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contributor authorSung, Jiyoung
contributor authorJang, Sunghyuk
contributor authorKim, Taehyeong
contributor authorKang, Boosik
date accessioned2026-08-20T11:06:52Z
date available2026-08-20T11:06:52Z
date copyright2025/12/13
date issued2026
identifier otherJHYEFF.HEENG-6608.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4311711
description abstractAbstractAccurate flood forecasting is crucial for effective reservoir operations and flood protection. This study examines the effectiveness of long short-term memory (LSTM) surrogate models in forecasting flood inflows at the Namgang multipurpose dam in ...Practical ApplicationsThis study demonstrates the application of advanced DL models, particularly ConvLSTM, to improve flood inflow prediction at the Namgang multipurpose dam in South Korea. The methodology integrates the strengths of traditional ...
publisherAmerican Society of Civil Engineers
titleConvLSTM-Based Surrogate Modeling for Flood Inflow Prediction at Namgang Dam
typeJournal Article
journal volume31
journal issue1
journal titleJournal of Hydrologic Engineering
identifier doi10.1061/JHYEFF.HEENG-6608
journal fristpage04025056-1
journal lastpage04025056-15
page15
treeJournal of Hydrologic Engineering:;2026:;Volume ( 031 ):;issue: 001
contenttypeFulltext


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