Flood susceptibility mapping and assessment using a novel deep learning model combining multilayer perceptron and autoencoder neural networks

Author:

Ahmadlou Mohammad1,Al‐Fugara A'kif2,Al‐Shabeeb Abdel Rahman3,Arora Aman4,Al‐Adamat Rida3,Pham Quoc Bao56,Al‐Ansari Nadhir7,Linh Nguyen Thi Thuy89,Sajedi Hedieh10

Affiliation:

1. GIS Department, Geodesy and Geomatics Faculty K. N. Toosi University of Technology Tehran Iran

2. Department of Surveying Engineering, Faculty of Engineering Al al‐Bayt University Mafraq Jordan

3. Department of GIS and Remote Sensing, Institute of Earth and Environmental Sciences Al al‐Bayt University Mafraq Jordan

4. Department of Geography, Faculty of Natural Sciences New Delhi India

5. Environmental Quality, Atmospheric Science and Climate Change Research Group Ton Duc Thang University Ho Chi Minh City Vietnam

6. Faculty of Environment and Labour Safety Ton Duc Thang University Ho Chi Minh City Vietnam

7. Department of Civil, Environmental and Natural Resources Engineering Lulea University of Technology 97187, Lulea Sweden

8. Institute of Research and Development Duy Tan University Danang 550000 Vietnam

9. Faculty of Environmental and Chemical Engineering Duy Tan University Danang 550000 Vietnam

10. Department of Computer Science, School of Mathematics, Statistics and Computer Science, College of Science University of Tehran Tehran Iran

Publisher

Wiley

Subject

Water Science and Technology,Safety, Risk, Reliability and Quality,Geography, Planning and Development,Environmental Engineering

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