| dc.contributor.author | Vazirian, Roya | |
| dc.date.accessioned | 2026-08-20T11:07:15Z | |
| dc.date.available | 2026-08-20T11:07:15Z | |
| dc.date.copyright | 2026/05/07 | |
| dc.date.issued | 2026 | |
| dc.identifier.other | JHYEFF.HEENG-6651.pdf | |
| dc.identifier.uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4311720 | |
| dc.description.abstract | AbstractArtificial intelligence, particularly deep learning, is transforming discharge forecasting
to address climate challenges and enhance water management by capturing complex, nonlinear,
long-term dependencies. This study provides a process-based ... | |
| dc.publisher | American Society of Civil Engineers | |
| dc.title | Deep Learning–Based Streamflow Forecasting in a Snowmelt-Dominated Basin: A Regime-Aware Evaluation | |
| dc.type | Journal Article | |
| dc.journal.volume | 31 | |
| dc.journal.issue | 4 | |
| dc.journal.title | Journal of Hydrologic Engineering | |
| dc.identifier.doi | 10.1061/JHYEFF.HEENG-6651 | |
| dc.journal.fristpage | 04026012-1 | |
| dc.journal.lastpage | 04026012-8 | |
| dc.page | 8 | |
| dc.tree | Journal of Hydrologic Engineering:;2026:;Volume ( 031 ):;issue: 004 | |
| dc.contenttype | Fulltext | |
