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Forecasting Sediment Accumulation in the Southwest Pass with Machine-Learning Models
| 题名： | Forecasting Sediment Accumulation in the Southwest Pass with Machine-Learning Models |
| 正文语种： | eng |
| 作者： | Magdalena Asborno;Jacob Broders;Kenneth N. Mitchell;Michael A. Hartman;Lauren D. Dunkin |
| 作者单位： | Applied Research Associates Inc. for Coastal and Hydraulics Laboratory U.S. Army Engineer Research and Development Center 3909 Halls Ferry Rd. Vicksburg MS 39180;Inc. 119 Monument PL Vicksburg MS 39180;Coastal and Hydraulics Laboratory U.S. Army |
| 关键词： | Waterways; Sediment; Dredging; Machine learning; Timeseries; Multivariate forecasting |
| 摘要： | Connecting the Mississippi River and the Gulf of Mexico, the Southwest Pass (SWP) is one of the most highly utilized commercial waterways in the United States. Hard-to-predict accumulation of sediments in the SWP affects the access of deep-draft vessels t |
| 出版年： | 2024 |
| 期刊名称： | Journal of Waterway, Port, Coastal and Ocean Engineering |
| 卷： | 150 |
| 期： | 2 |
| 页码： | 04023022.1-04023022.13 |
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