponding to the target POI index data of each village or town, determine the grey correlation coefficient of the grey correlation system corresponding to each village or town.

[0103] In this embodiment, the reference sequence is a sequence composed of the optimal standard values ​​corresponding to various types of POI indicator data. The reference sequence is composed of the optimal standard values ​​of various types of POI indicator data. The reference sequence is recorded as x0, which can be specifically expressed as x0 = {x0(1), x0(2), ..., x0(m)}. The compared sequence in the association analysis is generally recorded as x i , the expression is x i ={x i (1),x i (2),...,x i(m)}, where the comparison sequence is a sequence of target POI indicator data actually collected for each village or town in the comparison order;

[0104] Furthermore, the grey relational coefficient ξ i (j) can be expressed as:

[0105]

[0106] Among them, ξ i (j) represents the grey correlation coefficient of the j-th target POI index data in the i-th village (that is, the relative strength of the influence of the j-th target POI index data on the optimal standard value of the corresponding category of POI index data in the reference sequence); Indicates the minimum absolute error value of each target POI indicator data, It represents the maximum absolute error value of each target POI indicator data, ξ∈[0,1] represents the resolution coefficient, generally ξ≤0.5.

[0107] In an optional embodiment of the present invention, the above step 132 may further include:

[0108] Step 1323, based on the target weight and grey correlation coefficient under the corresponding evaluation dimension, determine the dimensional development index corresponding to each village and town under the corresponding evaluation dimension indicator.

[0109] Here, the dimensional development index of each village and town in the corresponding dimension can be determined based on the target weight of the target POI indicator data in each evaluation dimension and the corresponding grey correlation coefficient. The specific dimensional development index can be expressed as:

[0110]

[0111] Among them, F k ,k∈[1,2,...,5], respectively represents the corresponding dimension development index under the economic dimension indicator, social dimension indicator, resource dimension indicator, transportation dimension indicator and organizational management dimension indicator; m k It is expressed as the number of target POI indicator data under the kth evaluation dimension indicator.

[0112] In an optional embodiment of the present invention, the above step 13 may further include:

[0113] Step 133: Determine the comprehensive development index and coupling coordination index of each village and town in the target area based on the dimensional development index under the corresponding evaluation dimension indicator and the preset coupling coordination model.

[0114] In this embodiment, a preset coupling coordination model is used to measure the degree of coordinated development among the five dimensions of economic dimension indicators, social dimension indicators, resource dimension indicators, transportation dimension indicators, and organizational management dimension indicators. The closer the index is to 1, the more coordinated the dimensions are, and the closer it is to 0, the more serious the imbalance of development between the dimensions.

[0115] Furthermore, based on the dimensional development index under the corresponding evaluation dimension indicator, the comprehensive development index of each village and town can be determined. The comprehensive development index can be expressed as:

[0116]

[0117] Among them, w k Represents dimension weight; here, the dimension weight confirmation process is the same as the target weight confirmation process of the above-mentioned target POI indicator data, and will not be repeated here.

[0118] Here, we can first determine the coupling index C of each village and town based on the comprehensive development index. The coupling index C can be expressed as:

[0119]

[0120] Among them, F1, F2, F3, F4, and F5 represent the corresponding dimensional development indexes under the economic dimension indicators, social dimension indicators, resource dimension indicators, transportation dimension indicators, and organizational management dimension indicators, respectively.

[0121] Furthermore, the coupling coordination index D can be expressed as:

[0122]

[0123] Among them, α k It is expressed as the weight corresponding to each dimension indicator, which can be expressed by the target weight.

[0124] In an optional embodiment of the present invention, the above step 14 may include:

[0125] Step 141: When the comprehensive development index is greater than or equal to the first preset threshold, and the coupling coordination index is greater than or equal to the second preset threshold, the current village or town in the target area is determined to be a comprehensive development type;

[0126] Step 142: When the comprehensive development index is greater than or equal to the first preset threshold and the coupling coordination index is less than the second preset threshold, the current village or town in the target area is determined to be a characteristic advantage type;

[0127] Step 143: When the comprehensive development index is greater than or equal to the third preset threshold and the comprehensive development index is less than the first preset threshold, the current village or town in the target area is determined to be a potential to be tapped type;

[0128] Step 144: When the comprehensive development index is greater than or equal to the fourth preset threshold, the comprehensive development index is less than the third preset threshold, and the coupling coordination index is greater than or equal to the second preset threshold, the current village or town in the target area is determined to be a slow-developing type.

