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전체 가 나 다 라 마 바 사 아 자 차 카 타 파 하

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Bias correction of RCM outputs using mixture distributions under multiple extreme weather influences

Shin, Ju-Young; Lee, Taesam; Park, Taewoong; Kim, Sangdan

ArticleIssue Date2019CitationTheorectical and Applied Climatology, v.137, no.1-2, pp 201 - 216PublisherSpringer Verlag
SCIESCOPUS
Deep Learning-Based Maximum Temperature Forecasting Assisted with Meta-Learning for Hyperparameter Optimizationopen access

Tran, Trang Thi Kieu; Lee, Taesam; Shin, Ju-Young; Kim, Jong-Suk; Kamruzzaman, Mohamad

ArticleIssue Date2020CitationATMOSPHERE, v.11, no.5PublisherMDPI
SCIESCOPUS
Heterogeneous Mixture Distributions for Modeling Multisource Extreme Rainfallsopen access

Shin, Ju-Young; Lee, Taesam; Ouarda, Taha B. M. J.

ArticleIssue Date2015CitationJOURNAL OF HYDROMETEOROLOGY, v.16, no.6, pp 2639 - 2657PublisherAMER METEOROLOGICAL SOC
SCIESCOPUS
Heterogeneous mixture distributions for modeling wind speed, application to the UAE

Shin, Ju-Young; Ouarda, Taha B. M. J.; Lee, Taesam

ArticleIssue Date2016CitationRENEWABLE ENERGY, v.91, pp 40 - 52PublisherPERGAMON-ELSEVIER SCIENCE LTD
SCISCIESCOPUS
Meta-heuristic maximum likelihood parameter estimation of the mixture normal distribution for hydro-meteorological variables

Shin, Ju-Young; Heo, Jun-Haeng; Jeong, Changsam; Lee, Taesam

ArticleIssue Date2014CitationSTOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, v.28, no.2, pp 347 - 358PublisherSPRINGER
SCIESCOPUS
Stochastic simulation on reproducing long-term memory of hydroclimatological variables using deep learning model

Lee, Taesam; Shin, Ju-Young; Kim, Jong-Suk; Singh, Vijay P.

ArticleIssue Date2020CitationJournal of Hydrology, v.582PublisherElsevier BV
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