A novel framework for addressing uncertainties in machine learning-based geospatial approaches for flood prediction-Reference-Cited by-同舟云学术

A novel framework for addressing uncertainties in machine learning-based geospatial approaches for flood prediction

Published:2023-01 Issue: Volume:326 Page:116813
ISSN:0301-4797
Container-title:Journal of Environmental Management
language:en
Short-container-title:Journal of Environmental Management

Author:

Adnan Mohammed Sarfaraz Gani^ORCID,Siam Zakaria Shams^ORCID,Kabir Irfat^ORCID,Kabir Zobaidul,Ahmed M. Razu^ORCID,Hassan Quazi K.,Rahman Rashedur M.^ORCID,Dewan Ashraf

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Waste Management and Disposal,General Medicine,Environmental Engineering

Reference87 articles.

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3. The potential of tidal river management for flood alleviation in south western Bangladesh;Adnan;Sci. Total Environ.,2020

4. Flood susceptibility mapping and assessment using a novel deep learning model combining multilayer perceptron and autoencoder neural networks;Ahmadlou;J. Flood Risk Manag.,2021

5. Evaluation of flood susceptibility mapping using logistic regression and GIS conditioning factors;Al-Juaidi;Arabian J. Geosci.,2018

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