[0129] Step 145: When the comprehensive development index is greater than or equal to the fourth preset threshold, the comprehensive development index is less than the third preset threshold, and the coupling coordination index is less than the second preset threshold, the current village or town in the target area is determined to be a transformation development type;

[0130] Step 146: When the comprehensive development index is less than the fourth preset threshold, the current village or town in the target area is determined to be a backward development type.

[0131] To ensure accurate identification of village and town development models, this embodiment generates a discrimination system based on the dual dimensions of the comprehensive development index and the coupling coordination index. Based on this two-dimensional indicator system, threshold intervals are set, and the classification criteria and discrimination thresholds for the six village and town development models are defined, clarifying the typical characteristics and differentiated performance of villages and towns with each development model. Here, the first, second, third, and fourth preset thresholds can be set to 0.8, 0.5, 0.7, and 0.6, respectively. The first preset threshold > the third preset threshold > the fourth preset threshold > the second preset threshold.

[0132] After determining the comprehensive development index and coupling coordination index, this embodiment further characterizes the structural division and typical characteristics of village and town development models. Based on the two dimensions of the comprehensive development index and coupling coordination index, villages and towns can be divided into six typical development models, and the comprehensive characteristics of each development model are further characterized in terms of development foundation, structural coordination, and typical characteristics. Here, the comprehensive characteristics corresponding to each development model are shown in Table 2 below:

[0133] Table 2 Classification and comprehensive characteristics of village and town development models

[0134]

[0135] Here, the discrimination system fully considers the two core dimensions of the "strength" of village and town development and the "coordination" of internal structure. Through a two-dimensional cross-cutting approach, it clearly divides the development status of villages and towns and summarizes them into six typical models. In the discrimination system, a heuristic algorithm can be used to automatically identify and judge village and town development models. The specific process of implementing the heuristic algorithm is as follows:

[0136] enter:

[0137] Comprehensive development index F, ranging from [0, 1];

[0138] Coupling coordination index D, ranging from [0, 1];

[0139] Output:

[0140] Village and town development model;

[0141] The identification steps are as follows:

[0142] Step 1: If F≥0.8, proceed to the next step:

[0143] If D ≥ 0.5, the village or town is judged as “comprehensive development type”;

[0144] Otherwise (i.e. D < 0.5), the village or town will be judged as “characteristic advantage type”.

[0145] Step 2: If 0.8>F≥0.7, the village or town is judged as "potential to be tapped".

[0146] Step 3: If 0.7>F≥0.6, proceed to coordination judgment:

[0147] If D ≥ 0.5, it is judged as “slow development type”;

[0148] Otherwise (i.e. D<0.5), it is judged as “transitional development type”.

[0149] Step 4: If F < 0.6, then regardless of the value of D, the village or town will be judged as "underdeveloped".

[0150] Preferably, based on the above-mentioned heuristic algorithm, the BP neural network algorithm can be combined to construct a heuristic neural network algorithm for village and town development model discrimination. The heuristic neural network algorithm performs model training on the village and town development model data set after the heuristic algorithm, thereby obtaining a village and town development model classification and discrimination model with good predictive performance. Furthermore, the subsequently collected village and town POI data is input into the village and town development model classification and discrimination model, and intelligent judgment is made through continuous iterative learning to improve the efficiency and accuracy of village and town development model discrimination.

[0151] The above-mentioned embodiment of the present invention provides a method for determining a village and town development model based on POI data. Initial POI index data within a target area is acquired in real time, and target POI index data and evaluation dimension indicators corresponding to each village and town in the target area are determined based on the attribute information of the initial POI index data. Furthermore, a comprehensive development index and a coupling coordination index corresponding to each village and town in the target area under the evaluation dimension indicators are determined based on the target POI index data. Furthermore, a target development model corresponding to each village and town in the target area is determined based on the comprehensive development index and the coupling coordination index.

