An integrated deep learning framework enables rapid spatiotemporal morphodynamic predictions toward long-term simulations
<p>Physics-based morphodynamic modeling is essential for advancing river management science and understanding Earth's geomorphological evolution processes. However, their computational demands and long processing times hinder long-term applications. This paper introduces and tests a robust Deep Lear...
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| Автори: | , , , , , , |
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| Формат: | Artigo |
| Мова: | Inglês |
| Опубліковано: |
Copernicus Publications
2026-04-01
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| Серія: | Earth Surface Dynamics |
| Онлайн доступ: | https://esurf.copernicus.org/articles/14/313/2026/esurf-14-313-2026.pdf |
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