A novel voting ensemble model empowered by metaheuristic feature selection for accurate flash flood susceptibility mapping

A novel voting ensemble model empowered by metaheuristic feature selection for accurate flash flood susceptibility mapping

This study addresses the challenges of flash flood susceptibility mapping in Yemen’s Qaa’Jahran Basin, characterized by complex terrain and limited hydro-meteorological data. To enhance predictive accuracy, we integrate metaheuristic feature selection with ensemble learning models. Initially, fiftee...

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Bibliographic Details
Main Authors: Radhwan A. Saleh, Ahmed M. Al-Areeq, Amran A. Al Aghbari, Mustafa Ghaleb, Mohammed Benaafi, Nabil M. Al‑Areeq, Baqer M. Al-Ramadan
Format: Article
Language:English
Published: Taylor & Francis Group 2024-12-01
Series:Geomatics, Natural Hazards & Risk
Subjects:
Remote sensing
feature selection
deep learning
flash flood
Qaa’Jahran
Online Access:https://www.tandfonline.com/doi/10.1080/19475705.2024.2360000
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https://www.tandfonline.com/doi/10.1080/19475705.2024.2360000

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