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Optimization of state-of-the-art fuzzy-metaheuristic ANFIS-based machine learning models for flood susceptibility prediction mapping in the Middle Ganga Plain, India

dc.contributor.authorArora, Aman
dc.contributor.authorArabameri, Alireza
dc.contributor.authorPandey, Manish
dc.contributor.authorSiddiqui, Masood
dc.contributor.authorShukla, U.K.
dc.contributor.authorTien Bui, Dieu
dc.contributor.authorNarayan Mishra, Varun
dc.contributor.authorBhardwaj, Anshuman
dc.date.accessioned2021-08-12T23:08:23Z
dc.date.available2021-08-12T23:08:23Z
dc.date.issued2021-01-01
dc.identifier176584033
dc.identifier43f33197-e4fa-4d65-bcd2-3bd9fb79217b
dc.identifier85089944796
dc.identifier.citationArora , A , Arabameri , A , Pandey , M , Siddiqui , M , Shukla , U K , Tien Bui , D , Narayan Mishra , V & Bhardwaj , A 2021 , ' Optimization of state-of-the-art fuzzy-metaheuristic ANFIS-based machine learning models for flood susceptibility prediction mapping in the Middle Ganga Plain, India ' , Science of the Total Environment , vol. 750 , 141565 . https://doi.org/10.1016/j.scitotenv.2020.141565en
dc.identifier.issn0048-9697
dc.identifier.otherSCOPUS: 85089944796
dc.identifier.otherORCID: /0000-0002-2502-6384/work/82659746
dc.identifier.urihttps://hdl.handle.net/2164/16943
dc.descriptionCRediT authorship contribution statement: Dr. Aman Arora and Dr. Alireza Arabameri have conceptualized the study, prepared the dataset, and optimized the models. Dr. Manish Pandey has helped in writing the manuscript. Prof. Masood A. Siddiqui, Prof. U.K. Shukla, Prof. Dieu Tien Bui, Dr. Varun Narayan Mishra, and Dr. Anshuman Bhardwaj have helped in improving the manuscript at different stages of this work.en
dc.format.extent21
dc.format.extent3467437
dc.language.isoeng
dc.relation.ispartofScience of the Total Environmenten
dc.subjectSDG 15 - Life on Landen
dc.subjectFlood susceptibility mappingen
dc.subjectANFISen
dc.subjectGenetic algorithm (GA)en
dc.subjectDifferential evolution (DE)en
dc.subjectParticle swarm optimization (PSOen
dc.subjectMetaheuristic optimizationen
dc.subjectMiddle ganga plainen
dc.subjectParticle swarm optimization (PSO)en
dc.subjectQB Astronomyen
dc.subjectQ Scienceen
dc.subjectPollutionen
dc.subjectWaste Management and Disposalen
dc.subjectEnvironmental Engineeringen
dc.subjectEnvironmental Chemistryen
dc.subject.lccQBen
dc.subject.lccQen
dc.titleOptimization of state-of-the-art fuzzy-metaheuristic ANFIS-based machine learning models for flood susceptibility prediction mapping in the Middle Ganga Plain, Indiaen
dc.typeJournal articleen
dc.contributor.institutionUniversity of Aberdeen.Planetary Sciencesen
dc.contributor.institutionUniversity of Aberdeen.Cryosphere and Climate Change Research Groupen
dc.description.statusPeer revieweden
dc.identifier.doi10.1016/j.scitotenv.2020.141565
dc.date.embargoedUntil2021-08-13
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85089944796&partnerID=8YFLogxKen


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