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  • 28. Systematic analysis of capacitive deionization using stepwise operating data and multiple machine learning models: the effect of data attributes on process estimation

    Sung Ho Chae, Jonghun Lee, Chang-Kyu Lee, Seokyoon Moon, Byung-Moon Jun, June-Seok Choi, Hojung Rho

    Desalination Link

  • 27. Exploring decisive operating factors for micropollutants fate in ultraviolet-based advanced oxidation processes using the integrated clustering-classification model

    Ejerssaa, W.W., Seida, M.G., Moon, B.C., Son, M.*, Chae, S.H.*, Hong, S.W.*

    Separation and Purification Technology Link

  • 26. Remediation of acidic effluents from Uranium-Contaminated soil using coffee Residue Biochar: A Combined experimental and Machine learning approach

    Byung-Moon Jun, Sung Ho Chae, Deokhwan Kim, Changgil Son, Tack-Jin Kim, Seok Won Hong, Yeomin Yoon, Kangmin Chon, Hojung Rho

    Separation and Purification Technology Link

  • 25. Robust deep learning model combined with missing input data estimation: Application in a 1000 m3/day high-salinity SWRO plant

    Jeongwoo Moon, Kwanho Jeong, Sung Ho Chae, Jaegyu Shim, Jihye Kim, Kyung Hwa Cho, Kiho Park

    Desalination Link

  • 24. Feasibility study of real-time virtual sensing for water quality parameters in river systems using synthetic data and deep learning models

    Byeongwook Choi, Eun Jin Han, KyoungJin Lee, Moon Son, Seok Won Hong, Sungjong Lee, Sung Ho Chae

    Journal of Environmental Management Link

  • 23. Temporal fusion transformer model for predicting differential pressure in reverse osmosis process

    Seunghyeon Lee, Jaegyu Shim, Jinuk Lee, Sung Ho Chae, Chulmin Lee, Kyung Hwa Cho

    Journal of Water Process Engineering Link

  • 22. Nitrosamine formation driven by electrochemical chlorination of urine-containing source waters: Effects of operational conditions.

    Mingizem Gashaw Seid, Sung Ho Chae, Changha Lee, Kangwoo Cho, Seok Won Hong

    Water Research Link

  • 21. Metadata and feature importance analyses of membrane capacitive deionization models: Is a water treatment artificial intelligence panacea possible?

    Sung Ho Chae, Seok Won Hong, Moon Son

    Desalination Link

  • 20. Autonomous real-time control for membrane capacitive deionization

    Jaegyu Shim, Suin Lee, Nakyeong Yun, Moon Son, Sung Ho Chae, Kyung Hwa Cho

    Water Research Link

  • 19. Multimodal deep learning models incorporating the adsorption characteristics of the adsorbent for estimating the permeate flux in dynamic membranes

    Heewon Jeong, Byeongchan Yun, Seongyeon Na, Moon Son, Sung Ho Chae, Chang-Min Kim, Kyung Hwa Cho

    Journal of Membrane Science Link

2025

  • Systematic analysis of capacitive deionization using stepwise operating data and multiple machine learning models: the effect of data attributes on process estimation

    Sung Ho Chae, Jonghun Lee, Chang-Kyu Lee, Seokyoon Moon, Byung-Moon Jun, June-Seok Choi, Hojung Rho

    Desalination Link

  • Exploring decisive operating factors for micropollutants fate in ultraviolet-based advanced oxidation processes using the integrated clustering-classification model

    Ejerssaa, W.W., Seida, M.G., Moon, B.C., Son, M.*, Chae, S.H.*, Hong, S.W.*

    Separation and Purification Technology Link

  • Remediation of acidic effluents from Uranium-Contaminated soil using coffee Residue Biochar: A Combined experimental and Machine learning approach

    Byung-Moon Jun, Sung Ho Chae, Deokhwan Kim, Changgil Son, Tack-Jin Kim, Seok Won Hong, Yeomin Yoon, Kangmin Chon, Hojung Rho

    Separation and Purification Technology Link

  • Robust deep learning model combined with missing input data estimation: Application in a 1000 m3/day high-salinity SWRO plant

    Jeongwoo Moon, Kwanho Jeong, Sung Ho Chae, Jaegyu Shim, Jihye Kim, Kyung Hwa Cho, Kiho Park

    Desalination Link

  • Feasibility study of real-time virtual sensing for water quality parameters in river systems using synthetic data and deep learning models

    Byeongwook Choi, Eun Jin Han, KyoungJin Lee, Moon Son, Seok Won Hong, Sungjong Lee, Sung Ho Chae

    Journal of Environmental Management Link

  • Temporal fusion transformer model for predicting differential pressure in reverse osmosis process

    Seunghyeon Lee, Jaegyu Shim, Jinuk Lee, Sung Ho Chae, Chulmin Lee, Kyung Hwa Cho

    Journal of Water Process Engineering Link

2024

  • Nitrosamine formation driven by electrochemical chlorination of urine-containing source waters: Effects of operational conditions.

    Mingizem Gashaw Seid, Sung Ho Chae, Changha Lee, Kangwoo Cho, Seok Won Hong

    Water Research Link

  • Metadata and feature importance analyses of membrane capacitive deionization models: Is a water treatment artificial intelligence panacea possible?

    Sung Ho Chae, Seok Won Hong, Moon Son

    Desalination Link

  • Autonomous real-time control for membrane capacitive deionization

    Jaegyu Shim, Suin Lee, Nakyeong Yun, Moon Son, Sung Ho Chae, Kyung Hwa Cho

    Water Research Link

  • Multimodal deep learning models incorporating the adsorption characteristics of the adsorbent for estimating the permeate flux in dynamic membranes

    Heewon Jeong, Byeongchan Yun, Seongyeon Na, Moon Son, Sung Ho Chae, Chang-Min Kim, Kyung Hwa Cho

    Journal of Membrane Science Link

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