Small town facility construction level dynamic evaluation method and system
By preprocessing and quantifying the weights of evaluation factors for infrastructure construction in small towns, and combining standardized evaluation curves and grey relational analysis, the dynamic evaluation problem of infrastructure construction in small towns was solved, thereby improving the accuracy and efficiency of resource allocation.
Patent Information
- Application Number
- CN202511866862.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-11
- Publication Date
- 2026-02-10
AI Technical Summary
Existing technologies cannot achieve dynamic assessment of infrastructure construction in small towns on a large scale. The assessment results lack objectivity and efficiency, and cannot match the development level of small towns, resulting in inaccurate resource allocation and problems of premature or delayed construction.
By preprocessing the evaluation factors, they are divided into factors related to the development stage of small towns and the level of infrastructure construction. Weights are calculated, indices are quantified, standardized evaluation curves are fitted, and combined with a grey relational analysis model, the level of infrastructure construction is dynamically monitored, providing feedback to guide resource allocation.
It enables dynamic evaluation of infrastructure construction in small towns across a wide range, improves resource allocation efficiency, ensures that infrastructure construction matches the level of development, and provides a basis for precise resource allocation.
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Figure CN121503919A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the technical field of small town construction planning, and more specifically, to a method and system for dynamic evaluation of the level of infrastructure construction in small towns. Background Technology
[0002] The construction of infrastructure in small towns involves a wide range of aspects, and the assessment of the construction level is a multi-faceted and integrated task that requires the support of diverse and heterogeneous data involved in the construction process. In most cases, data gaps and differences in statistical methods can lead to significant discrepancies in the assessment results. Therefore, a standardized approach needs to be established for the use of data and for data-based predictions.
[0003] Furthermore, current assessments of infrastructure development in small towns only support annual inspections of individual towns, failing to provide dynamic evaluations of infrastructure development across a large scale. Such large-scale assessments would require significantly more human and material resources. Additionally, the level of infrastructure development in small towns must be commensurate with their development level. Current assessment methods are not linked to development levels, failing to reflect the actual needs of towns at different development stages. This leads to issues of premature or delayed development, failing to scientifically reflect the objective needs of a town's development stage, and lacking a construction-oriented feedback mechanism to guide improvements in infrastructure development. Consequently, these methods cannot provide a basis for the precise allocation of urban construction resources, resulting in low resource allocation efficiency. Summary of the Invention
[0004] To address the current problems of lack of objectivity, limited scope, and low efficiency in assessing the level of infrastructure construction in small towns, this invention proposes a dynamic assessment method and system for the level of infrastructure construction in small towns. This method scientifically processes diverse and heterogeneous data involved in the construction of infrastructure in small towns, enabling dynamic assessment of infrastructure construction in large-scale towns. This provides a basis for the precise allocation of urban construction resources and improves the efficiency of urban construction resource allocation.
[0005] To achieve the above-mentioned technical effects, the technical solution of the present invention is as follows: Firstly, this application proposes a dynamic evaluation method for the infrastructure development level of small towns, including the following steps: The selected evaluation factors are preprocessed to obtain preprocessed evaluation factors. The preprocessed evaluation factors are then divided into evaluation factors for the development stage of small towns and evaluation factors for the level of infrastructure construction in small towns. Typical small towns were selected as research objects, and construction data of typical small towns corresponding to the evaluation factors were collected. The weights of the evaluation factors of the development stage of small towns and the evaluation factors of the infrastructure construction level of small towns were calculated respectively. Based on the weights of the evaluation factors for the development stage of small towns, the evaluation factors for the development stage of small towns are standardized and the socio-economic development index is quantified; based on the weights of the evaluation factors for the level of infrastructure construction in small towns, the evaluation factors for the level of infrastructure construction in small towns are standardized and the infrastructure construction level index is quantified. Small towns were selected as research samples within a certain area. The evaluation factors of the development stage of small towns in the research samples were correlated with the evaluation factors of the infrastructure level of small towns. Based on the correspondence between the socio-economic development index and the infrastructure construction level index, a standardized evaluation curve was fitted. Using a standardized assessment curve as a benchmark, the deviation index of actual infrastructure construction in a single small town is calculated to assess the level of infrastructure construction in that small town. Select sample towns, fit a standardized reference curve for town construction level, and use the year as the dynamic calculation unit to dynamically monitor the level of infrastructure construction in small towns; Based on a pre-established grey relational analysis model, the correlation coefficient of infrastructure construction level of small town infrastructure construction level assessment factors is determined. Based on the correlation coefficient, the assessment of development driving force is reconstructed, and resource allocation guidance feedback is provided for town construction.
[0006] Preferably, the process of preprocessing the selected evaluation factors to obtain the preprocessed evaluation factors is as follows: Based on the standard requirements for small town infrastructure construction assessment and the difficulty in obtaining indicator data, small town development index assessment indicators are obtained, including primary indicators, secondary indicators and tertiary indicators; Based on the primary, secondary, and tertiary indicators, an expert consultation questionnaire survey was conducted to screen preliminary evaluation factors from the primary, secondary, and tertiary indicators. Principal component analysis was used to further screen the preliminary evaluation factors to obtain effective evaluation factors. Redundant evaluation information is removed from the effective evaluation factors to obtain preprocessed evaluation factors.
[0007] Preferably, the small town development stage assessment factor is used to assess the socioeconomic development index (TDI), denoted as X1, X2, ..., X... i Xn, where n represents the number of assessment factors for the development stage of small towns; the assessment factors for the level of infrastructure construction in small towns are used to assess the TCI (Training Council Index) of infrastructure construction in small towns, denoted as Y1, Y2, Y3, ..., Yn. j Y m , m represents the number of assessment factors for the level of infrastructure construction in small towns.
[0008] Preferably, after collecting typical small town construction data corresponding to the evaluation factors, the collected typical small town construction data is standardized using the range method; the processed typical small town construction data is linearly weighted using the entropy weight method and the analytic hierarchy process to obtain the weights of the infrastructure construction level evaluation factors and the socio-economic development index evaluation factors, respectively. The evaluation factors for the development stage of small towns are standardized, and the expression for quantifying the socio-economic development index is as follows: TDI (X) =
[0009] The evaluation factors for the level of infrastructure construction in small towns are standardized, and the expression for quantifying the infrastructure construction level index is as follows: TCI (Y)
[0010] Among them, TDI （X） This represents the socio-economic development index of small towns. This represents the weight of the evaluation factor for the i-th stage of small town development, i=1,2,...,n; TCI (Y) This represents an index indicating the level of infrastructure development in small towns. Let represent the weight of the evaluation factor for the infrastructure construction level of the j-th small town, where j = 1, 2, ..., m.
