# Feasibility Assessment of the Construction of Characteristic Towns in Revolutionary Areas Based on Grey Correlation

Authors: Wei Bi; Guangming Wang; Meijuan Zhang
Journal: Mobile Information Systems
 (2022)

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## Abstract

With the gradual acceleration of urban transformation, the characteristic towns in the revolutionary areas have received great attention as a new carrier for the development of new urbanization. It is critical to conduct a thorough and complete evaluation of the unique town project and to take appropriate corresponding measures to ensure the project’s development and success. This study presents the important policy aspects that determine the long-term evolution of characteristic town projects based on a theoretical examination of their construction. Based on this, this study builds and combines the grey relational method to solve the weight of each index under various industry types and then obtains the best model for evaluating characteristics town construction projects. Considering the differences of regions and the focus of industries, this paper constructs the evaluation index system and optimization model of characteristic towns under different industry types and verifies the validity of the model. This model provides a reference for the evaluation and optimization of construction projects of characteristic towns in other regions.


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## Body

## 1. Introduction

Characteristic town is an important measure to promote economic transformation and upgrading, promote the coordinated and balanced development of urban and rural areas, and promote new urbanization and new rural construction [1, 2]. Characteristic towns, when combined with the development model concept of characteristic towns and the task of rural revitalization, can become an essential vehicle for driving rural economic development and can provide new development ideas for achieving rural revitalization strategic goals [3]. With the emergence of various national preferential policies and indicators, the development of characteristic towns has embarked on a fast track, and the development of characteristic towns has risen one after another, and more and more developers and investors have devoted themselves to the construction of characteristic towns [4, 5].With the support of policies, characteristic towns have developed and built rapidly in China. Although many achievements have been made, there are still some problems. One is that the early selection of characteristic town projects is too subjective and there is no objective measure and standard [6–8]. Felix et al. [9] combined theory and practice, established a KPI evaluation index system for road infrastructure projects, and determined the elements of sustainability assessment of road infrastructure projects accordingly. Based on the case study method, Jesse et al. [10] determined the sustainable management control measures of infrastructure projects in the implementation phase. Zhou et al. [11] proposed the need for a national standard framework to assist key stakeholders in making decisions on sustainability based on a questionnaire method. Marlies et al. [12] argue that sustainability is largely ignored in projects and explore incentives for incorporating sustainability considerations into infrastructure projects based on a case study approach. Thomson et al. [13] emphasized the important role of knowledge exchange among stakeholders in the sustainability assessment of the project life cycle. Under the background of the country’s vigorous promotion of new urbanization construction, economic transformation and upgrading, and the implementation of rural revitalization strategies, the proposal of characteristic towns is innovative and contemporary [14, 15]. At present, all local governments are actively applying for characteristic town projects, but funds and resources are limited. Therefore, higher-level governments should try their best to select projects with better foundations and better development prospects for investment and construction. In this way, towns with unreasonable planning or unsuitable natural geography can be avoided, and the waste of resources caused by blind construction can be avoided, to realize the rapid return of funds and the optimization and maximization of resource utilization [16, 17].Based on this, this study starts from the early selection of characteristic town construction projects, and through theoretical analysis of characteristic town construction, this paper summarizes the key policy factors that affect the sustainable development of characteristic town projects. On this basis, this paper combines the grey relational algorithm to solve the weight of each index under different industry types and finally obtains the optimal model for the evaluation of characteristic town construction projects. It is believed that by developing an evaluation model suited for the selection of characteristic town construction projects, it may be believed to assist the government in selecting the most appropriate characteristic town projects for investment and development.