[0152] In this application, based on the characteristics of "small scale, multiple dimensions, and complex structure" of village and town POI indicator data, the entropy weighting method, grey correlation analysis, and coupling coordination model are integrated to analyze and process the POI indicator data, effectively overcoming the defects of existing evaluation methods such as reliance on a single model, strong subjective weighting, and narrow scope of application. Specifically, the entropy weighting method is used to extract objective weights from the information differences of the POI indicator data itself, avoiding the deviation caused by human settings; grey correlation analysis can extract the main influencing relationships between POI indicator data when POI indicator data is incomplete and samples are insufficient, and is particularly suitable for data-sparse areas such as villages and towns; the coupling coordination model evaluates the interaction mechanism and coordination level between economic dimension indicators, social dimension indicators, resource dimension indicators, transportation dimension indicators, organizational management dimension indicators, and other dimensional indicators from the system structure level, thereby revealing structural bottlenecks or potential imbalance points, and then achieving scientific measurement and structural coordination evaluation of multi-dimensional indicators such as economic dimension indicators, social dimension indicators, resource dimension indicators, transportation dimension indicators, and organizational management dimension indicators in villages and towns, laying a quantitative basis for subsequent development model identification and ensuring the accuracy and rationality of development model identification;

[0153] Furthermore, in order to further ensure the accuracy of village and town development model identification, the embodiment of the present invention constructs a village and town development model identification system based on the comprehensive development index (F) and the coupling coordination index (D); the identification system divides village and town development models into six typical models, including comprehensive development type, characteristic advantage type, potential to be tapped type, transformation development type, slow development type and backward development type, which fully reflects the two-dimensional characterization of development intensity and structural synergy; compared with existing evaluation technologies that usually only output a "strong-medium-weak" grade distribution, the present invention can more finely identify the different structural characteristics between villages and towns, and effectively serve classified policy implementation, resource guidance and regional differentiated governance.

[0154] like Figure 2 As shown, an embodiment of the present invention further provides a device 20 for determining a village and town development model based on POI data, comprising:

[0155] An acquisition module 21 is configured to acquire initial POI indicator data in a target area in real time, wherein the target area includes a plurality of towns and villages, and each town and village corresponds to a plurality of different types of initial POI indicator data;

[0156] Processing module 22 is used to determine the target POI index data and evaluation dimension indicators corresponding to each village and town in the target area based on the attribute information of the initial POI index data; determine the comprehensive development index and coupling coordination index of each village and town in the target area under the evaluation dimension indicators based on the target POI index data; and determine the target development model corresponding to each village and town in the target area based on the comprehensive development index and the coupling coordination index.

[0157] It should be noted that this device is a device corresponding to the above-mentioned method for determining the village and town development model based on POI data. All implementation methods in the above-mentioned method embodiment are applicable to this embodiment and can achieve the same technical effect.

[0158] like Figure 3 As shown, an embodiment of the present invention further provides an electronic device 30, comprising: a memory 31 for storing one or more computer programs; and one or more processors 32 for executing the one or more computer programs. When the computer programs are executed by the processors, the method for determining a village and town development model based on POI data as described in the above-mentioned method embodiment is implemented. All implementations in the above-mentioned method embodiment are applicable to this embodiment and can achieve the same technical effects. The electronic device 30 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown in the present invention, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0159] like Figure 4 As shown, the electronic device 30 is a computing device or a computer system, which may include a CPU 301 (computing unit) that can perform various appropriate actions and processes according to a computer program stored in a ROM 302 (read-only memory) or a computer program loaded from a storage unit 308 into a random access RAM 303 (memory). Various programs and data required for the operation of the device 30 may also be stored in the RAM 303. The CPU 301, ROM 302, and RAM 303 are connected to each other via a bus 304. An I / O interface 305 (input / output interface) is also connected to the bus 304.

