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