Review Article

Evaluation of the Urban Low-Carbon Sustainable Development Capability Based on the TOPSIS-BP Neural Network and Grey Relational Analysis

Table 1

Research on evaluation index system of green development ability.

NumberAuthorResearch areaIndex

1(Yuan et al.) [61]Shandong peninsula City group, ChinaResource input, nonresource input, ideal output and nonideal output
2(Feng and Wang) [62]ChinaEnergy, labor, capital, GDP, and carbon dioxide emissions
3(Qiu et al.) [63]Xuzhou City group, ChinaInvestment in fixed assets, number of employees in the whole society, total energy consumption, GDP, and industrial sulfur dioxide emissions
4(Zhu et al.) [64]31 provinces and cities in mainland ChinaCapital stock, labor, energy consumption, GDP, and carbon dioxide emissions
5(Guo et al.) [65]34 cities in northeast ChinaConstruct evaluation indicators from the perspective of input-output, which mainly include indicators such as capital, labor, resource consumption, technological progress, economic development, industrial wastewater, industrial SO2, and industrial dust
6(Ma et al.) [66]285 prefecture-level cities in ChinaFrom the perspective of input-output, the construction includes capital stock, number of employees, total water supply, annual electricity consumption, GDP, per capita disposable income, green coverage, public financial expenditure, industrial wastewater discharge, PM2.5, SO2, the evaluation index system including urban registered unemployment rate
7(Feng et al.) [67]165 countries worldwideEnergy consumption, labor, capital, GDP, SO2 emissions, CO2 emissions
8(Pan et al.) [68]ChinaLabor, energy consumption and capital stock, GDP, CO2 emissions
9(Chen et al.) [69]ChinaConstructed green development evaluation indicators including labor, capital, energy consumption, expected output, and bad output.
10(Shao et al.) [70]Shanghai, ChinaConstructed input-output indicators including gross industrial output, capital, labor, energy consumption, carbon emissions, etc.