An evaluation of automated structure learning with Bayesian networks: An application to estuarine chlorophyll dynamics. - Ibrahim Alameddine; YoonKyung Cha; Kenneth H. Reckhow (Environ. Model. Softw., 2011)

A Bayesian network incorporating observation error to predict phosphorus and chlorophyll a in Saginaw Bay. - YoonKyung Cha; Craig A. Stow (Environ. Model. Softw., 2014)

Optimizing Semi-Analytical Algorithms for Estimating Chlorophyll-a and Phycocyanin Concentrations in Inland Waters in Korea. - Jong Cheol Pyo; Yakov Pachepsky; Sang-Soo Baek; YongSeong Kwon; Minjeong Kim; Hyuk Lee; Sanghyun Park; YoonKyung Cha; Rim Ha; Gibeom Nam; Yongeun Park; Kyung Hwa Cho (Remote. Sens., 2017)

Small values in big data: The continuing need for appropriate metadata. - Craig A. Stow; Katherine E. Webster; Tyler Wagner; Noah Lottig; Patricia A. Soranno; YoonKyung Cha (Ecol. Informatics, 2018)

Simulating seasonal variability of phytoplankton in stream water using the modified SWAT model. - Jong Cheol Pyo; Yakov A. Pachepsky; Minjeong Kim; Sang-Soo Baek; Hyuk Lee; YoonKyung Cha; Yongeun Park; Kyung Hwa Cho (Environ. Model. Softw., 2019)

An Integrative Remote Sensing Application of Stacked Autoencoder for Atmospheric Correction and Cyanobacteria Estimation Using Hyperspectral Imagery. - Jong Cheol Pyo; Hongtao Duan 001; Mayzonee Ligaray; Minjeong Kim; Sang-Soo Baek; Yong Sung Kwon; Hyuk Lee; Taegu Kang; Kyunghyun Kim; YoonKyung Cha; Kyung Hwa Cho (Remote. Sens., 2020)

Effects of class imbalance on resampling and ensemble learning for improved prediction of cyanobacteria blooms. - Jihoon Shin; Seonghyeon Yoon; YoungWoo Kim; Taeho Kim; ByeongGeon Go; YoonKyung Cha (Ecol. Informatics, 2021)

Data-driven models for predicting community changes in freshwater ecosystems: A review. - Da-Yeong Lee; Dae-Seong Lee; YoonKyung Cha; Joong-Hyuk Min; Young-Seuk Park (Ecol. Informatics, 2023)

Changes in zooplankton community in response to a shift from lentic to lotic conditions in a regulated river. - Taeseung Park; Gunhyeong Lee; Jihoon Shin; Jong-hwan Park; Byungwoong Choi; Dong-Kyun Kim; YoonKyung Cha (Ecol. Informatics, 2023)

Generalizability evaluations of heterogeneous ensembles for river health predictions. - Taeseung Park; Jihoon Shin; Baekyung Park; Jeongsuk Moon; YoonKyung Cha (Ecol. Informatics, 2024)

A river network model using a weight-based merged LSTM for multi-source monitoring integration. - Jonggyu Jung; Taeseung Park; Jaegwan Park; Dogeon Lee; YoonKyung Cha (Ecol. Informatics, 2025)