Development of a model to predict water quality using an automated machine learning algorithm View count 252

Jungsu Park

Journal of the Korean Society of Water and Wastewater :: Vol.36 No.6 pp.329-337

DOI:https://doi.org/10.11001/jksww.2022.36.6.329

Development of ensemble machine learning model considering the characteristics of input variables and the interpretation of model performance using explainable artificial intelligence View count 309

Jungsu Park

Journal of the Korean Society of Water and Wastewater :: Vol.36 No.4 pp.239-248

DOI:https://doi.org/10.11001/jksww.2022.36.4.239

Effect of input variable characteristics on the performance of an ensemble machine learning model for algal bloom prediction View count 623

Byeong-Koo Kang, Jungsu Park

Journal of the Korean Society of Water and Wastewater :: Vol.35 No.6 pp.417-424

DOI:https://doi.org/10.11001/jksww.2021.35.6.417

A study on the method of setting the water quality target level for integrated environmental management View count 681

Hyeon-Jeong Hwang, Jong-Beom Khan, Ji Hye Seo, Sunkyung Lee, Young-Lan Kim

Journal of the Korean Society of Water and Wastewater :: Vol.35 No.3 pp.187-196

DOI:https://doi.org/10.11001/jksww.2021.35.3.187

Evolution of Water supply system! Smart Water Management for customer View count 1655

Jae-Bog Kim

Journal of the Korean Society of Water and Wastewater :: Vol.29 No.4 pp.511-517

DOI:https://doi.org/10.11001/jksww.2015.29.4.511