Improving Seasonal Prediction of Summer Precipitation in the Middle–Lower Reaches of the Yangtze River Using a TU-Net Deep Learning ApproachSource: Artificial Intelligence for the Earth Systems:;2023:;volume( 002 ):;issue: 002DOI: 10.1175/AIES-D-22-0078.1Publisher: American Meteorological Society
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| contributor author | Yang, Shuxian | |
| contributor author | Ling, Fenghua | |
| contributor author | Li, Yue | |
| contributor author | Luo, Jing-Jia | |
| date accessioned | 2024-12-24T15:00:00Z | |
| date available | 2024-12-24T15:00:00Z | |
| date copyright | 01 Apr. 2023 | |
| date issued | 2023 | |
| identifier other | aies-AIES-D-22-0078.1.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4301660 | |
| language | English | |
| publisher | American Meteorological Society | |
| title | Improving Seasonal Prediction of Summer Precipitation in the Middle–Lower Reaches of the Yangtze River Using a TU-Net Deep Learning Approach | |
| type | Journal Paper | |
| journal volume | 2 | |
| journal issue | 2 | |
| journal title | Artificial Intelligence for the Earth Systems | |
| identifier doi | 10.1175/AIES-D-22-0078.1 | |
| journal lastpage | 220078 | |
| tree | Artificial Intelligence for the Earth Systems:;2023:;volume( 002 ):;issue: 002 | |
| contenttype | Fulltext |