Performance and uncertainty analysis in deep learning frameworks for streamflow forecasting via Monte Carlo dropout technique
Study Region: The research was conducted at the Red River Basin, Vietnam. Study Focus: This study evaluated the performance of six deep learning models (Standard LSTM (S_LSTM), Bidirectional LSTM (Bi_LSTM), LSTM with attention mechanism (At_LSTM), Advanced LSTM (Ad_LSTM), Temporal Convolutional Netw...
Gorde:
| Egile Nagusiak: | , , |
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| Formatua: | Artigo |
| Hizkuntza: | Inglês |
| Argitaratua: |
Elsevier
2025-10-01
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| Saila: | Journal of Hydrology: Regional Studies |
| Gaiak: | |
| Sarrera elektronikoa: | http://www.sciencedirect.com/science/article/pii/S2214581825004975 |
| Etiketak: |
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