Adaptive neuro‐fuzzy inference system approach for urban sustainability assessment: A China case study

Urbanization, especially in developing countries, has led to numerous concerns, such as air pollution, traffic congestion and habitat destruction. Within this context, it is important to evaluate urban development as sustainable, and various sustainability assessment methods have been developed, inc...

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Published inSustainable development (Bradford, West Yorkshire, England) Vol. 26; no. 6; pp. 749 - 764
Main Authors Tan, Yongtao, Shuai, Chenyang, Jiao, Liudan, Shen, Liyin
Format Journal Article
LanguageEnglish
Published Chichester Wiley Periodicals Inc 01.11.2018
Subjects
Adaptive systems
Air pollution
ANFIS
artificial neural network
Case studies
Cities
decision‐making
Developing countries
Environmental degradation
Evaluation
Experts
Fuzzy logic
Fuzzy systems
Habitat loss
Inference
LDCs
Membership
Sustainability
Sustainable development
Traffic
Traffic congestion
Training
Urban development
urban sustainability
Urbanization
China
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Summary:Urbanization, especially in developing countries, has led to numerous concerns, such as air pollution, traffic congestion and habitat destruction. Within this context, it is important to evaluate urban development as sustainable, and various sustainability assessment methods have been developed, including fuzzy logic approaches. However, predefined fuzzy rules and simple linear membership functions were used, which are largely based on the knowledge of subject experts. Therefore, this paper aims to introduce an adaptive neuro‐fuzzy inference systems (ANFIS) approach for urban sustainability assessment. With collected training samples from the Urban China Initiative, and the ANFIS approach was used to rank 185 selected cities in China. The results show that the ANFIS approach is appropriate for assessing urban sustainability, and the nonlinear membership functions fit the training samples better than the linear membership functions. Further discussion indicates that future research on sustainability assessment should be more integrated.
Bibliography:ObjectType-Case Study-2
SourceType-Scholarly Journals-1
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ISSN:0968-0802
1099-1719
DOI:10.1002/sd.1744