[0160] Multiple components in the electronic device 30 are connected to the I / O interface 305, including an input unit 306, such as a keyboard, a mouse, etc.; an output unit 307, such as various types of displays, speakers, etc.; a storage unit 308, such as a magnetic disk, an optical disk, etc.; and a communication unit 309, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 309 allows the device 30 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0161] The CPU 301 may be a variety of general and / or specialized processing components with processing and computing capabilities. Some examples of the CPU 301 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units for running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The CPU 301 performs the various methods and processes described above. For example, in some embodiments, the method for determining a village and town development model based on POI data may be implemented as a computer software program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 308. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 30 via the ROM 302 and / or the communication unit 309. When the computer program is loaded into the RAM 303 and executed by the CPU 301, one or more steps of the method for determining a village and town development model based on POI data described in the above method embodiment may be performed. Alternatively, in other embodiments, the CPU 301 may be configured in any other appropriate manner (for example, by means of firmware) to execute the method for determining a village and town development pattern based on POI data.

[0162] Embodiments of the present invention further provide a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to execute the method for determining a village and town development model based on POI data, as described in the above-described method embodiment. All implementations in the above-described method embodiment are applicable to this embodiment and can achieve the same technical effects.

[0163] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0164] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0165] In the embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interface, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0166] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0167] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0168] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the existing technology, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the method of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, ROM, RAM, disk or optical disk, etc. Various media that can store program code.

[0169] In addition, it should be noted that, in the apparatus and method of the present invention, it is obvious that each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent schemes of the present invention. Moreover, the steps of performing the above-mentioned series of processing can naturally be performed in chronological order according to the order of description, but it is not necessary to perform them in chronological order, and some steps can be performed in parallel or independently of each other. For those of ordinary skill in the art, it will be understood that all or any steps or components of the method and apparatus of the present invention can be implemented in any computing device (including processors, storage media, etc.) or a network of computing devices in hardware, firmware, software or a combination thereof, which can be achieved by those of ordinary skill in the art using their basic programming skills after reading the description of the present invention.

[0170] Therefore, the purpose of the present invention can also be achieved by running a program or a group of programs on any computing device. The computing device can be a well-known general-purpose device. Therefore, the purpose of the present invention can also be achieved simply by providing a program product containing program code for implementing the method or device. That is to say, such a program product also constitutes the present invention, and the storage medium storing such a program product also constitutes the present invention. Obviously, the storage medium can be any well-known storage medium or any storage medium developed in the future. It should also be pointed out that in the device and method of the present invention, it is obvious that each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent schemes of the present invention. In addition, the steps of performing the above-mentioned series of processing can naturally be performed in chronological order according to the order of description, but do not necessarily need to be performed in chronological order. Certain steps can be performed in parallel or independently of each other.

[0171] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A method for determining village and town development models based on POI data, characterized in that: include: Acquire initial POI indicator data in a target area in real time, where the target area includes multiple villages and towns, and each village and town corresponds to multiple different types of initial POI indicator data; Determining target POI index data and evaluation dimension indicators corresponding to each village and town in the target area based on the attribute information of the initial POI index data; Determine the comprehensive development index and coupling coordination index of each village and town in the target area under the evaluation dimension indicators based on the target POI indicator data; The target development model corresponding to each village and town in the target area is determined according to the comprehensive development index and the coupling coordination index.

2. The method for determining a village and town development model based on POI data according to claim 1, characterized in that: Determining target POI index data and evaluation dimension indicators corresponding to each village or town in the target area based on the attribute information of the initial POI index data includes: Matching the initial POI indicator data to each village and town in the target area according to the address information and spatial coordinate information of the initial POI indicator data to determine target POI indicator data corresponding to each village and town; Based on the name information and data type information of the target POI indicator data corresponding to each village and town, the evaluation dimension indicators of each village and town are determined, and the evaluation dimension indicators include different types of target POI indicator data.

