New tool for evaluation of performance of wastewater treatment plant: Artificial neural network

Abstract Kohonen self-organizing feature maps, a method of artificial intelligence method, was used to classify operational data of Pelham wastewater treatment plant and to determine the reasons for high effluent concentrations of biological oxygen demand (BOD), total suspended solids (TSS) and fecal coliform in this study. The reasons causing high effluent concentrations of these parameters were low pH in the biological reactor and high solid retention time (SRT).