| contributor author | Fang, Xin | |
| contributor author | Li, Heng | |
| contributor author | Zhang, Sherong | |
| contributor author | Liu, Kang | |
| contributor author | Wang, Xiaohua | |
| contributor author | Wang, Chao | |
| date accessioned | 2026-08-20T21:24:15Z | |
| date available | 2026-08-20T21:24:15Z | |
| date copyright | 2025/09/27 | |
| date issued | 2026 | |
| identifier other | JCCEE5.CPENG-6533.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4314396 | |
| description abstract | AbstractExtreme climate events are becoming increasingly frequent, and flood disasters have
been one of the most frequent and devastating forms of such events, threatening the
lives and property of coastal residents. To reduce the potential costs to ...Practical ApplicationsThe hybrid model developed in this study has significant practical implications for
flood risk management and emergency response. By integrating hydrodynamic analysis
with advanced deep learning techniques, the model enables real-... | |
| publisher | American Society of Civil Engineers | |
| title | Integrating Hydrodynamic Mechanisms and Deep Learning for Real-Time Flood Inundation Forecasting | |
| type | Journal Article | |
| journal volume | 40 | |
| journal issue | 1 | |
| journal title | Journal of Computing in Civil Engineering | |
| identifier doi | 10.1061/JCCEE5.CPENG-6533 | |
| journal fristpage | 04025121-1 | |
| journal lastpage | 04025121-15 | |
| page | 15 | |
| tree | Journal of Computing in Civil Engineering:;2026:;Volume ( 040 ):;issue: 001 | |
| contenttype | Fulltext | |