[0011] Preferably, the research sample consists of small towns with different socio-economic development indices selected within a national region or province, and the socio-economic development indices of these small towns conform to a normal distribution. Based on the correlation between the socio-economic development index and the infrastructure construction level index, using the socio-economic development index of small towns in the research sample as the horizontal axis and the infrastructure construction level index of small towns in the research sample as the vertical axis, a standardized evaluation curve is fitted based on the research sample to obtain a standardized evaluation curve. This standardized evaluation curve represents the average level of infrastructure construction in small towns under different socio-economic development levels during a certain period. The expression for the standardized evaluation curve is: Y k =aX k 2 +bX k +c Among them, X k Y represents the socioeconomic development index of the kth town. k The dependent variable is the average level that the infrastructure construction of the kth small town should reach in the fitted curve, where k is a positive integer and n is the number of factors, k=1,2,…,n.
[0012] Preferably, the process of calculating the deviation index of actual infrastructure construction in a single small town to assess the infrastructure construction level of a single small town, based on a standardized assessment curve, includes: Based on the expression for the quantitative infrastructure development level index, calculate the socio-economic development index (TCI) of the w-th small town in a certain period. (Y)w ; Based on the expression of the standardized evaluation curve, calculate the average level Y that the infrastructure construction of the w-th small town should reach in a certain period. w ; Based on the socio-economic development index (TCI) of the wth small town (Y)w And the average level Y that the infrastructure construction of the wth small town should reach. w The deviation index of actual infrastructure construction in the w-th small town is calculated as follows: |Y w =TCI (Y)w –Y w If the deviation from the index |Y w If the index is greater than 0, then the infrastructure level of the w-th town is relatively good, and the construction quality of the town is relatively high under the current socio-economic development index; if it deviates from the index... |Y w If the value is less than 0, then the infrastructure construction level of the w-th small town is relatively poor. Under the current socio-economic development index, the construction quality of the small town is poor, and resource investment should be increased. |Y w If the value is 0, then the infrastructure level of the wth town is equal to the average level.
[0013] Preferably, the process of calculating the deviation index of actual infrastructure construction in a single small town to assess the infrastructure construction level of a single small town, based on a standardized assessment curve, further includes: Select a single small town's infrastructure development level assessment factor Y j , for Y j After standardization, the Socioeconomic Development Index (TDI) is used. （X） Using Y, a single-item small town infrastructure construction level assessment factor, as the horizontal axis. j Discrete points are generated, and a fitting is performed based on these discrete points to obtain the evaluation factor Y for the level of infrastructure construction in small towns. j Based on the corresponding standardized fitting curve, the evaluation factor Y of the infrastructure construction level of the w-th small town is calculated. j Actual infrastructure construction deviation index |Y j If it deviates from the index |Y j If the index is greater than 0, the infrastructure level of the small town corresponding to the single evaluation factor of small town infrastructure construction level is relatively good; if it deviates from the index... |Y j If the value is less than 0, then the infrastructure level of the small town corresponding to the single-item small town infrastructure construction level assessment factor is relatively poor. Under the current socio-economic development index, the single-item small town infrastructure construction level assessment factor Y should be increased. j The corresponding investment in small town resource development, if |Y j =0, then the evaluation factor Y of the level of infrastructure construction in a single small town j The corresponding level of infrastructure in small towns is equal to the average level.
[0014] Preferably, the process of dynamically monitoring the level of infrastructure construction in small towns, using years as the dynamic calculation unit, includes: Selecting different socioeconomic development indices (TDI) (X) The sample towns are to be selected, and the sample towns must meet the normal distribution. A standardized reference curve for the level of urban construction is fitted. The small town r to be monitored is identified, and the socio-economic development index (TDI) of small town r is calculated annually using the year as the dynamic calculation unit. (X)r and infrastructure development level TCI (Y)r ; The annual socioeconomic development index (TDI) of small towns (X)r Infrastructure Development Level (TCI) (Y)r By comparing with the standardized reference curve for urban development levels, the deviation index for each year is determined. |Y r ; Based on the deviation index of each year |Y r To dynamically monitor the level of infrastructure construction in small towns; The process of dynamically monitoring the level of infrastructure construction in small towns, using years as the dynamic calculation unit, also includes: Evaluation factor Y for the level of infrastructure construction in selected small towns q , for Y q After standardization, the Socioeconomic Development Index (TDI) is used. （X） Using Y, a single-item small town infrastructure construction level assessment factor, as the horizontal axis. q Discrete points are generated, and a fitting is performed based on these discrete points to obtain the evaluation factor Y for the level of infrastructure construction in small towns. q Based on the corresponding standardized fitting curve, the individual small town infrastructure construction level assessment factor Y for small town r is calculated annually. qActual infrastructure construction deviation index |Y q Based on the annual deviation index |Y q Dynamic monitoring of the level of individual infrastructure construction in small towns.
[0015] Preferably, using the small town infrastructure construction level index as a reference sequence and the standardized data obtained from the standardized processing of the small town infrastructure construction level assessment factors as a comparison sequence, the infrastructure construction level correlation coefficient of the small town infrastructure construction level assessment factors is determined based on a pre-established grey relational analysis model, and the process satisfies:
[0016]
[0017]
[0018] in, This represents the absolute difference of the assessment factors for the infrastructure development level of the i-th small town. This represents the correlation coefficient of infrastructure construction level for the i-th small town infrastructure construction level assessment factor. This represents the correlation degree of the infrastructure construction level assessment factor of the i-th small town. , These are the assessment factors for the infrastructure construction level of the i-th small town. The absolute value of the difference between the maximum and minimum values of the Small Town Infrastructure Development Index (TCI). The resolution coefficient, The larger the correlation coefficient of the infrastructure construction level assessment factor of small towns, the stronger the driving force of the infrastructure construction level assessment factor on the infrastructure construction level of small towns.
[0019] Secondly, this application also proposes a system for implementing the aforementioned dynamic evaluation method for the level of infrastructure construction in small towns, comprising: The evaluation factor screening and processing module is used to preprocess the selected evaluation factors to obtain preprocessed evaluation factors, and divide the preprocessed evaluation factors into evaluation factors for the development stage of small towns and evaluation factors for the level of infrastructure construction in small towns. The factor weight calculation module selects typical small towns as research objects, collects construction data of typical small towns corresponding to the evaluation factors, and calculates the weights of the evaluation factors of the development stage of small towns and the evaluation factors of the infrastructure construction level of small towns respectively. The index quantification module standardizes the evaluation factors of small town development stage based on their weights, and quantifies the socio-economic development index; it also standardizes the evaluation factors of small town infrastructure construction level based on their weights, and quantifies the infrastructure construction level index. The first standardized curve fitting module is used to select small towns as research samples within a certain area, associate the small town development stage assessment factor with the small town infrastructure level assessment factor, and fit a standardized assessment curve based on the correspondence between the socio-economic development index and the infrastructure construction level index. The first assessment module uses a standardized assessment curve as a benchmark to calculate the deviation index of actual infrastructure construction in a single small town in order to assess the level of infrastructure construction in a single small town. The second standardized curve fitting module is used to select sample towns and fit a standardized reference curve for the town's construction level. The curve is dynamically calculated in years to monitor the level of infrastructure construction in small towns. The second evaluation module, based on a pre-established grey relational analysis model, determines the correlation coefficient of infrastructure construction level of small town infrastructure construction level evaluation factors, and based on the correlation coefficient, conducts a reconstructed development driving force evaluation to provide resource allocation guidance feedback for town construction.
