Integrating machine learning and empirical approaches for scour depth estimation at sluice gates: evaluating tree-based models, hyperparameter tuning, and proposing new formulas
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| Format: | Article |
| Language: | English |
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Sciendo
2025-03-01
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| Series: | Journal of Hydrology and Hydromechanics |
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| Online Access: | https://doi.org/10.2478/johh-2025-0004 |
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| _version_ | 1850253108116979712 |
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| author | Le Xuan-Hien Hien Le Thi Thu |
| author_facet | Le Xuan-Hien Hien Le Thi Thu |
| author_sort | Le Xuan-Hien |
| collection | DOAJ |
| description | Abstract: |
| format | Article |
| id | doaj-art-3d23c0177fad48c29067e29879cd50ef |
| institution | OA Journals |
| issn | 1338-4333 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Journal of Hydrology and Hydromechanics |
| spelling | doaj-art-3d23c0177fad48c29067e29879cd50ef2025-08-20T01:57:28ZengSciendoJournal of Hydrology and Hydromechanics1338-43332025-03-01731516410.2478/johh-2025-0004Integrating machine learning and empirical approaches for scour depth estimation at sluice gates: evaluating tree-based models, hyperparameter tuning, and proposing new formulasLe Xuan-Hien0Hien Le Thi Thu11Faculty of Water Resources Engineering, Thuyloi University, 175 Tay Son, Dong Da, Hanoi 10000, Vietnam.1Faculty of Water Resources Engineering, Thuyloi University, 175 Tay Son, Dong Da, Hanoi 10000, Vietnam.Abstract:https://doi.org/10.2478/johh-2025-0004extra trees (ert)histogram-based gradient boosting (hgb)hyperparameter tuningparticle swarm optimization (pso)scour depth estimationtree-structured parzen estimator (tpe) |
| spellingShingle | Le Xuan-Hien Hien Le Thi Thu Integrating machine learning and empirical approaches for scour depth estimation at sluice gates: evaluating tree-based models, hyperparameter tuning, and proposing new formulas Journal of Hydrology and Hydromechanics extra trees (ert) histogram-based gradient boosting (hgb) hyperparameter tuning particle swarm optimization (pso) scour depth estimation tree-structured parzen estimator (tpe) |
| title | Integrating machine learning and empirical approaches for scour depth estimation at sluice gates: evaluating tree-based models, hyperparameter tuning, and proposing new formulas |
| title_full | Integrating machine learning and empirical approaches for scour depth estimation at sluice gates: evaluating tree-based models, hyperparameter tuning, and proposing new formulas |
| title_fullStr | Integrating machine learning and empirical approaches for scour depth estimation at sluice gates: evaluating tree-based models, hyperparameter tuning, and proposing new formulas |
| title_full_unstemmed | Integrating machine learning and empirical approaches for scour depth estimation at sluice gates: evaluating tree-based models, hyperparameter tuning, and proposing new formulas |
| title_short | Integrating machine learning and empirical approaches for scour depth estimation at sluice gates: evaluating tree-based models, hyperparameter tuning, and proposing new formulas |
| title_sort | integrating machine learning and empirical approaches for scour depth estimation at sluice gates evaluating tree based models hyperparameter tuning and proposing new formulas |
| topic | extra trees (ert) histogram-based gradient boosting (hgb) hyperparameter tuning particle swarm optimization (pso) scour depth estimation tree-structured parzen estimator (tpe) |
| url | https://doi.org/10.2478/johh-2025-0004 |
| work_keys_str_mv | AT lexuanhien integratingmachinelearningandempiricalapproachesforscourdepthestimationatsluicegatesevaluatingtreebasedmodelshyperparametertuningandproposingnewformulas AT hienlethithu integratingmachinelearningandempiricalapproachesforscourdepthestimationatsluicegatesevaluatingtreebasedmodelshyperparametertuningandproposingnewformulas |