Treffer: An innovative ensemble approach of deep learning models with soft computing techniques for GIS-based drought-zonation mapping in Rarh Region, West Bengal.

An innovative ensemble approach of deep learning models with soft computing techniques for GIS-based drought-zonation mapping in Rarh Region, West Bengal.

Chowdhury G; Department of Geography, Delhi School of Economics, University of Delhi, Delhi, India. gopalchowdhury989@gmail.com., Mandal S; Department of Geography, Delhi School of Economics, University of Delhi, Delhi, India., Saha AK; Department of Geography, Delhi School of Economics, University of Delhi, Delhi, India.

Environmental science and pollution research international [Environ Sci Pollut Res Int] 2025 Jun; Vol. 32 (27), pp. 16295-16323. Date of Electronic Publication: 2025 Jun 25.

Journal Article

English

Publisher: Springer Country of Publication: Germany NLM ID: 9441769 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1614-7499 (Electronic) Linking ISSN: 09441344 NLM ISO Abbreviation: Environ Sci Pollut Res Int Subsets: MEDLINE

Publication: <2013->: Berlin : Springer
Original Publication: Landsberg, Germany : Ecomed

Deep Learning* , Droughts* , Geographic Information Systems*, India ; Neural Networks, Computer ; Agriculture ; Soft Computing

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Keywords: Drought proneness Rarh region; Hybrid deep learning ensemble; Machine learning; SPI

Date Created: 20250625 Date Completed: 20250718 Latest Revision: 20250718

20250718

10.1007/s11356-025-36634-7

40560313

MEDLINE