[0020] Compared with the prior art, the beneficial effects of the technical solution of the present invention are: This invention proposes a dynamic evaluation method and system for the infrastructure construction level of small towns. The method preprocesses selected evaluation factors to extract more effective ones, dividing these factors into evaluation factors for the town's development stage and infrastructure construction level. The weights of these factors are calculated separately. Then, the socio-economic development index and the infrastructure construction level index are quantified. Based on these indices, a standardized evaluation curve is fitted, establishing a correlation model for the infrastructure construction level of small towns under different socio-economic development conditions. This allows for an objective comparison of the reasonable infrastructure construction levels that towns at different socio-economic development levels should achieve, effectively evaluating the overall infrastructure construction level. It can also evaluate individual construction level factors. By selecting sample towns and fitting a standardized reference curve for town construction level, with years as the dynamic calculation unit, the method intuitively achieves a dynamic evaluation of infrastructure construction in large-scale towns under constantly changing socio-economic conditions. Based on a pre-established grey relational analysis model, the correlation coefficient of the infrastructure construction level evaluation factors is determined, providing resource allocation guidance for town construction and providing a basis for precise allocation of town construction resources, thereby improving the efficiency of town construction resource allocation. Attached Figure Description
[0021] Figure 1 A flowchart illustrating the dynamic evaluation method for the infrastructure construction level of small towns proposed in this embodiment of the invention; Figure 2 This diagram illustrates the quantification of socio-economic development index based on three-level indicators as proposed in this embodiment of the invention. Figure 3 This is a schematic diagram illustrating the quantification of infrastructure construction level index based on three-level indicators proposed in this invention. Figure 4 This invention presents a schematic diagram of a standardized evaluation curve fitting, illustrating the correspondence between the socio-economic development index and infrastructure construction level index of a small town in a certain province, as proposed in this embodiment. Figure 5 This diagram illustrates the analysis of the standardized evaluation curve proposed in this embodiment of the invention. Figure 6 This is a schematic diagram illustrating the deviation index of actual infrastructure construction in a single small town, based on a standardized evaluation curve, as proposed in this embodiment of the invention. Figure 7 This is a schematic diagram illustrating the assessment of the infrastructure level of small towns corresponding to the single assessment factors for the infrastructure construction level of small towns proposed in this embodiment of the invention. Figure 8 This is a schematic diagram illustrating the dynamic assessment of the infrastructure construction level of small towns under dynamic socio-economic development conditions, as proposed in this embodiment of the invention. Figure 9 This is a structural diagram of the dynamic evaluation system for the level of infrastructure construction in small towns proposed in this embodiment of the invention. Detailed Implementation
[0022] The accompanying drawings are for illustrative purposes only and should not be construed as limiting the scope of this patent. To better illustrate this embodiment, some parts of the accompanying drawings may be omitted, enlarged, or reduced, and do not represent the actual dimensions; It is understandable to those skilled in the art that some well-known details may be omitted from the accompanying drawings.
[0023] The technical solution of the present invention will be further described below with reference to the accompanying drawings and embodiments.
[0024] The positional relationships depicted in the accompanying drawings are for illustrative purposes only and should not be construed as limiting this patent. Example 1 This embodiment proposes a dynamic evaluation method for the infrastructure construction level of small towns, and the flowchart of the method is as follows: Figure 1 As shown, it includes the following steps: S1: Preprocess the selected evaluation factors to obtain preprocessed evaluation factors, and divide the preprocessed evaluation factors into evaluation factors for the development stage of small towns and evaluation factors for the level of infrastructure construction in small towns. S2: Select typical small towns as research objects, collect construction data of typical small towns corresponding to the evaluation factors, and calculate the weights of the evaluation factors of the development stage of small towns and the evaluation factors of the infrastructure construction level of small towns respectively. S3: Based on the weights of the evaluation factors for the development stage of small towns, the evaluation factors for the development stage of small towns are standardized to quantify the socio-economic development index; based on the weights of the evaluation factors for the level of infrastructure construction in small towns, the evaluation factors for the level of infrastructure construction in small towns are standardized to quantify the level of infrastructure construction index. S4: Select small towns as research samples within a certain area, associate the evaluation factors of the development stage of small towns with the evaluation factors of the infrastructure level of small towns, and fit a standardized evaluation curve based on the correspondence between the socio-economic development index and the infrastructure construction level index. S5: Using a standardized assessment curve as a benchmark, calculate the deviation index of actual infrastructure construction in a single small town to assess the level of infrastructure construction in that small town. S6: Select sample towns, fit a standardized reference curve for town construction level, and use the year as the dynamic calculation unit to dynamically monitor the level of infrastructure construction in small towns; S7: Based on the pre-established grey relational analysis model, determine the correlation coefficient of infrastructure construction level of small town infrastructure construction level assessment factors, and based on the correlation coefficient, conduct a reconstructed development driving force assessment to provide resource allocation guidance feedback for town construction.
[0025] This embodiment proposes a dynamic evaluation method and system for the infrastructure construction level of small towns. The method preprocesses selected evaluation factors to extract more effective ones, dividing them into evaluation factors for the development stage of small towns and evaluation factors for the infrastructure construction level. The weights of the development stage evaluation factors and the infrastructure construction level evaluation factors are calculated separately. Then, the socio-economic development index and the infrastructure construction level index are quantified. Based on these indices, a standardized evaluation curve is fitted, establishing a correlation model for the infrastructure construction level of small towns under different socio-economic development conditions. This allows for an objective comparison of the reasonable infrastructure construction levels that towns at different socio-economic development levels should achieve, effectively evaluating the overall infrastructure construction level. It can also evaluate individual construction level factors. By selecting sample towns and fitting a standardized reference curve for town construction level, using years as the dynamic calculation unit, the method intuitively achieves a dynamic evaluation of infrastructure construction in large-scale towns under constantly changing socio-economic conditions. Based on a pre-established grey relational analysis model, the correlation coefficient of the infrastructure construction level evaluation factors for small towns is determined, providing resource allocation guidance feedback for town construction and providing a basis for the precise allocation of town construction resources, thereby improving the efficiency of town construction resource allocation.
[0026] Example 2 In this embodiment, when selecting evaluation factors, representative and operable indicators are chosen based on current needs, existing standards and requirements for small town construction evaluation, and research conclusions. The difficulty of data acquisition is also considered. In this embodiment, a typical town from the "High-Quality Development Project of 100 Counties, 1000 Towns and 10,000 Villages" in Province A can be selected as the research object to collect evaluation factors.
[0027] The process of preprocessing the selected evaluation factors to obtain the preprocessed evaluation factors is as follows: Based on the standard requirements for small town infrastructure construction assessment and the difficulty in obtaining indicator data, small town development index assessment indicators are obtained. The assessment indicators include primary indicators, secondary indicators, and tertiary indicators. The specific content of the assessment system corresponding to the primary indicators, secondary indicators, and tertiary indicators can be found in Table 1.
