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Issue title: Artificial Intelligent Techniques and its Applications
Guest editors: Mahalingam Sundhararajan, Xiao-Zhi Gao and Hamed Vahdat Nejad
Article type: Research Article
Authors: Lu, Shengronga | Liu, Yaob; *
Affiliations: [a] School of Transportation, Wuhan University of Technology, Wuhan, China | [b] School of Logistics and Trade, Wuhan Business University, Wuhan, China
Correspondence: [*] Corresponding author. Yao Liu, School of Logistics and Trade, Wuhan Business University, Wuhan, China. E-mail: c2698197xionggo@163.com.
Abstract: On the background of national economic growth and urbanization process in a long period in China, urban transportation system has experienced an unprecedented growth. The growth of traffic volume and acceleration of motorization has caused a lot of environmental problems which seem more and more serious in some cities. So how to evaluate the sustainability of urban transportation system and ecological environment system has become an important issue. This paper constructs an evaluation index system through Delphi method, and Support Vector Machine which has been successfully applied to evaluate system states is used to make the evaluation. Twenty-two cities in Yangtze River Economic Belt is selected for empirical research. The results show that the evaluation index system is reasonable. Support vector machine can applicably evaluate the status of the selected cities in real time with robustness and fault-tolerant ability. The evaluation results can provide a scientific basis for future urban transportation development. Finally, suggestions including optimizing urban traffic structure, developing intelligent transportation system and strengthen the control of motor vehicle emissions and construction of road greening are provided with the purpose of ensuring and promoting the sustainability and coordination between urban transportation and ecological environment.
Keywords: Evaluation, urban transportation, ecological environment, sustainable development, support vector machine
DOI: 10.3233/JIFS-169376
Journal: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 2, pp. 831-838, 2018
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