Coupling Fuzzy Multi-Criteria Decision-Making and Clustering Algorithm for MSW Landfill Site Selection (Case Study: Lanzhou, China)
| Autor: | Jizong Jiao, Bin Xiao, Yueshi Li, Jiamin Liu |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Geography (General)
DEMATEL-ANP 010504 meteorology & atmospheric sciences Computer science Geography Planning and Development Delphi method Site selection TOPSIS 010501 environmental sciences Multiple-criteria decision analysis computer.software_genre 01 natural sciences Fuzzy logic site selection Weighting Earth and Planetary Sciences (miscellaneous) G1-922 Data mining fuzzy logic Computers in Earth Sciences Cluster analysis computer Reliability (statistics) 0105 earth and related environmental sciences clustering |
| Zdroj: | ISPRS International Journal of Geo-Information, Vol 10, Iss 403, p 403 (2021) ISPRS International Journal of Geo-Information Volume 10 Issue 6 |
| ISSN: | 2220-9964 |
| Popis: | The siting of Municipal Solid Waste (MSW) landfills is a complex decision process. Existing siting methods utilize expert scores to determine criteria weights, however, they ignore the uncertainty of data and criterion weights and the efficacy of results. In this study, a coupled fuzzy Multi-Criteria Decision-Making (MCDM) approach was employed to site landfills in Lanzhou, a semi-arid valley basin city in China, to enhance the spatial decision-making process. Primarily, 21 criteria were identified in five groups through the Delphi method at 30 m resolution, then criteria weights were obtained by DEMATEL and ANP, and the optimal fuzzy membership function was determined for each evaluation criterion. Combined with GIS spatial analysis and the clustering algorithm, candidate sites that satisfied the landfill conditions were identified, and the spatial distribution characteristics were analyzed. These sites were subsequently ranked utilizing the MOORA, WASPAS, COPRAS, and TOPSIS methods to verify the reliability of the results by conducting sensitivity analysis. This study is different from the previous research that applied the MCDM approach in that fuzzy MCDM for weighting criteria is more reliable compared to the other common methods. |
| Databáze: | OpenAIRE |
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