[0028]
[0029] Based on the aforementioned primary, secondary, and tertiary indicators, an expert consultation questionnaire was conducted to screen preliminary evaluation factors. In this embodiment, the expert consultation questionnaire included the importance of the evaluation indicators for the high-quality development index of small towns in Province A, the operability of the evaluation indicators for the small town development index, and the basis for judgment. SPSS software was used for statistical analysis. Evaluation factors with less influence in the preliminary screening were deleted.
[0030] Principal component analysis (PCA) was used to further screen the preliminary evaluation factors to obtain effective evaluation factors. In this embodiment, PCA was performed on the preliminary evaluation factors selected by experts. PCA was conducted on the secondary indicators of the evaluation system that contained three or more tertiary indicators, including population agglomeration capacity, industrial development level, urban construction scale, public service facility configuration, infrastructure construction level, and landscape construction quality. For example, population agglomeration capacity is shown in Table 2.
[0031] Table 2
[0032] Redundancy in evaluation information is removed from the effective evaluation factors to obtain preprocessed evaluation factors. In this embodiment, the Pearson coefficient is used to verify the interrelationships of similar element indicators in the evaluation system, including population agglomeration capacity, industrial development level, fiscal autonomy, urban construction scale, public service facility configuration (educational facilities, medical and elderly care facilities, cultural and sports facilities, and commercial facilities), infrastructure construction level, and landscape construction quality. The final preprocessed evaluation factors are shown in Table 3.
[0033] Table 3
[0034] In this embodiment, the small town development stage assessment factor is used to assess the socioeconomic development index (TDI), denoted as X1, X2, ..., X... i Xn, where n represents the number of evaluation factors for the development stage of small towns. After screening, the evaluation factors for the socio-economic development index include: urbanization rate of permanent residents (X1), net population inflow rate (X2), per capita GDP (X3), year-on-year growth rate of GDP (X4), and the proportion of government fund budget fiscal appropriations to total revenue (X5).
[0035] The assessment factors for the level of infrastructure construction in small towns are used to evaluate the TCI (Traffic Control Index) of infrastructure construction in small towns, denoted as Y1, Y2, Y3, ..., Yj, Ym, where m represents the number of assessment factors. After screening, the assessment factors for the level of infrastructure construction in small towns include: number of hospital beds per thousand people (Y1), coverage rate of cultural and sports facilities within a 15-minute walk (Y2), proportion of public compulsory education schools admitting students from nearby schools (Y3), road network density in built-up areas (Y4), drainage pipeline density in built-up areas (Y5), average annual COD influent concentration of urban sewage treatment plants (Y6), street space quality evaluation (Y7), and green coverage rate in built-up areas (Y8).
[0036] In this embodiment, when collecting data on the construction of typical small towns corresponding to the evaluation factors, data is collected according to the evaluation factors, including publicly available data from statistical and literature sources, as well as data reported by the government and statistical authorities. Textual statistical data includes: relevant population, economic, and social statistical data; village and town construction statistical reports and relevant work reports from the town government; spatial data includes: national land survey data, satellite remote sensing imagery, planning atlases, and relevant online data (POI data crawled, queries from mainstream map software); and questionnaire survey data.
[0037] After collecting typical small town construction data corresponding to the evaluation factors, the range method was used to process the collected typical small town construction data. The entropy weight method and the analytic hierarchy process were used to perform linear weighting calculations on the processed typical small town construction data to obtain the weights of the infrastructure construction level evaluation factor and the socio-economic development index evaluation factor, respectively.
[0038] In practical implementation, the scenario can be a region within a certain area of a country, province, or city, not limited to a single province. Small towns in province A are selected as the research object. The specific steps are as follows: Data collection: Typical towns identified in province A's "High-Quality Development Project of 100 Counties, 1000 Towns, and 10,000 Villages" are selected as research objects, and their indicator factors are collected. 300 representative towns are selected as reference models based on different levels of socio-economic development. These towns, as typical towns in province A, can represent different levels of socio-economic development across the province and meet the requirements of a normal distribution. Data for these indicators is collected and standardized using the range method.
[0039] The data were linearly weighted using the entropy weight method and the analytic hierarchy process (AHP) to calculate the weights of the infrastructure construction level assessment factor and the socio-economic development index assessment factor, respectively. The data used were several high-quality development indicators of model towns. Taking the weight calculation of the socio-economic development index assessment factor as an example, the results are shown in Table 4, and in Table 5.
[0040] Table 4
[0041] Table 5
[0042] Based on the weights determined above, the evaluation factors for the development stage of small towns are standardized and linearly weighted. The expression for quantifying the socio-economic development index is as follows: TDI (X) =
[0043] The evaluation factors for the level of infrastructure construction in small towns are standardized and linearly weighted. The expression for quantifying the infrastructure construction level index is as follows: TCI (Y)
[0044] Among them, TDI （X） This represents the socio-economic development index of small towns. This represents the weight of the evaluation factor for the i-th stage of small town development, i=1,2,...,n; TCI (Y) This represents an index indicating the level of infrastructure development in small towns. Let represent the weight of the evaluation factor for the infrastructure construction level of the j-th small town, where j = 1, 2, ..., m.
[0045] In this embodiment, 31 representative small towns in Province A were selected for study and investigation. Based on the evaluation factors and weights, the socio-economic development index TDI(X) and the infrastructure development level index TCI(Y) of the selected sample small towns were calculated respectively. Figure 2 This diagram illustrates the quantification of socioeconomic development indices for tertiary indicators. Figure 3 This diagram illustrates the quantification of the infrastructure development level index based on three levels of indicators. Figure 2This report presents the infrastructure development level index of 31 small towns across eight assessment factors. The average values for each indicator range from 0.1299 to 0.6774, demonstrating the differences in performance across different towns across various indicators. Overall, some towns excelled in specific indicators, while others need improvement, providing a basis for future resource allocation. Yonghan Town performed exceptionally well in indicator Y1, and its medical resource allocation model can serve as a reference for other towns. Tongqiao Town performed exceptionally well in indicator Y2, with the best coverage rate of cultural and sports facilities. Y3 generally performed well, with an average of 0.66, but Lingbei Town's score was only 0.0324, far below the average, suggesting attention and improvement in the allocation of educational resources in this town. Hongqi Town performed exceptionally well in indicator Y4, while Silun Town's score was only 0.01, recommending strengthened road network construction. Longtang Town performed exceptionally well in Y5, and Lingbei Town performed exceptionally well in Y6. Pingtan Town and Chunwan Town, however, were far below the average, suggesting strengthened drainage network construction and rainwater and sewage separation to increase COD influent concentration. Shahu Town performed exceptionally well in Y7, while Baipenzhu Town achieved a Y8 score of 1.00, demonstrating significant advantages in street space quality and greening. Its landscape improvement strategies can serve as a model for other towns. Significant differences in performance across various indicators indicate that each town adopted different strategies and measures for infrastructure development. Figure 3 The study presents the socio-economic development index of 31 small towns based on five assessment factors for the development stages of small towns.