3. The method for determining a village and town development model based on POI data according to claim 1, characterized in that: Based on the target POI index data, the comprehensive development index and coupling coordination index of each village and town in the target area under the evaluation dimension indicators are determined, including: Constructing a grey correlation system for the villages and towns in the target area, where all target POI indicator data for each village and town corresponds to a grey correlation system; Determine the dimensional development index of each village and town in the target area under the corresponding evaluation dimension indicator based on the grey correlation system and the target POI index data; According to the dimensional development index under the corresponding evaluation dimension indicator and the preset coupling coordination model, the comprehensive development index and coupling coordination index of each village and town in the target area are determined.

4. The method for determining a village and town development model based on POI data according to claim 3, characterized in that: Based on the grey correlation system and the target POI index data, the dimensional development index of each village and town in the target area under the corresponding evaluation dimension index is determined, including: Based on a preset weight algorithm, determine the target weight of each type of target POI indicator data in the target POI indicator data of each village and town; Based on the target POI index data of each village and town, determine the grey correlation coefficient of the grey correlation system corresponding to each village and town; According to the target weight and grey correlation coefficient under the corresponding evaluation dimension, the dimension development index of each village and town under the corresponding evaluation dimension indicator is determined.

5. The method for determining a village and town development model based on POI data according to claim 4, characterized in that: Based on the preset weight algorithm, the target weight of each type of target POI indicator data in the target POI indicator data of each village and town under the corresponding evaluation dimension indicator is determined, including: Determine the proportion of each type of target POI indicator data in all target POI indicator data of all villages and towns; The target weight of each type of target POI indicator data is determined according to the proportion value and the preset weight algorithm.

6. The method for determining a village and town development model based on POI data according to claim 4, characterized in that: Based on the target POI index data of each village and town, the grey correlation coefficient of the grey correlation system corresponding to each village and town is determined, including: Determining a reference sequence corresponding to the target POI indicator data within the target area based on the target POI indicator data of each village and town within the target area; Based on the comparison sequence corresponding to the target POI index data of each village and town and the reference sequence, the grey correlation coefficient of the grey correlation degree system corresponding to each village and town is determined.

7. The method for determining a village and town development model based on POI data according to claim 1, characterized in that: Determine the target development model corresponding to each village and town in the target area based on the comprehensive development index and the coupling coordination index, including: When the comprehensive development index is greater than or equal to a first preset threshold, and the coupling coordination index is greater than or equal to a second preset threshold, determining that the current village or town in the target area is a comprehensive development type; When the comprehensive development index is greater than or equal to a first preset threshold and the coupling coordination index is less than a second preset threshold, the current village or town in the target area is determined to be a characteristic advantage type; When the comprehensive development index is greater than or equal to a third preset threshold and the comprehensive development index is less than the first preset threshold, determining that the current village or town in the target area is a potential to be tapped type; When the comprehensive development index is greater than or equal to a fourth preset threshold, the comprehensive development index is less than the third preset threshold, and the coupling coordination index is greater than or equal to a second preset threshold, it is determined that the current village or town in the target area is a slow-developing type; When the comprehensive development index is greater than or equal to a fourth preset threshold, the comprehensive development index is less than the third preset threshold, and the coupling coordination index is less than the second preset threshold, the current village or town in the target area is determined to be a transformation development type; When the comprehensive development index is less than a fourth preset threshold, the current village or town in the target area is determined to be a backward development type, and the first preset threshold>the third preset threshold>the fourth preset threshold>the second preset threshold.

8. A device for determining a village and town development model based on POI data, characterized in that: include: An acquisition module is used to acquire initial POI indicator data in a target area in real time, where the target area includes multiple villages and towns, and each village and town corresponds to multiple different types of initial POI indicator data; A processing module is used to determine the target POI index data and evaluation dimension indicators corresponding to each village and town in the target area based on the attribute information of the initial POI index data; determine the comprehensive development index and coupling coordination index of each village and town in the target area under the evaluation dimension indicators based on the target POI index data; and determine the target development model corresponding to each village and town in the target area based on the comprehensive development index and the coupling coordination index.

9. A computing device, characterized in that include: a memory for storing one or more programs; One or more processors, configured to execute the one or more programs to implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a program, which, when executed by a processor, implements the method according to any one of claims 1 to 7.

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