| 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 | 259 | 2015 |
| 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 | 118 | 2019 |
| Heterogeneous mixture distributions for modeling wind speed, application to the UAE JY Shin, TBMJ Ouarda, T Lee Renewable Energy 91, 40-52, 2016 | 80 | 2016 |
| 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 | 76 | 2020 |
| Monthly precipitation forecasting with a neuro-fuzzy model C Jeong, JY Shin, T Kim, JH Heo Water resources management 26, 4467-4483, 2012 | 66 | 2012 |
| 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 | 63 | 2020 |
| 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 | 60 | 2018 |
| 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 | 54 | 2020 |
| 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 | 53 | 2019 |
| 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 | 45 | 2019 |
| 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 | 44 | 2021 |
| 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 | 39 | 2020 |
| 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 | 37 | 2014 |
| Heterogeneous mixture distributions for modeling multisource extreme rainfalls JY Shin, T Lee, TBMJ Ouarda Journal of hydrometeorology 16 (6), 2639-2657, 2015 | 33 | 2015 |
| 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 | 30 | 2020 |
| 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 | 30 | 2019 |
| 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 | 25 | 2017 |
| 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 | 24 | 2019 |
| 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 | 23 | 2018 |
| Regional frequency analysis of extreme precipitation based on a nonstationary population index flood method H Kim, JY Shin, T Kim, S Kim, JH Heo Advances in Water Resources 146, 103757, 2020 | 20 | 2020 |
Taesam LeeProfessor of Civil Engineering, Gyeongsang National UniversityE-mailová adresa ověřena na: gnu.ac.kr
