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Masroor, Md, Razavi-Termeh, Seyed Vahid, Rahaman, Md Hibjur, Choudhari, Pandurang, Kulimushi, Luc Cimusa, Sajjad, Haroon (2023) Adaptive neuro fuzzy inference system (ANFIS) machine learning algorithm for assessing environmental and socio-economic vulnerability to drought: a study in Godavari middle sub-basin, India. Stochastic Environmental Research and Risk Assessment, 37 (1) 233-259 doi:10.1007/s00477-022-02292-1

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Reference TypeJournal (article/letter/editorial)
TitleAdaptive neuro fuzzy inference system (ANFIS) machine learning algorithm for assessing environmental and socio-economic vulnerability to drought: a study in Godavari middle sub-basin, India
JournalStochastic Environmental Research and Risk Assessment
AuthorsMasroor, MdAuthor
Razavi-Termeh, Seyed VahidAuthor
Rahaman, Md HibjurAuthor
Choudhari, PandurangAuthor
Kulimushi, Luc CimusaAuthor
Sajjad, HaroonAuthor
Year2023 (January)Volume37
Issue1
PublisherSpringer Science and Business Media LLC
DOIdoi:10.1007/s00477-022-02292-1Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID15672626Long-form Identifiermindat:1:5:15672626:1
GUID0
Full ReferenceMasroor, Md, Razavi-Termeh, Seyed Vahid, Rahaman, Md Hibjur, Choudhari, Pandurang, Kulimushi, Luc Cimusa, Sajjad, Haroon (2023) Adaptive neuro fuzzy inference system (ANFIS) machine learning algorithm for assessing environmental and socio-economic vulnerability to drought: a study in Godavari middle sub-basin, India. Stochastic Environmental Research and Risk Assessment, 37 (1) 233-259 doi:10.1007/s00477-022-02292-1
Plain TextMasroor, Md, Razavi-Termeh, Seyed Vahid, Rahaman, Md Hibjur, Choudhari, Pandurang, Kulimushi, Luc Cimusa, Sajjad, Haroon (2023) Adaptive neuro fuzzy inference system (ANFIS) machine learning algorithm for assessing environmental and socio-economic vulnerability to drought: a study in Godavari middle sub-basin, India. Stochastic Environmental Research and Risk Assessment, 37 (1) 233-259 doi:10.1007/s00477-022-02292-1
In(2023, January) Stochastic Environmental Research and Risk Assessment Vol. 37 (1) Springer Science and Business Media LLC

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