Prediction of flood sensitivity based on Logistic Regression, eXtreme Gradient Boosting, and Random Forest modeling methods
© 2024 The Authors This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY 4.0), which permits copying, adaptation and redistribution, provided the original work is properly cited (http://creativecommons.org/licenses/by/4.0/).
Détails bibliographiques
| Publié dans: | Water science and technology : a journal of the International Association on Water Pollution Research. - 1986. - 89(2024), 10 vom: 01. Mai, Seite 2605-2624
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| Auteur principal: |
Wu, Ying
(Auteur) |
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| Autres auteurs: |
Zhang, Zhiming,
Qi, Xiaotian,
Hu, Wenhan,
Si, Shuai |
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| Format: | Article en ligne
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| Langue: | English |
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| Publié: |
2024
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| Accès à la collection: | Water science and technology : a journal of the International Association on Water Pollution Research
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| Sujets: | Journal Article
Logistic Regression (LR)
Random Forest (RF)
eXtreme Gradient Boosting (XGBoost)
flood sensitivity assessment |
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