## 2. Overview of Related Technologies

The construction of characteristic towns of industrial development type, agricultural service type, and trade circulation type can drive the development of the town’s own industry. The construction of characteristic towns of historical and cultural type and tourism development type can also alleviate the “tourism pressure” of popular tourist areas during holidays [18, 19]. The construction of different types of characteristic towns can stimulate the prosperity and balanced development of the regional economy to a certain extent. Characteristic towns, as distinct from administrative towns and industrial parks, are innovation and entrepreneurship platforms that focus on characteristic industries and developing industries and collect development elements [20]. According to policy requirements, the planned area of such towns is generally about 3 square kilometers, and the construction area should be controlled at about 1 square kilometer. The industrial positioning of the town is more clear, the cultural connotation is rich, and the production, living, and ecological space of the town are integrated [21, 22]. For example, the Yuhuang Shannan Fund Town is dominated by the financial industry in Zhejiang, and the Yuhang Dream Town is dominated by Internet entrepreneurship. The industrial types of characteristic towns are more diverse, such as information technology, financial economy, handicraft manufacturing, trade and logistics, agriculture, forestry, animal husbandry and fishery, energy and chemical industry, biomedicine, science, education, culture and sports, and a series of industries [23]. Figure 1 shows the selection process of the sustainability evaluation index system for characteristic town projects.Figure 1
Construction path architecture of characteristic towns.Characteristic small towns refer to administrative towns with traditional administrative divisions as units, distinctive industries, and a certain population and economic scale. Generally, it refers to villages and towns with important geographical location, unique resource advantages, relatively concentrated industries, a certain scale of economic development, and at the same time unique in terms of architecture and culture. The planning and construction of such towns generally covers the area of the entire township. Compared with the conventional characteristic towns, the planning and construction area is larger [24]. To sum up, it can be seen that both characteristic towns and characteristic small towns refer to a modern community with characteristics and cultural atmosphere developed and formed based on a certain characteristic industry and gathering relevant elements such as organizations, institutions, enterprises, and personnel. These two forms complement each other and support each other. In the process of development, we must combine our own characteristics, identify the industry positioning, tap our own characteristics, combine the local cultural heritage and ecological resource endowments, and finally form an organic “production, city, people, and culture,” an important functional platform for integration.


## 3. Research on Information Mining of English Film and Television Resources Based on Grey Relational

### 3.1. Construction of the Indicator System

The index system is the basis for comprehensive evaluation. When analyzing and evaluating the sustainability of a project, a single or several indicators cannot fully and accurately reflect the sustainability of the project. A series of indicators that reflect multiple aspects are required to form an indicator system to reflect the sustainability of the project. Establishing a reasonable index system is a key link to ensure the quality of sustainable project evaluation [25]. Therefore, the sustainable evaluation of characteristic town projects is firstly reflected in the evaluation of economic benefits. Different from general characteristic towns, social capital plays a decisive role in the operation of characteristic town projects operating in mode. Therefore, the evaluation of the economic benefits of characteristic town projects must also consider the overall economic benefits of the town and consider the return on investment that social capital can bring to the town [26, 27]. Secondly, the sustainability evaluation of characteristic town projects is mainly reflected in the ecological environment. The investment and increase of the industrial economy will inevitably lead to pollution emissions. To achieve the coordination and unity with the ecological environment while developing the economy, the bearing capacity of the ecological environment and the small size must be considered, the pollution control capacity of the town itself [28]. Finally, the evaluation of the long-term viability of characteristic town projects is mostly based on social benefits. Industrial economic development will push social and economic development with significant impact on national economic and social development. It is necessary to consider the economic benefits that drive social benefits.Figure2 describes the selection process of the sustainability evaluation index system of the characteristic town project.Figure 2
The selection process of the sustainability evaluation index system for characteristic town projects.Starting from the connotation of sustainable development of characteristic town projects, the sustainability evaluation can be divided into three dimensions, namely, the sustainability of economic benefits, the sustainability of social benefits, and the sustainability of ecological environment. Following the above principles and methods for the construction of the index system, on the basis of a large number of theoretical studies, and consulting experts, this paper constructs a sustainability evaluation index system in three aspects: economic benefit, social benefit, and ecological environment for the characteristic town project.Among them, the economic benefit evaluation indicators include the total industrial output value and the financial internal rate of return of social capital [29]. The social benefit evaluation indicators include per capita output value and per capita road mileage. The ecological environment evaluation indicators include solid waste pollution discharge and comprehensive utilization of solid waste, wastewater pollution discharge, and wastewater treatment volume.


