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Youngmin Park, Euihyun Kim, Youngjin Choi, Gwangho Seo, Youngtaeg Kim and Hokyun Kim
Typhoon attacks on the Korean Peninsula have recently become more frequent, and the strength of these typhoons is also gradually increasing because of climate change. Typhoon attacks cause storm surges in coastal regions; therefore, forecasts that enable...
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Youngmin Seo, Soonmyeong Kwon and Yunyoung Choi
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Youngmin Seo, Soonmyeong Kwon and Yunyoung Choi
Accurate water demand forecasting is essential to operate urban water supply facilities efficiently and ensure water demands for urban residents. This study proposes an extreme learning machine (ELM) coupled with variational mode decomposition (VMD) for ...
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Youngmin Seo, Yunyoung Choi, Jeongwoo Choi
Pág. 1 - 24
This paper proposes a river stage modeling approach combining maximal overlap discrete wavelet transform (MODWT), support vector machines (SVMs) and genetic algorithm (GA). The MODWT decomposes original river stage time series into sub-time series (detai...
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Youngmin Seo, Yunyoung Choi and Jeongwoo Choi
This paper proposes a river stage modeling approach combining maximal overlap discrete wavelet transform (MODWT), support vector machines (SVMs) and genetic algorithm (GA). The MODWT decomposes original river stage time series into sub-time series (detai...
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Mohammad Zounemat-Kermani, Youngmin Seo, Sungwon Kim, Mohammad Ali Ghorbani, Saeed Samadianfard, Shabnam Naghshara, Nam Won Kim and Vijay P. Singh
This study evaluates standalone and hybrid soft computing models for predicting dissolved oxygen (DO) concentration by utilizing different water quality parameters. In the first stage, two standalone soft computing models, including multilayer perceptron...
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