Predicting maximum scour depth at sluice outlet: a comparative study of machine learning models and empirical equations

Estimating the maximum scour depth of sluice outlets is pivotal in hydrological engineering, directly influencing the safety and efficiency of water infrastructure. This research compared traditional empirical formulas with advanced machine learning (ML) algorithms, including RID, SVM, CAT, and XGB,...

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Dades bibliogràfiques
Autors principals: Xuan-Hien Le, Le Thi Thu Hien
Format: Article
Idioma:English
Publicat: IOP Publishing 2024-01-01
Col·lecció:Environmental Research Communications
Matèries:
Accés en línia:https://doi.org/10.1088/2515-7620/ad1f94