[0046] In this embodiment, the research sample consists of small towns with different socio-economic development indices selected within a national region or province. These indices conform to a normal distribution to meet the needs of subsequent analysis, represent the development level of small towns at different stages of socio-economic development, and satisfy the user's expected development goals.
[0047] In this embodiment, a coordinate system is constructed based on the correspondence between the socio-economic development index and the infrastructure construction level index. The socio-economic development index of small towns in the research sample is used as the horizontal axis, and the infrastructure construction level index of small towns in the research sample is used as the vertical axis. Based on the research sample, standardized evaluation curve fitting is performed using mathematical analysis software such as MATLAB to obtain a standardized evaluation curve. This standardized evaluation curve represents the average level of infrastructure construction in small towns under different socio-economic development levels during a certain period. The expression for the standardized evaluation curve is: Y k =aX k 2 +bX k +c Among them, X k Y represents the socioeconomic development index of the kth town. kLet be the dependent variable, representing the average level of infrastructure development that the k-th small town should achieve in the fitted curve, where k is a positive integer and n is the number of factors, k = 1, 2, ..., n. For example... Figure 4 As shown, based on the sample of 31 small towns mentioned above, the TDI and TCI of each small town were calculated, and the results were marked on the coordinate system according to the above method to generate a standardized evaluation curve. This curve can be used to examine the level and gap in infrastructure construction of small towns with different socio-economic development levels in Guangdong Province. Figure 5 This is a schematic diagram illustrating the analysis of standardized evaluation curves.
[0048] In this embodiment, the process of calculating the deviation index of actual infrastructure construction in a single small town to assess the infrastructure construction level of a single small town, based on a standardized evaluation curve, includes: Based on the expression for the quantitative infrastructure development level index, calculate the socio-economic development index (TCI) of the w-th small town in a certain period. (Y)w ; Based on the expression of the standardized evaluation curve, calculate the average level Y that the infrastructure construction of the w-th small town should reach in a certain period. w ; Based on the socio-economic development index (TCI) of the wth small town (Y)w And the average level Y that the infrastructure construction of the wth small town should reach. w The deviation index of actual infrastructure construction in the w-th small town is calculated as follows: |Y w =TCI (Y)w –Y w If the deviation from the index |Y w If the index is greater than 0, then the infrastructure level of the w-th town is relatively good, and the construction quality of the town is relatively high under the current socio-economic development index; if it deviates from the index... |Y w If the value is less than 0, then the infrastructure construction level of the w-th small town is relatively poor. Under the current socio-economic development index, the construction quality of the small town is poor, and resource investment should be increased. |Y w If the value is 0, then the infrastructure level of the w-th town is equal to the average level. For example... Figure 6 As shown, for the 31 typical small towns selected in Province A, after generating standardized evaluation curves, the relative positions of each town's points on the coordinate system and the standardized curves were examined. If a point is above the curve, it indicates a high level of infrastructure development; if below the curve, it indicates a low level of infrastructure development that needs improvement. Figure 6 In the middle, 18 small towns, including Dipai Town and Yonghan Town, are located above the curve. |Yk >0; therefore, among towns with the same level of socio-economic development, those with higher levels of infrastructure development are at a higher level. Conversely, the other 13 small towns have lower levels of infrastructure development.
[0049] In this embodiment, the process of calculating the deviation index of actual infrastructure construction in a single small town to assess the infrastructure construction level of a single small town, based on a standardized evaluation curve, further includes: Select a single small town's infrastructure development level assessment factor Y j , for Y j After standardization, the Socioeconomic Development Index (TDI) is used. （X） Using Y, a single-item small town infrastructure construction level assessment factor, as the horizontal axis. j Discrete points are generated, and a fitting is performed based on these discrete points to obtain the evaluation factor Y for the level of infrastructure construction in small towns. j Based on the corresponding standardized fitting curve, the evaluation factor Y of the infrastructure construction level of the w-th small town is calculated. j Actual infrastructure construction deviation index |Y j If it deviates from the index |Y j If the index is greater than 0, the infrastructure level of the small town corresponding to the single evaluation factor of small town infrastructure construction level is relatively good; if it deviates from the index... |Y j If the value is less than 0, then the infrastructure level of the small town corresponding to the single-item small town infrastructure construction level assessment factor is relatively poor. Under the current socio-economic development index, the single-item small town infrastructure construction level assessment factor Y should be increased. j The corresponding investment in small town resource development, if |Y j =0, then the evaluation factor Y of the level of infrastructure construction in a single small town j The corresponding level of infrastructure in small towns is equal to the average level.
[0050] In this embodiment, single evaluation factors such as the proportion of students enrolled in nearby public compulsory education schools (Y3) and the density of the road network in the built-up area (Y4) are selected for evaluation. This allows for the assessment of the construction level of individual evaluation factors based on a comprehensive evaluation. After understanding the existing problems in the infrastructure construction level of the selected typical towns in Province A, in order to further understand the problems, a single evaluation factor for the infrastructure construction level of a small town is selected for individual evaluation. In the TCI evaluation factors, taking Y3 as an example, the data obtained after standardization of the proportion of students enrolled in nearby public compulsory education schools (Y3) is placed in a coordinate system, with the socio-economic development index (TDI) as the horizontal axis. （X）Using the proportion of students enrolled in nearby public compulsory education schools (Y3) as the ordinate, a series of coordinate points were generated. Then, mathematical analysis software such as MATLAB was used to generate a fitted curve. This curve represents the expected average level of the proportion of students enrolled in nearby public compulsory education schools (Y3) under different socioeconomic conditions. This curve serves as a reference standard. Similarly, see [link to relevant documentation]. Figure 7 Calculate the deviation index ( |Y3), this index means that the deviation from the index |Y3>0 indicates that the proportion of students enrolled in nearby public compulsory education schools (Y3) is relatively good. |Y3<0 indicates a poor level of construction, reflecting a poor rate of enrollment in nearby public compulsory education schools under socio-economic development conditions (Y3), and investment should be increased. If |Y3=0, then the proportion of students enrolled in nearby public compulsory education schools in the town (Y3) is equal to the average level.
[0051] Taking a town in City B as an example, the values of indicators Y1, Y2, Y3, Y5, and Y7 are above the fitted curve, indicating that the above-mentioned infrastructure construction has been effective. However, the values of indicators Y4, Y6, and Y8 are below the fitted curve, indicating that the above-mentioned infrastructure construction needs further improvement. Calculating the absolute value of the difference between the indicators below the curve and the curve itself, and sorting them by size, yields: |Y4|> |Y8|> The |Y6| indicates that for Yonghan Town, the most urgent task is to increase the density of its road network in the built-up area, followed by increasing the green coverage rate of the built-up area, and finally improving the sewage treatment facility system and increasing the COD influent concentration of the sewage treatment plant.
