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...
Enregistré dans:
| Auteurs principaux: | , , , , , , |
|---|---|
| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
Copernicus Publications
2026-04-01
|
| Collection: | Earth Surface Dynamics |
| Accès en ligne: | https://esurf.copernicus.org/articles/14/313/2026/esurf-14-313-2026.pdf |
| Tags: |
Pas de tags, Soyez le premier à ajouter un tag!
|