DPSIR公司
可持续发展
持续性
蚁群优化算法
可持续城市
层次分析法
计算机科学
环境经济学
城市规划
运筹学
环境资源管理
土木工程
工程类
环境科学
经济
生物
算法
法学
生态学
政治学
作者
Zhenhua Luo,Zijing Chen,Xiaoqing Wu,Haize Pan,Fanglin Wang,Rui Tu,Zongquan Yao,Yue Wang,Shou-Chi Chen
标识
DOI:10.1007/s10668-024-05902-w
摘要
The integrated station-city urban space development model based on public transportation-oriented development solves problems such as chaotic traffic order and provides new ideas for promoting sustainable urban development. Evaluating the sustainability of station-city integration at the station-city integration planning and development stage can solve the current problems of station-city integration development, such as low efficiency of transportation synergy and lack of coordination and organization of land development. This paper constructs a sustainability evaluation index system for station-city integration based on the Driving Force-Pressure-State-Impact-Response-Sustainable Development Goals (SDGs) framework, which effectively integrates the resource, economic, and environmental factors of station-city integration and solves the problem of the SDGs model's broad designation. The influence relationship among the indicators was analyzed using network hierarchy analysis (ANP), and the weights of the indicators were determined. A genetically improved Ant Colony Optimization (ACO) algorithm establishes a sustainability evaluation model for station-city integration. The genetically improved ACO algorithm effectively overcomes the shortcomings of the ACO algorithm, such as the tendency of the ACO algorithm to fall into the local optimum, and the model is easy to calculate and operate. Taking the Chengdu X station project in China as an example for empirical research, the results show that the overall sustainability level of this station-city integration project is IV (good), and 18 out of 33 third-level indicators are Higher Sensitivity indicators. Finally, combining the indicator weights and sensitivity, the study proposes targeted sustainable development planning suggestions for the three types of indicators: Higher Weight–Higher Sensitivity, Higher Weight–Low Sensitivity, and Low Weight–Higher Sensitivity. The evaluation system and evaluation model of station-city integration sustainable development proposed in this study provide a theoretical basis for decision-makers to carry out station-city integration sustainable development planning.
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