Improved flood susceptibility mapping using a best first decision tree integrated with ensemble learning techniques

Improved flood susceptibility mapping using a best first decision tree integrated with ensemble learning techniques

Improving the accuracy of flood prediction and mapping is crucial for reducing damage resulting from flood events. In this study, we proposed and validated three ensemble models based on the Best First Decision Tree (BFT) and the Bagging (Bagging-BFT), Decorate (Bagging-BFT), and Random Subspace (RS...

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Bibliographic Details
Main Authors: Binh Thai Pham, Abolfazl Jaafari, Tran Van Phong, Hoang Phan Hai Yen, Tran Thi Tuyen, Vu Van Luong, Huu Duy Nguyen, Hiep Van Le, Loke Kok Foong
Format: Article
Language:English
Published: Elsevier 2021-05-01
Series:Geoscience Frontiers
Subjects:
Machine learning
Ensemble learners
Hybrid modeling
Online Access:http://www.sciencedirect.com/science/article/pii/S1674987120302450

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http://www.sciencedirect.com/science/article/pii/S1674987120302450

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