Sungwon Kim
Sungwon Kim
Dongyang University
Verified email at - Homepage
Cited by
Cited by
Neural networks and genetic algorithm approach for nonlinear evaporation and evapotranspiration modeling
S Kim, HS Kim
Journal of Hydrology 351 (3-4), 299-317, 2008
Daily water level forecasting using wavelet decomposition and artificial intelligence techniques
Y Seo, S Kim, O Kisi, VP Singh
Journal of Hydrology 520, 224-243, 2015
Pan evaporation modeling using neural computing approach for different climatic zones
S Kim, J Shiri, O Kisi
Water resources management 26 (11), 3231-3249, 2012
Estimating daily pan evaporation using different data-driven methods and lag-time patterns
S Kim, J Shiri, O Kisi, VP Singh
Water resources management 27 (7), 2267-2286, 2013
Estimating daily reference evapotranspiration using available and estimated climatic data by adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN)
A Pour-Ali Baba, J Shiri, O Kisi, AF Fard, S Kim, R Amini
Hydrology Research 44 (1), 131-146, 2013
Modeling daily soil temperature using data-driven models and spatial distribution
S Kim, VP Singh
Theoretical and applied climatology 118 (3), 465-479, 2014
Shear strength prediction of steel fiber reinforced concrete beam using hybrid intelligence models: a new approach
ZM Yaseen, MT Tran, S Kim, T Bakhshpoori, RC Deo
Engineering Structures 177, 244-255, 2018
Novel hybrid data-intelligence model for forecasting monthly rainfall with uncertainty analysis
ZM Yaseen, I Ebtehaj, S Kim, H Sanikhani, H Asadi, MI Ghareb, ...
Water 11 (3), 502, 2019
Estimation of daily dew point temperature using genetic programming and neural networks approaches
J Shiri, S Kim, O Kisi
Hydrology Research 45 (2), 165-181, 2014
Predicting daily pan evaporation by soft computing models with limited climatic data
S Kim, J Shiri, VP Singh, O Kisi, G Landeras
Hydrological Sciences Journal 60 (6), 1120-1136, 2015
Uncertainty Reduction of the Flood Stage Forecasting Using Neural Networks Model1
S Kim, HS Kim
JAWRA Journal of the American Water Resources Association 44 (1), 148-165, 2008
Estimating spatial precipitation using regression kriging and artificial neural network residual kriging (RKNNRK) hybrid approach
Y Seo, S Kim, VP Singh
Water Resources Management 29 (7), 2189-2204, 2015
Soft computing techniques for rainfall-runoff simulation: local non–parametric paradigm vs. model classification methods
M Rezaie-Balf, Z Zahmatkesh, S Kim
Water Resources Management 31 (12), 3843-3865, 2017
Estimation of dew point temperature using neuro-fuzzy and neural network techniques
O Kisi, S Kim, J Shiri
Theoretical and Applied Climatology 114 (3), 365-373, 2013
River stage forecasting using wavelet packet decomposition and machine learning models
Y Seo, S Kim, O Kisi, VP Singh, K Parasuraman
Water Resources Management 30 (11), 4011-4035, 2016
Drought forecasting using novel heuristic methods in a semi-arid environment
O Kisi, AD Gorgij, M Zounemat-Kermani, A Mahdavi-Meymand, S Kim
Journal of Hydrology 578, 124053, 2019
Daily river flow forecasting using ensemble empirical mode decomposition based heuristic regression models: Application on the perennial rivers in Iran and South Korea
M Rezaie-Balf, S Kim, H Fallah, S Alaghmand
Journal of Hydrology 572, 470-485, 2019
Modeling monthly pan evaporation process over the Indian central Himalayas: Application of multiple learning artificial intelligence model
A Malik, A Kumar, S Kim, MH Kashani, V Karimi, A Sharafati, MA Ghorbani, ...
Engineering Applications of Computational Fluid Mechanics 14 (1), 323-338, 2020
Modelling daily reference evapotranspiration in humid locations of South Korea using local and cross‐station data management scenarios
S Karimi, O Kisi, S Kim, AH Nazemi, J Shiri
International Journal of Climatology 37 (7), 3238-3246, 2017
Machine learning models coupled with variational mode decomposition: A new approach for modeling daily rainfall-runoff
Y Seo, S Kim, VP Singh
Atmosphere 9 (7), 251, 2018
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