[0052] In this embodiment, the process of dynamically monitoring the level of infrastructure construction in small towns, using years as the dynamic calculation unit, includes: Selecting different socioeconomic development indices (TDI) (X) The sample towns are fitted with a standardized reference curve for town development level. In this embodiment, the sample towns need to objectively reflect the level of infrastructure development in small towns under different socioeconomic conditions, and the TCI of the sample towns is calculated. （Y） Repeating the method described in the above embodiments, a standardized curve is fitted, which can represent the level of urban infrastructure construction under different socioeconomic conditions. This curve is used as a reference standardized curve and is recognized as the standardized curve under different socioeconomic conditions.
[0053] This study examines the dynamics of socio-economic development in small towns. A small town (k) is selected for investigation, and its socio-economic development index and infrastructure development level are dynamically calculated annually. These are then plotted against a standardized reference curve, and the deviation index from the standardized curve is compared under different dynamic changes in socio-economic development levels. |Yk can enable dynamic monitoring and supervision of its infrastructure construction level.
[0054] In this embodiment, a small town r to be monitored is determined, and the socio-economic development index (TDI) of small town r is calculated annually using the year as the dynamic calculation unit. (X)r and infrastructure development level TCI (Y)r ; The annual socioeconomic development index (TDI) of small towns (X)r Infrastructure Development Level (TCI) (Y)r By comparing with the standardized reference curve for urban development levels, the deviation index for each year is determined. |Y r ; Based on the deviation index of each year |Y r To dynamically monitor the level of infrastructure construction in small towns; The process of dynamically monitoring the level of infrastructure construction in small towns, using years as the dynamic calculation unit, also includes: Evaluation factor Y for the level of infrastructure construction in selected small towns q , for Y q After standardization, the Socioeconomic Development Index (TDI) is used. （X） Using Y, a single-item small town infrastructure construction level assessment factor, as the horizontal axis. q Discrete points are generated, and a fitting is performed based on these discrete points to obtain the evaluation factor Y for the level of infrastructure construction in small towns. q Based on the corresponding standardized fitting curve, the individual small town infrastructure construction level assessment factor Y for small town r is calculated annually. q Actual infrastructure construction deviation index |Y q Based on the annual deviation index |Y q Dynamic monitoring of the level of individual infrastructure construction in small towns.
[0055] like Figure 8 As shown, taking the selected typical towns in Province A as the research objects, a standardized production curve is fitted to towns at different socioeconomic development levels. This curve can reflect the infrastructure construction level that small towns at different socioeconomic development stages should achieve, and it serves as a dynamic research reference coordinate system for a specific small town K. The selected research object sample k will have its socioeconomic development level (TDI) change over time. Based on the socioeconomic development level (TDI)... kIn specific cases, using standardized curves as a reference, it is possible to dynamically examine whether the construction level is lagging behind or ahead of schedule.
[0056] Dynamic monitoring is conducted on the individual assessment factors of the infrastructure development level (TCI) of small towns. The optimal factors for the infrastructure development level of the selected research object k are used to generate standardized curves for the individual factors of the infrastructure development level (TCI). Furthermore, the assessment factor Y of the infrastructure development level of the j-th small town is calculated for each year under different socio-economic development levels. k（J） By comparing the differences, it is possible to assess individual factors.
[0057] In this embodiment, the infrastructure construction level index of small towns is used as a reference sequence, and the standardized data obtained by standardizing the assessment factors of infrastructure construction level in small towns is used as a comparison sequence. Based on the pre-established grey relational analysis model (Grey relational analysis GRA is a decision-making and evaluation method for small sample and incomplete information systems), the infrastructure construction level correlation coefficient of the assessment factors of infrastructure construction level in small towns is determined. The process satisfies:
[0058]
[0059]
[0060] in, This represents the absolute difference of the assessment factors for the infrastructure development level of the i-th small town. This represents the correlation coefficient of infrastructure construction level for the i-th small town infrastructure construction level assessment factor. This represents the correlation degree of the infrastructure construction level assessment factor of the i-th small town. , These are the assessment factors for the infrastructure construction level of the i-th small town. The absolute value of the difference between the maximum and minimum values of the Small Town Infrastructure Development Index (TCI). The resolution coefficient; In this embodiment, among the eight evaluation items of the facility construction level index, "density of drainage pipes in built-up areas Y5" was rated the highest (correlation degree: 0.713), followed by "density of road network in built-up areas Y4" (correlation degree: 0.673), and then "coverage rate of cultural and sports facilities within 15 minutes' walk Y2" (correlation degree: 0.671). The correlation coefficients are shown in Table 6.
[0061] Table 6
[0062] The larger the correlation coefficient of the infrastructure construction level assessment factor for small towns, the stronger the driving force of the infrastructure construction level assessment factor on the infrastructure construction level of small towns. In this embodiment, a correlation coefficient R > 0.65 indicates a strong correlation, meaning the infrastructure construction level assessment factor has a strong driving force for restructuring and development; 0.6 < R ≤ 0.65 indicates a moderate correlation, meaning the infrastructure construction level assessment factor has a relatively strong driving force for restructuring and development; and R ≤ 0.6 indicates a weak correlation, meaning the infrastructure construction level assessment factor has a relatively weak driving force for restructuring and development.
[0063] Taking a town in City B as an example, the values of indicators Y1, Y2, Y3, Y5, and Y7 are above the fitted curve, indicating that the above-mentioned infrastructure construction has achieved good results. However, the values of indicators Y4, Y6, and Y8 are below the fitted curve, indicating that the above-mentioned infrastructure construction needs further improvement. Looking at the correlation coefficients, the correlation coefficient of Y4 is greater than that of Y8, and the correlation coefficient of Y8 is greater than that of Y6. This indicates that among these indicators, increasing the road network density (Y4) in the built-up area has a significant effect on improving the level of infrastructure construction in small towns; the green coverage rate (Y8) in the built-up area is second, and the average annual COD influent concentration of urban sewage treatment plants (Y6) is last. Therefore, a construction feedback mechanism based on a dynamic model is obtained.
[0064] In this embodiment, the correlation coefficient of infrastructure construction level reflects the driving force of the assessment factors for infrastructure construction level in small towns on improving the infrastructure construction level index, presenting the differences in the contribution of various facilities to the improvement of construction level. Among them, the three preferred factors, namely, the density of drainage pipes in the built-up area (Y5), the density of the road network in the built-up area (Y4), and the coverage rate of cultural and sports facilities within a 15-minute walk (Y2), have higher gray coefficients and have a greater impact on the infrastructure construction level (TCI). On the other hand, the three indicators, namely, the green coverage rate in the built-up area (Y8), the annual average COD influent concentration of urban sewage treatment plants (Y6), and the street space quality evaluation (Y7), have a relatively large impact on the infrastructure construction level (TCI). The two indicators, namely, the number of beds in medical and health institutions per thousand people (Y1) and the proportion of public compulsory education schools enrolled in nearby schools (Y3), have a relatively small impact on the infrastructure construction level (TCI). Therefore, in examining the infrastructure construction level (TCI) of the kth small town in the study, we can identify which factor is the key weakness, conduct system early warning and feedback, and form guidance and feedback opinions for construction.
