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Ju-Young Shin
Ju-Young Shin
School of Civil and Environmental Engineering, Kookmin University
Verified email at kookmin.ac.kr
Title
Cited by
Cited by
Year
Probability distributions of wind speed in the UAE
TBMJ Ouarda, C Charron, JY Shin, PR Marpu, AH Al-Mandoos, ...
Energy conversion and management 93, 414-434, 2015
2372015
Probability distributions for a quantile mapping technique for a bias correction of precipitation data: A case study to precipitation data under climate change
JH Heo, H Ahn, JY Shin, TR Kjeldsen, C Jeong
Water 11 (7), 1475, 2019
952019
Heterogeneous mixture distributions for modeling wind speed, application to the UAE
JY Shin, TBMJ Ouarda, T Lee
Renewable Energy 91, 40-52, 2016
742016
Monthly precipitation forecasting with a neuro-fuzzy model
C Jeong, JY Shin, T Kim, JH Heo
Water resources management 26, 4467-4483, 2012
632012
Deep learning-based maximum temperature forecasting assisted with meta-learning for hyperparameter optimization
T Thi Kieu Tran, T Lee, JY Shin, JS Kim, M Kamruzzaman
Atmosphere 11 (5), 487, 2020
622020
Identification of relationships between climate indices and long-term precipitation in South Korea using ensemble empirical mode decomposition
T Kim, JY Shin, S Kim, JH Heo
Journal of Hydrology 557, 726-739, 2018
562018
Stochastic simulation on reproducing long-term memory of hydroclimatological variables using deep learning model
T Lee, JY Shin, JS Kim, VP Singh
Journal of Hydrology 582, 124540, 2020
492020
Spatial and temporal variations in rainfall erosivity and erosivity density in South Korea
JY Shin, T Kim, JH Heo, JH Lee
Catena 176, 125-144, 2019
422019
Seasonal forecasting of daily mean air temperatures using a coupled global climate model and machine learning algorithm for field-scale agricultural management
JY Shin, KR Kim, JC Ha
Agricultural and Forest Meteorology 281, 107858, 2020
392020
Meta-heuristic maximum likelihood parameter estimation of the mixture normal distribution for hydro-meteorological variables
JY Shin, JH Heo, C Jeong, T Lee
Stochastic environmental research and risk assessment 28, 347-358, 2014
372014
The use of large-scale climate indices in monthly reservoir inflow forecasting and its application on time series and artificial intelligence models
T Kim, JY Shin, H Kim, S Kim, JH Heo
Water 11 (2), 374, 2019
352019
Allergenic pollen calendar in Korea based on probability distribution models and up-to-date observations
JY Shin, MJ Han, C Cho, KR Kim, JC Ha, JW Oh
Allergy, asthma & immunology research 12 (2), 259-273, 2020
332020
Heterogeneous mixture distributions for modeling multisource extreme rainfalls
JY Shin, T Lee, TBMJ Ouarda
Journal of Hydrometeorology 16 (6), 2639-2657, 2015
312015
Regional quantile delta mapping method using regional frequency analysis for regional climate model precipitation
S Kim, K Joo, H Kim, JY Shin, JH Heo
Journal of Hydrology 596, 125685, 2021
282021
The spatial and temporal structure of extreme rainfall trends in South Korea
Y Jung, JY Shin, H Ahn, JH Heo
Water 9 (10), 809, 2017
232017
Ensemble‐based neural network modeling for hydrologic forecasts: Addressing uncertainty in the model structure and input variable selection
T Kim, JY Shin, H Kim, JH Heo
Water Resources Research 56 (6), e2019WR026262, 2020
222020
A new approach for river network classification based on the beta distribution of tributary junction angles
K Jung, JY Shin, D Park
Journal of Hydrology 572, 66-74, 2019
222019
Bias correction of RCM outputs using mixture distributions under multiple extreme weather influences
JY Shin, T Lee, T Park, S Kim
Theoretical and Applied Climatology 137 (1), 201-216, 2019
202019
A novel statistical method to temporally downscale wind speed Weibull distribution using scaling property
JY Shin, C Jeong, JH Heo
Energies 11 (3), 633, 2018
182018
Long‐term trend and variability of surface humidity from 1973 to 2018 in South Korea
JY Shin, KR Kim, J Kim, S Kim
International Journal of Climatology 41 (8), 4215-4235, 2021
162021
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