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dc.contributor.authorDuan, Yanan
dc.contributor.authorAkula, Sathish
dc.contributor.authorKumar, Sanjiv
dc.contributor.authorLee, Wonjun
dc.contributor.authorKhajehei, Sepideh
dc.date.accessioned2024-12-24T14:19:50Z
dc.date.available2024-12-24T14:19:50Z
dc.date.copyright01 Jan. 2023
dc.date.issued2023
dc.identifier.otheraies-AIES-D-22-0023.1.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4300555
dc.languageEnglish
dc.publisherAmerican Meteorological Society
dc.titleA Hybrid Physics–AI Model to Improve Hydrological Forecasts
dc.typeJournal Paper
dc.journal.volume2
dc.journal.issue1
dc.journal.titleArtificial Intelligence for the Earth Systems
dc.identifier.doi10.1175/AIES-D-22-0023.1
dc.journal.lastpagee220023
dc.treeArtificial Intelligence for the Earth Systems:;2023:;volume( 002 ):;issue: 001
dc.contenttypeFulltext


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