Hybrid XGboost model with various Bayesian hyperparameter optimization algorithms for flood hazard susceptibility modeling-Reference-Cited by-同舟云学术

Hybrid XGboost model with various Bayesian hyperparameter optimization algorithms for flood hazard susceptibility modeling

Published:2021-10-29 Issue: Volume: Page:1-20
ISSN:1010-6049
Container-title:Geocarto International
language:en
Short-container-title:Geocarto International

Author:

Janizadeh Saeid¹,Vafakhah Mehdi¹^ORCID,Kapelan Zoran²^ORCID,Mobarghaee Dinan Naghmeh³

Affiliation:

1. Department of Watershed Management Engineering and Sciences, Faculty of Natural Resources and Marine Sciences, Tarbiat Modares University, Tehran, Iran

2. Department of Water Management, Delft University of Technology, Delft, The Netherlands

3. Department of Environmental Planning and Design, Environmental Sciences Research Institute, Shahid Beheshti University, Tehran, Iran

Publisher

Informa UK Limited

Subject

Water Science and Technology,Geography, Planning and Development

Link

https://www.tandfonline.com/doi/pdf/10.1080/10106049.2021.1996641

Reference60 articles.

1. Multicollinearity

2. Modeling of gas hydrate phase equilibria: Extremely randomized trees and LSSVM approaches

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4. Modeling Flood Hazard Zones at the Sub-District Level with the Rational Model Integrated with GIS and Remote Sensing Approaches

5. Flash Flood Susceptibility Modeling Using New Approaches of Hybrid and Ensemble Tree-Based Machine Learning Algorithms

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