Flood Susceptibility Mapping Using Information Fusion Paradigm Integrated with Decision Trees
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DOI: 10.1007/s11269-024-03918-5
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- Hüseyin Akay, 2022. "Towards Linking the Sustainable Development Goals and a Novel-Proposed Snow Avalanche Susceptibility Mapping," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(15), pages 6205-6222, December.
- Huchang Liao & Zeshui Xu & Meimei Xia, 2014. "Multiplicative Consistency Of Hesitant Fuzzy Preference Relation And Its Application In Group Decision Making," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 13(01), pages 47-76.
- Karim Solaimani & Fatemeh Shokrian & Shadman Darvishi, 2023. "An Assessment of the Integrated Multi-Criteria and New Models Efficiency in Watershed Flood Mapping," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(1), pages 403-425, January.
- Manish Singh Rana & Chandan Mahanta, 2023. "Spatial prediction of flash flood susceptible areas using novel ensemble of bivariate statistics and machine learning techniques for ungauged region," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 115(1), pages 947-969, January.
- Yangfan Xiao & Shanzhen Yi & Zhongqian Tang, 2018. "A Spatially Explicit Multi-Criteria Analysis Method on Solving Spatial Heterogeneity Problems for Flood Hazard Assessment," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(10), pages 3317-3335, August.
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Keywords
Flood susceptibility mapping; Information fusion; Decision tree; Kocanaz watershed;All these keywords.
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