### 3.2. Feasibility Assessment Method

Since the previous article, the grey relational algorithm in this chapter solves the weights of each index under different industry types [14] and finally obtains the optimal model for the evaluation of characteristic town construction projects. The data series that grey relational theory needs to deal with are various, some of them have no dimension, and the dimension may be inconsistent. The improved grey slope correlation degree is used for correlation analysis, which satisfies the uniqueness, symmetry, and comparability of correlation analysis, which makes this method have good use value. At the same time, the calculation method introduces a sign function m to reflect the correlation between positive and negative correlations. It is meaningless to process data sequences in different forms, so before performing association analysis, it is necessary to initialize the data sequences. Of course, according to the analysis of the situation, the initialization step can sometimes be omitted, for example, when the data sequences to be processed all have the same dimension.
(1)μτ,p=∑iNxdt=τ+pxi,xiΔxi.Correlation analysis can be performed regardless of time series, indicator series or horizontal data series, but it should be noted that different types of data must be classified and processed.(2)μ=LHda,d′=Lμb.The data sequence is defined as shown above. The data sequence must be initialized before it can be used for association analysis. Initialization has two purposes: one is to remove the dimension, and the other is to translate the data. Different initialization operators have different purposes and have their own characteristics and purposes.(3)xj′≤xj≤xj′′j=1,2,⋯,n,gj≤gj′′j=1,2,⋯,n,hj′≤hjxj=1,2,⋯,n,wj′≤wjx≤wj′′j=1,2,⋯,n.The main function of the averaging operator is to eliminate the dimension. At the same time, the averaging operator’s data swings around 1, indicating the degree of deviation of distinct data points from the mean. The data sequence here might refer to either the original or the initialized data sequence.(4)μ=LHL−1LHd,(5)d′t,x=∑jNpμτ=t−pjx,pjΔpj.However, its essential meaning is the same, that is, the data sequence is represented by geometric shapes, which is convenient for analyzing its geometric properties. And since whether the data is initialized needs to be selected according to the actual situation, if no special description is given below, it is considered that all data sequences have been initialized.(6)d′t,x=∫−∞+∞μτ−px,xdp.In the current study, the TOPSIS evaluation model is used to optimize the construction projects of characteristic towns. The TOPSIS is a method which is used to solve decision-making problems. In the actual application of the TOPSIS method, the phenomenon of reverse order will occur, and when the number of schemes is increased or decreased, the decision makers not only need to renormalize the decision matrix but also redetermine the ideal solution according to the scheme, which will lead to the original calculation, and decision-making results are meaningless.(7)Dv=∑Cvi,vj,wherevi,vj∈V.Objectively speaking, the change of the number of plans changes the decision-making environment, so the appearance of the reverse order phenomenon is also objective and reasonable, and people also recognize its rationality in many practices.(8)Dvn+1=minDvn+Cvi,w,wherevi∈U,w∈V−U.However, the appearance of the reverse order will make people confused and disturbed, because when a scheme is added or removed, the attribute values of the original scheme will not change, and the reverse order phenomenon should not occur. Subjectively, decision makers hope that the decision-making method is order-preserving, that is, the change of the number of plans does not affect the decision-making result; otherwise, it will lead to confusion in the decision-making, which is the subjective irrationality of the reverse order.


## 3.1. Construction of the Indicator System

The index system is the basis for comprehensive evaluation. When analyzing and evaluating the sustainability of a project, a single or several indicators cannot fully and accurately reflect the sustainability of the project. A series of indicators that reflect multiple aspects are required to form an indicator system to reflect the sustainability of the project. Establishing a reasonable index system is a key link to ensure the quality of sustainable project evaluation [25]. Therefore, the sustainable evaluation of characteristic town projects is firstly reflected in the evaluation of economic benefits. Different from general characteristic towns, social capital plays a decisive role in the operation of characteristic town projects operating in mode. Therefore, the evaluation of the economic benefits of characteristic town projects must also consider the overall economic benefits of the town and consider the return on investment that social capital can bring to the town [26, 27]. Secondly, the sustainability evaluation of characteristic town projects is mainly reflected in the ecological environment. The investment and increase of the industrial economy will inevitably lead to pollution emissions. To achieve the coordination and unity with the ecological environment while developing the economy, the bearing capacity of the ecological environment and the small size must be considered, the pollution control capacity of the town itself [28]. Finally, the evaluation of the long-term viability of characteristic town projects is mostly based on social benefits. Industrial economic development will push social and economic development with significant impact on national economic and social development. It is necessary to consider the economic benefits that drive social benefits.Figure2 describes the selection process of the sustainability evaluation index system of the characteristic town project.Figure 2
The selection process of the sustainability evaluation index system for characteristic town projects.Starting from the connotation of sustainable development of characteristic town projects, the sustainability evaluation can be divided into three dimensions, namely, the sustainability of economic benefits, the sustainability of social benefits, and the sustainability of ecological environment. Following the above principles and methods for the construction of the index system, on the basis of a large number of theoretical studies, and consulting experts, this paper constructs a sustainability evaluation index system in three aspects: economic benefit, social benefit, and ecological environment for the characteristic town project.Among them, the economic benefit evaluation indicators include the total industrial output value and the financial internal rate of return of social capital [29]. The social benefit evaluation indicators include per capita output value and per capita road mileage. The ecological environment evaluation indicators include solid waste pollution discharge and comprehensive utilization of solid waste, wastewater pollution discharge, and wastewater treatment volume.


