TaeHo Kim

An interpretable machine learning method for supporting ecosystem management: Application to species distribution models of freshwater macroinvertebrates

YoonKyung Cha, Jihoon Shin, ByeongGeon Go et al. · Journal of Environmental Management · 2021 · 105 citations

Species Distribution Models, Biodiversity, Engineering +7

Validity evaluation of a machine-learning model for chlorophyll a retrieval using Sentinel-2 from inland and coastal waters

Young Woo Kim, TaeHo Kim, Jihoon Shin et al. · Ecological Indicators · 2022 · 74 citations · Full text

Simultaneous feature engineering and interpretation: Forecasting harmful algal blooms using a deep learning approach

TaeHo Kim, Jihoon Shin, Doyeon Lee et al. · Water Research · 2022 · 59 citations

Convolutional Neural Network, Engineering, Machine Learning +8

Forecasting Abrupt Depletion of Dissolved Oxygen in Urban Streams Using Discontinuously Measured Hourly Time‐Series Data

Young Woo Kim, TaeHo Kim, Jihoon Shin et al. · Water Resources Research · 2021 · 45 citations

Hydrological Prediction, Environmental Monitoring, Engineering +19

Machine learning and explainable AI for chlorophyll-a prediction in Namhan River Watershed, South Korea

Ji Woo Han, TaeHo Kim, Sangchul Lee et al. · Ecological Indicators · 2024 · 25 citations · Full text