Kyunghyun Kim

Ensemble Machine Learning of Gradient Boosting (XGBoost, LightGBM, CatBoost) and Attention-Based CNN-LSTM for Harmful Algal Blooms Forecasting

Jung Min Ahn, Jungwook Kim, Kyunghyun Kim · Toxins · 2023 · 137 citations · Full text

Computing, Computer Science, Data Science +17

Using convolutional neural network for predicting cyanobacteria concentrations in river water

JongCheol Pyo, Lan Joo Park, Yakov Pachepsky et al. · Water Research · 2020 · 118 citations

Natural Resources, Environmental Sciences, Hydrology +13

Prioritization of highly exposable pharmaceuticals via a suspect/non-target screening approach: A case study for Yeongsan River, Korea

Park Naree, Younghun Choi, Deokwon Kim et al. · The Science of The Total Environment · 2018 · 100 citations

Pharmacy, Pharmaceutical Analysis, Toxicology +14

Identification, quantification, and prioritization of new emerging pollutants in domestic and industrial effluents, Korea: Application of LC-HRMS based suspect and non-target screening

Younghun Choi, Jiho Lee, Kyunghyun Kim et al. · Journal of Hazardous Materials · 2020 · 98 citations

Natural Sciences, Environmental Engineering, Environmental Sciences +12

Cyanobacteria cell prediction using interpretable deep learning model with observed, numerical, and sensing data assemblage

JongCheol Pyo, Kyung Hwa Cho, Kyunghyun Kim et al. · Water Research · 2021 · 76 citations

Computing, Bioengineering, Microbiology +8