## 3.2. Feasibility Assessment Method

Since the previous article, the grey relational algorithm in this chapter solves the weights of each index under different industry types [14] and finally obtains the optimal model for the evaluation of characteristic town construction projects. The data series that grey relational theory needs to deal with are various, some of them have no dimension, and the dimension may be inconsistent. The improved grey slope correlation degree is used for correlation analysis, which satisfies the uniqueness, symmetry, and comparability of correlation analysis, which makes this method have good use value. At the same time, the calculation method introduces a sign function m to reflect the correlation between positive and negative correlations. It is meaningless to process data sequences in different forms, so before performing association analysis, it is necessary to initialize the data sequences. Of course, according to the analysis of the situation, the initialization step can sometimes be omitted, for example, when the data sequences to be processed all have the same dimension.
(1)μτ,p=∑iNxdt=τ+pxi,xiΔxi.Correlation analysis can be performed regardless of time series, indicator series or horizontal data series, but it should be noted that different types of data must be classified and processed.(2)μ=LHda,d′=Lμb.The data sequence is defined as shown above. The data sequence must be initialized before it can be used for association analysis. Initialization has two purposes: one is to remove the dimension, and the other is to translate the data. Different initialization operators have different purposes and have their own characteristics and purposes.(3)xj′≤xj≤xj′′j=1,2,⋯,n,gj≤gj′′j=1,2,⋯,n,hj′≤hjxj=1,2,⋯,n,wj′≤wjx≤wj′′j=1,2,⋯,n.The main function of the averaging operator is to eliminate the dimension. At the same time, the averaging operator’s data swings around 1, indicating the degree of deviation of distinct data points from the mean. The data sequence here might refer to either the original or the initialized data sequence.(4)μ=LHL−1LHd,(5)d′t,x=∑jNpμτ=t−pjx,pjΔpj.However, its essential meaning is the same, that is, the data sequence is represented by geometric shapes, which is convenient for analyzing its geometric properties. And since whether the data is initialized needs to be selected according to the actual situation, if no special description is given below, it is considered that all data sequences have been initialized.(6)d′t,x=∫−∞+∞μτ−px,xdp.In the current study, the TOPSIS evaluation model is used to optimize the construction projects of characteristic towns. The TOPSIS is a method which is used to solve decision-making problems. In the actual application of the TOPSIS method, the phenomenon of reverse order will occur, and when the number of schemes is increased or decreased, the decision makers not only need to renormalize the decision matrix but also redetermine the ideal solution according to the scheme, which will lead to the original calculation, and decision-making results are meaningless.(7)Dv=∑Cvi,vj,wherevi,vj∈V.Objectively speaking, the change of the number of plans changes the decision-making environment, so the appearance of the reverse order phenomenon is also objective and reasonable, and people also recognize its rationality in many practices.(8)Dvn+1=minDvn+Cvi,w,wherevi∈U,w∈V−U.However, the appearance of the reverse order will make people confused and disturbed, because when a scheme is added or removed, the attribute values of the original scheme will not change, and the reverse order phenomenon should not occur. Subjectively, decision makers hope that the decision-making method is order-preserving, that is, the change of the number of plans does not affect the decision-making result; otherwise, it will lead to confusion in the decision-making, which is the subjective irrationality of the reverse order.


## 4. Validation of the Evaluation Model for Characteristic Towns

### 4.1. Evaluation Sample Sources

The research object of this chapter is the X Happiness and Healthy Characteristic Town Project, so the space of the model is defined as the X Happiness and Healthy Characteristic Town. The total investment of the X Happiness and Healthy Characteristic Town Project is 9.3 trillion yuan. Social capital and the government will set up a project company based on 95% and 5% of the investment ratio and will be responsible for the overall construction, operation, and industry introduction of the characteristic town. Table1 shows the initial values of the model state variables and the associated constant value settings.Table 1
Model state variable initial value and related constant value setting.
State variablesParameter valueUnitState variablesParameter valueUnitEmployed population8000/Initial capital stock221382Ten thousand yuanTechnique level0.0234/Technical efficiency0.372/Construction investment940000Ten thousand yuanEnvironmental constraint coefficient0.042/Talent subsidy coefficient1/Initial value of Total population38000PeopleInitial investment rate12.24%/Birth rate.11.32%/Mortality rate5.13%/Comprehensive depreciation rate5.2%/The construction of the town includes public service and infrastructure projects and business projects. The public service and infrastructure projects adopt the PPP model, and the business projects adopt the industrial introduction model. The government does not give financial subsidies to the project and adopts a user-paid return mechanism. The income obtained from the introduction of industries during the cooperation period will return the investment in the subprojects of the infrastructure operated by the PPP model.


