A hybrid machine learning–based multi-objective supervisory control strategy of a full-scale wastewater treatment for cost-effective and sustainable operation under varying influent conditions | ||
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SungKu Heo†, KiJeon Nam†, Shahzeb Tariq, Juin Yau Lim, Junkyu Park, and Chang Kyoo Yoo*, A hybrid machine learning–based multi-objective supervisory control strategy of a full-scale wastewater treatment for cost-effective and sustainable operation under varying influent conditions, Journal of Cleaner Production (ISSN:0959-6526, SCIE, Top 10% journal:Engineering Civil), Elsevier, 291(4), pp.125853 (2021.04) (Ack:2017R1E1A1A03070713 & Climate Change Graduate School). |
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이전글 | Multi-objective optimization of a time-delay compensated ventilation control system in a subway facility – A harmony search strategy | |
다음글 | Inter-regional multimedia fate analysis of PAHs and potential risk assessment by integrating deep learning and climate change scenarios |