[0065] In summary, based on the calculation results, spatial analysis software such as ArcGIS can be used to generate a visual interface, enabling dynamic visual evaluation and display of a specific area.
[0066] Example 3 like Figure 9As shown, this embodiment proposes a system for implementing the dynamic evaluation method for the infrastructure construction level of small towns. This system can be used to implement the dynamic evaluation method for the infrastructure construction level of small towns proposed in Embodiments 1 and 2. See [link / reference]. Figure 9 The system structure includes: The evaluation factor screening and processing module is used to preprocess the selected evaluation factors to obtain preprocessed evaluation factors, and divide the preprocessed evaluation factors into evaluation factors for the development stage of small towns and evaluation factors for the level of infrastructure construction in small towns. The factor weight calculation module selects typical small towns as research objects, collects construction data of typical small towns corresponding to the evaluation factors, and calculates the weights of the evaluation factors of the development stage of small towns and the evaluation factors of the infrastructure construction level of small towns respectively. The index quantification module standardizes the evaluation factors of small town development stage based on their weights, and quantifies the socio-economic development index; it also standardizes the evaluation factors of small town infrastructure construction level based on their weights, and quantifies the infrastructure construction level index. The first standardized curve fitting module is used to select small towns as research samples within a certain area, associate the small town development stage assessment factor with the small town infrastructure level assessment factor, and fit a standardized assessment curve based on the correspondence between the socio-economic development index and the infrastructure construction level index. The first assessment module uses a standardized assessment curve as a benchmark to calculate the deviation index of actual infrastructure construction in a single small town in order to assess the level of infrastructure construction in a single small town. The second standardized curve fitting module is used to select sample towns and fit a standardized reference curve for the town's construction level. The curve is dynamically calculated in years to monitor the level of infrastructure construction in small towns. The second evaluation module, based on a pre-established grey relational analysis model, determines the correlation coefficient of infrastructure construction level of small town infrastructure construction level evaluation factors, and based on the correlation coefficient, conducts a reconstructed development driving force evaluation to provide resource allocation guidance feedback for town construction.
[0067] The embodiments described are merely examples to clearly illustrate the present invention and are not intended to limit the implementation of the invention. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively describe all possible implementations. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the claims of the present invention.
Claims
1. A method for dynamic evaluation of the infrastructure construction level of small towns, characterized in that, Includes the following steps: The selected evaluation factors are preprocessed to obtain preprocessed evaluation factors. The preprocessed evaluation factors are then divided into evaluation factors for the development stage of small towns and evaluation factors for the level of infrastructure construction in small towns. Typical small towns were selected as research objects, and construction data of typical small towns corresponding to the evaluation factors were collected. The weights of the evaluation factors of the development stage of small towns and the evaluation factors of the infrastructure construction level of small towns were calculated respectively. Based on the weights of the evaluation factors for the development stage of small towns, the evaluation factors for the development stage of small towns are standardized and the socio-economic development index is quantified. Based on the weights of the evaluation factors for the level of infrastructure construction in small towns, the evaluation factors for the level of infrastructure construction in small towns are standardized and the infrastructure construction level index is quantified. Small towns were selected as research samples within a certain area. The evaluation factors of the development stage of small towns in the research samples were correlated with the evaluation factors of the infrastructure level of small towns. Based on the correspondence between the socio-economic development index and the infrastructure construction level index, a standardized evaluation curve was fitted. Using a standardized assessment curve as a benchmark, the deviation index of actual infrastructure construction in a single small town is calculated to assess the level of infrastructure construction in that small town. Select sample towns, fit a standardized reference curve for town construction level, and use the year as the dynamic calculation unit to dynamically monitor the level of infrastructure construction in small towns; Based on a pre-established grey relational analysis model, the correlation coefficient of infrastructure construction level of small town infrastructure construction level assessment factors is determined. Based on the correlation coefficient, the assessment of development driving force is reconstructed, and resource allocation guidance feedback is provided for town construction.
2. The method for dynamic evaluation of the infrastructure construction level of small towns according to claim 1, characterized in that, The process of preprocessing the selected evaluation factors to obtain the preprocessed evaluation factors is as follows: Based on the standard requirements for small town infrastructure construction assessment and the difficulty in obtaining indicator data, small town development index assessment indicators are obtained, including primary indicators, secondary indicators and tertiary indicators; Based on the primary, secondary, and tertiary indicators, an expert consultation questionnaire survey was conducted to screen preliminary evaluation factors from the primary, secondary, and tertiary indicators. Principal component analysis was used to further screen the preliminary evaluation factors to obtain effective evaluation factors. Redundant evaluation information is removed from the effective evaluation factors to obtain preprocessed evaluation factors.
3. The method for dynamic evaluation of the infrastructure construction level of small towns according to claim 1, characterized in that, The small town development stage assessment factor is used to assess the socio-economic development index (TDI), denoted as X1, X2, ..., X... i Xn, where n represents the number of evaluation factors for the development stage of small towns; The assessment factors for the level of infrastructure construction in small towns are used to assess the TCI (Training Cost Index) of infrastructure construction in small towns, denoted as Y1, Y2, Y3, ..., Y... j Y m , m represents the number of assessment factors for the level of infrastructure construction in small towns.
4. The method for dynamic evaluation of the infrastructure construction level of small towns according to claim 1, characterized in that, After collecting typical small town construction data corresponding to the evaluation factors, the range method was used to standardize the collected typical small town construction data; the entropy weight method and the analytic hierarchy process were used to perform linear weighting calculation on the processed typical small town construction data to obtain the weights of the infrastructure construction level evaluation factors and the socio-economic development index evaluation factors, respectively. The evaluation factors for the development stage of small towns are standardized, and the expression for quantifying the socio-economic development index is as follows: TDI (X) = The evaluation factors for the level of infrastructure construction in small towns are standardized, and the expression for quantifying the infrastructure construction level index is as follows: TCI (Y) Among them, TDI （X） This represents the socio-economic development index of small towns. This represents the weight of the evaluation factor for the i-th stage of small town development, i=1,2,...,n; TCI (Y) This represents an index indicating the level of infrastructure development in small towns. Let represent the weight of the evaluation factor for the infrastructure construction level of the j-th small town, where j = 1, 2, ..., m.
5. The method for dynamic evaluation of the infrastructure construction level of small towns according to claim 4, characterized in that, The research sample consists of small towns with different socio-economic development indices selected within a national region or province, and the socio-economic development indices of these small towns conform to a normal distribution. Based on the correlation between the socio-economic development index and the infrastructure construction level index, using the socio-economic development index of small towns in the research sample as the horizontal axis and the infrastructure construction level index of small towns in the research sample as the vertical axis, a standardized evaluation curve is fitted based on the research sample to obtain a standardized evaluation curve. This standardized evaluation curve represents the average level of infrastructure construction in small towns under different socio-economic development levels during a certain period. The expression for the standardized evaluation curve is: Y k =aX k 2 +bX k +c Among them, X k Y represents the socioeconomic development index of the kth town. k The dependent variable is the average level that the infrastructure construction of the kth small town should reach in the fitted curve, where k is a positive integer and n is the number of factors, k=1,2,…,n.
