Computational Machine Learning Approach for Flood Susceptibility Assessment Integrated with Remote Sensing and GIS Techniques from Jeddah, Saudi Arabia

Computational Machine Learning Approach for Flood Susceptibility Assessment Integrated with Remote Sensing and GIS Techniques from Jeddah, Saudi Arabia

Floods, one of the most common natural hazards globally, are challenging to anticipate and estimate accurately. This study aims to demonstrate the predictive ability of four ensemble algorithms for assessing flood risk. Bagging ensemble (BE), logistic model tree (LT), kernel support vector machine (...

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Bibliographic Details
Main Authors: Ahmed M. Al-Areeq, S. I. Abba, Mohamed A. Yassin, Mohammed Benaafi, Mustafa Ghaleb, Isam H. Aljundi
Format: Article
Language:English
Published: MDPI AG 2022-11-01
Series:Remote Sensing
Subjects:
artificial intelligence
flood
Saudi Arabia
machine learning
GIS
remote sensing
Online Access:https://www.mdpi.com/2072-4292/14/21/5515

Internet

https://www.mdpi.com/2072-4292/14/21/5515

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