### 4.2. Evaluating Sample Simulation Results

According to the abovementioned characteristic town project sustainability evaluation model and the set initial value and constant value of variables, the Vensim PLE software is used to carry out dynamic simulation. Vensim PLE is a business strength simulation software which enhances improving the implementation of real systems. This software is mainly applied in developing, analyzing, and packaging models. In the current study, it is obtained that under the influence of the existing policies, the characteristic town construction of the X Happiness and Healthy Characteristic Town Project will be the simulation results of economic benefits, social benefits, and sustainable ecological environment. In this project, the pollutant discharge cap policy factor, the infrastructure investment coefficient, and the talent subsidy coefficient are the most important policy variables that affect economic benefits, social benefits, and ecological environment. Policy control components include the pollutant discharge cap, talent subsidy coefficient, and infrastructure investment coefficient. The policy variable configuration schemes are shown in Table2.Table 2
Policy variable configuration scheme.
ScenePollution cap policy factorsInfrastructure investment coefficientTalent subsidy coefficientBaseline scenario1.001.001.00Economic development1.001.001.03Environmental goals0.801.001.00Coordinated development0.901.101.01Figure3 shows the simulation results of the total industrial output value from 2023 to 2043 under different policy configuration schemes of the X Happiness and Healthy Characteristic Town Project.Figure 3
Simulation results of gross industrial output value (GIOV).The talent subsidy coefficient is the key policy factor affecting economic growth in this project, according to the simulation results of the indicators. The total industrial output value and the financial internal rate of return of social capital are both significantly affected by increasing the talent subsidy coefficient. The higher the subsidy coefficient, the higher the greater the magnitude. The impact of the pollutant discharge cap policy factor on economic benefits is much smaller than that of the talent subsidy coefficient, and the effect is not obvious. From the simulation data, increasing the environmental protection efforts has reduced the inhibitory effect of environmental pressure on the industry to a certain extent, and the total industrial output value has slightly increased. However, the corresponding increase in environmental protection investment and the increase in environmental protection expenditure are greater than the industrial economic growth, resulting in a slight decrease in the financial internal rate of return of social capital. The talent subsidy coefficient, the pollutant discharge cap policy factor, and the infrastructure investment coefficient show a superposition effect when they act together on the project.The simulation results of the indicators of solid waste discharge, wastewater discharge, and exhaust gas discharge from 2023 to 2043 under different policy configuration schemes of the X Happiness and Healthy Characteristic Town PPP project are shown in Figure4 below.Figure 4
Solid Waste Emission (SWPE) simulation results.According to Figure4, the simulation results of the indicators, the pollutant discharge cap policy factor, have a good influence on pollution changes in the environment. The lower the amount, the less pollution there is in the environment. The rise in the talent subsidy coefficient has fueled the industrial economy’s expansion and growth. Despite the fact that it has triggered a rise in the environmental protection investment, the processing capacity of the corresponding environmental protection investment is insufficient to control the three waste pollutions created by industrial economic growth. As a result, the higher the talent subsidy coefficient, the more pollution is produced and emitted.


## 4.1. Evaluation Sample Sources

The research object of this chapter is the X Happiness and Healthy Characteristic Town Project, so the space of the model is defined as the X Happiness and Healthy Characteristic Town. The total investment of the X Happiness and Healthy Characteristic Town Project is 9.3 trillion yuan. Social capital and the government will set up a project company based on 95% and 5% of the investment ratio and will be responsible for the overall construction, operation, and industry introduction of the characteristic town. Table1 shows the initial values of the model state variables and the associated constant value settings.Table 1
Model state variable initial value and related constant value setting.
State variablesParameter valueUnitState variablesParameter valueUnitEmployed population8000/Initial capital stock221382Ten thousand yuanTechnique level0.0234/Technical efficiency0.372/Construction investment940000Ten thousand yuanEnvironmental constraint coefficient0.042/Talent subsidy coefficient1/Initial value of Total population38000PeopleInitial investment rate12.24%/Birth rate.11.32%/Mortality rate5.13%/Comprehensive depreciation rate5.2%/The construction of the town includes public service and infrastructure projects and business projects. The public service and infrastructure projects adopt the PPP model, and the business projects adopt the industrial introduction model. The government does not give financial subsidies to the project and adopts a user-paid return mechanism. The income obtained from the introduction of industries during the cooperation period will return the investment in the subprojects of the infrastructure operated by the PPP model.