6. The method for dynamic evaluation of the infrastructure construction level of small towns according to claim 5, characterized in that, The process of calculating the deviation index of actual infrastructure construction in a single small town, based on a standardized assessment curve, to assess the level of infrastructure construction in that small town includes: Based on the expression for the quantitative infrastructure development level index, calculate the socio-economic development index (TCI) of the w-th small town in a certain period. (Y)w ; Based on the expression of the standardized evaluation curve, calculate the average level Y that the infrastructure construction of the w-th small town should reach in a certain period. w ; Based on the socio-economic development index (TCI) of the wth small town (Y)w And the average level Y that the infrastructure construction of the wth small town should reach. w The deviation index of actual infrastructure construction in the w-th small town is calculated as follows: |And w =TCI (Y)w -AND w If it deviates from the index |Y w If the index is greater than 0, then the infrastructure level of the w-th town is relatively good, and the construction quality of the town is relatively high under the current socio-economic development index; if it deviates from the index... |Y w If the value is less than 0, then the infrastructure construction level of the w-th small town is relatively poor. Under the current socio-economic development index, the construction quality of the small town is poor, and resource investment should be increased. |Y w If the value is 0, then the infrastructure level of the wth town is equal to the average level.
7. The method for dynamic evaluation of the infrastructure construction level of small towns according to claim 6, characterized in that, The process of calculating the deviation index of actual infrastructure construction in a single small town, based on a standardized assessment curve, to assess the level of infrastructure construction in that small town also includes: Select a single small town's infrastructure development level assessment factor Y j , for Y j After standardization, the Socioeconomic Development Index (TDI) is used. （X） Using Y, a single-item small town infrastructure construction level assessment factor, as the horizontal axis. j Discrete points are generated, and a fitting is performed based on these discrete points to obtain the evaluation factor Y for the level of infrastructure construction in a small town. j Based on the corresponding standardized fitting curve, the evaluation factor Y of the infrastructure construction level of the w-th small town is calculated. j Actual infrastructure construction deviation index |Y j If it deviates from the index |Y j If the index is greater than 0, the infrastructure level of the small town corresponding to the single evaluation factor of small town infrastructure construction level is relatively good; if it deviates from the index... |Y j If the value is less than 0, then the infrastructure level of the small town corresponding to the single-item small town infrastructure construction level assessment factor is relatively poor. Under the current socio-economic development index, the single-item small town infrastructure construction level assessment factor Y should be increased. j The corresponding investment in small town resource development, if |Y j =0, then the evaluation factor Y of the level of infrastructure construction in a single small town j The corresponding level of infrastructure in small towns is equal to the average level.
8. The method for dynamic evaluation of the infrastructure construction level of small towns according to claim 7, characterized in that, The process of dynamically monitoring the level of infrastructure construction in small towns, using years as the dynamic calculation unit, includes: Selecting different socioeconomic development indices (TDI) (X) The sample towns are to be selected, and the sample towns must meet the normal distribution. A standardized reference curve for the level of urban construction is fitted. The small town r to be monitored is identified, and the socio-economic development index (TDI) of small town r is calculated annually using the year as the dynamic calculation unit. (X)r and infrastructure development level TCI (Y)r ; The annual socioeconomic development index (TDI) of small towns (X)r Infrastructure Development Level (TCI) (Y)r By comparing with the standardized reference curve for urban development levels, the deviation index for each year is determined. |Y r ; Based on the deviation index of each year |Y r To dynamically monitor the level of infrastructure construction in small towns; The process of dynamically monitoring the level of infrastructure construction in small towns, using years as the dynamic calculation unit, also includes: Evaluation factor Y for the level of infrastructure construction in selected small towns q , for Y q After standardization, the Socioeconomic Development Index (TDI) is used. （X） Using Y, a single-item small town infrastructure construction level assessment factor, as the horizontal axis. q Discrete points are generated, and a fitting is performed based on these discrete points to obtain the evaluation factor Y for the level of infrastructure construction in a small town. q Based on the corresponding standardized fitting curve, the individual small town infrastructure construction level assessment factor Y for small town r is calculated annually. q Actual infrastructure construction deviation index |Y q Based on the annual deviation index |Y q Dynamic monitoring of the level of individual infrastructure construction in small towns.
9. The method for dynamic evaluation of the infrastructure construction level of small towns according to claim 1, characterized in that, Using the infrastructure construction level index of small towns as reference sequences and the standardized data obtained from the standardized processing of the infrastructure construction level assessment factors of small towns as comparison sequences, the correlation coefficient of infrastructure construction level of the assessment factors of small towns is determined based on a pre-established grey relational analysis model. The process satisfies the following: in, This represents the absolute difference of the assessment factors for the infrastructure development level of the i-th small town. This represents the correlation coefficient of infrastructure construction level for the i-th small town infrastructure construction level assessment factor. This represents the correlation degree of the infrastructure construction level assessment factor of the i-th small town. , These are the assessment factors for the infrastructure construction level of the i-th small town. The absolute value of the difference between the maximum and minimum values of the Small Town Infrastructure Development Index (TCI). The resolution coefficient, The larger the correlation coefficient of the infrastructure construction level assessment factor of small towns, the stronger the driving force of the infrastructure construction level assessment factor on the infrastructure construction level of small towns.
10. A system for implementing the dynamic evaluation method for the infrastructure construction level of small towns as described in claim 1, characterized in that, include: The evaluation factor screening and processing module is used to preprocess the selected evaluation factors to obtain preprocessed evaluation factors, and divide the preprocessed evaluation factors into evaluation factors for the development stage of small towns and evaluation factors for the level of infrastructure construction in small towns. The factor weight calculation module selects typical small towns as research objects, collects construction data of typical small towns corresponding to the evaluation factors, and calculates the weights of the evaluation factors of the development stage of small towns and the evaluation factors of the infrastructure construction level of small towns respectively. The index quantification module standardizes the evaluation factors of small town development stage based on their weights, and quantifies the socio-economic development index. Based on the weights of the evaluation factors for the level of infrastructure construction in small towns, the evaluation factors for the level of infrastructure construction in small towns are standardized and the infrastructure construction level index is quantified. The first standardized curve fitting module is used to select small towns as research samples within a certain area, associate the small town development stage assessment factor with the small town infrastructure level assessment factor, and fit a standardized assessment curve based on the correspondence between the socio-economic development index and the infrastructure construction level index. The first assessment module uses a standardized assessment curve as a benchmark to calculate the deviation index of actual infrastructure construction in a single small town in order to assess the level of infrastructure construction in a single small town. The second standardized curve fitting module is used to select sample towns and fit a standardized reference curve for the town's construction level. The curve is dynamically calculated in years to monitor the level of infrastructure construction in small towns. The second evaluation module, based on a pre-established grey relational analysis model, determines the correlation coefficient of infrastructure construction level of small town infrastructure construction level evaluation factors, and based on the correlation coefficient, conducts a reconstructed development driving force evaluation to provide resource allocation guidance feedback for town construction.