Flood susceptibility modeling in the urban watershed of Guwahati using improved metaheuristic-based ensemble machine learning algorithms
Author:
Affiliation:
1. Department of Geography, Faculty of Natural Sciences, Jamia Millia Islamia, New Delhi, India
2. Department of Electrical Engineering and Computer Science, Henry Samueli School of Engineering, University of California, Irvine, CA, USA
Funder
University Grants Commission
Maulana Azad National Fellowship
Publisher
Informa UK Limited
Subject
Water Science and Technology,Geography, Planning and Development
Link
https://www.tandfonline.com/doi/pdf/10.1080/10106049.2022.2066200
Reference99 articles.
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4. Global projections of river flood risk in a warmer world
5. GIS-based comparative assessment of flood susceptibility mapping using hybrid multi-criteria decision-making approach, naïve Bayes tree, bivariate statistics and logistic regression: A case of Topľa basin, Slovakia
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