Water, Volume 14, Issue 7
2022 April-1 - 184 articles
Cover Story: On-line sensors equipped in wastewater treatment plants (WWTPs) provide support for the future prediction of effluent water quality and associated proactive regulation actions. This paper developed an improved feedforward neural network (IFFNN) model that coupled on-line data. Hourly WWTP influent and treatment process data, as well as effluent data, were employed as model input variables. A demonstration in a real WWTP showed that the IFFNN enhanced prediction performance by over 50%, compared to a model without historical on-line effluent input. View this paper - Issues are regarded as officially published after their release is announced to the table of contents alert mailing list .
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