A Smart MCDM Framework to Evaluate the Impact of Air Pollution on City Sustainability: A Case Study from China

Qingyong Wang, Hong-Ning Dai and Hao Wang
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Qingyong Wang: Faculty of Information Technology, Macau University of Science and Technology, Macau SAR
Hong-Ning Dai: Faculty of Information Technology, Macau University of Science and Technology, Macau SAR
Hao Wang: Big Data Lab, Department of ICT and Natural Sciences, Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology, Ålesund 6009, Norway

Sustainability, 2017, vol. 9, issue 6, 1-17

Abstract: Air pollution has become one of the key environmental concerns in the urban sustainable development. It is important to evaluate the impact of air pollution on socioeconomic development since it is the prerequisite to enforce an effective prevention policy of air pollution. In this paper, we model the impact of air pollution on the urban economic development as a Multiple Criteria Decision Making (MCDM) problem. In particular, we propose a novel Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) analysis framework to evaluate multiple factors of air pollutants and economic development. Our method can overcome the drawbacks of conventional TOPSIS methods by using Bayesian regularization and the Back-Propagation (BP) neural network to optimize the weight training process. We have conducted a case study to evaluate our proposed framework.

Keywords: sustainability; air pollution; Multiple Criteria Decision Making (MCDM); TOPSIS; neural network (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (22)

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