## 4.2. Evaluating Sample Simulation Results

According to the abovementioned characteristic town project sustainability evaluation model and the set initial value and constant value of variables, the Vensim PLE software is used to carry out dynamic simulation. Vensim PLE is a business strength simulation software which enhances improving the implementation of real systems. This software is mainly applied in developing, analyzing, and packaging models. In the current study, it is obtained that under the influence of the existing policies, the characteristic town construction of the X Happiness and Healthy Characteristic Town Project will be the simulation results of economic benefits, social benefits, and sustainable ecological environment. In this project, the pollutant discharge cap policy factor, the infrastructure investment coefficient, and the talent subsidy coefficient are the most important policy variables that affect economic benefits, social benefits, and ecological environment. Policy control components include the pollutant discharge cap, talent subsidy coefficient, and infrastructure investment coefficient. The policy variable configuration schemes are shown in Table2.Table 2
Policy variable configuration scheme.
ScenePollution cap policy factorsInfrastructure investment coefficientTalent subsidy coefficientBaseline scenario1.001.001.00Economic development1.001.001.03Environmental goals0.801.001.00Coordinated development0.901.101.01Figure3 shows the simulation results of the total industrial output value from 2023 to 2043 under different policy configuration schemes of the X Happiness and Healthy Characteristic Town Project.Figure 3
Simulation results of gross industrial output value (GIOV).The talent subsidy coefficient is the key policy factor affecting economic growth in this project, according to the simulation results of the indicators. The total industrial output value and the financial internal rate of return of social capital are both significantly affected by increasing the talent subsidy coefficient. The higher the subsidy coefficient, the higher the greater the magnitude. The impact of the pollutant discharge cap policy factor on economic benefits is much smaller than that of the talent subsidy coefficient, and the effect is not obvious. From the simulation data, increasing the environmental protection efforts has reduced the inhibitory effect of environmental pressure on the industry to a certain extent, and the total industrial output value has slightly increased. However, the corresponding increase in environmental protection investment and the increase in environmental protection expenditure are greater than the industrial economic growth, resulting in a slight decrease in the financial internal rate of return of social capital. The talent subsidy coefficient, the pollutant discharge cap policy factor, and the infrastructure investment coefficient show a superposition effect when they act together on the project.The simulation results of the indicators of solid waste discharge, wastewater discharge, and exhaust gas discharge from 2023 to 2043 under different policy configuration schemes of the X Happiness and Healthy Characteristic Town PPP project are shown in Figure4 below.Figure 4
Solid Waste Emission (SWPE) simulation results.According to Figure4, the simulation results of the indicators, the pollutant discharge cap policy factor, have a good influence on pollution changes in the environment. The lower the amount, the less pollution there is in the environment. The rise in the talent subsidy coefficient has fueled the industrial economy’s expansion and growth. Despite the fact that it has triggered a rise in the environmental protection investment, the processing capacity of the corresponding environmental protection investment is insufficient to control the three waste pollutions created by industrial economic growth. As a result, the higher the talent subsidy coefficient, the more pollution is produced and emitted.


## 5. Conclusion

It is of great significance to evaluate the characteristic of town project scientifically and comprehensively and take corresponding adjustment measures to ensure the development of the project. In this paper, the grey relational algorithm is used to solve the weights of each index under different industry types, and finally, the optimal model for the evaluation of characteristic town construction projects is obtained. This paper assesses the sustainability of X Happiness and Healthy Characteristic Town Project from three perspectives, economic benefit, social benefit, and environmental sustainability, and finds the main factors influencing the project’s sustainability based on a system sustainability analysis question. This paper only constructs an index system suitable for the construction of characteristic towns and can only provide a certain reference for the feasibility of the construction of characteristic towns. Exploring the viability of town construction on a larger scale may require adding or subtracting indicators. Therefore, it is not suitable for a feasibility study to measure the construction of characteristic towns on a larger scale. To sum up, with the development of characteristic towns and the support of a large amount of data, future research will be more objective and applicable in a wider range, and at the same time, the risks existing in the construction of characteristic towns will also be considered in depth.



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*Source: 3833031-2022-05-06.xml*