Ammonical nitrogen effluent prediction using artificial neural network

• Main Authors: Mujeli, Mustapha, Jami, Mohammed Saedi, Kabbashi, Nassereldeen Ahmed
• Format: Conference or Workshop Item
• Language: English
• Published: 2011
• Subjects: TD194 Environmental effects of industries and plants
• Online Access: http://irep.iium.edu.my/3195/1/ICBioE_2011_paper.pdf; http://irep.iium.edu.my/3195/

Ammoniacal nitrogen (NH3-N) in domestic wastewater treatment plants (WWTP’s) has recently been added as the monitoring parameter by department of environment. It is necessary to obtain a suitable model for the prediction of NH3-N in the effluent stream of WWTP in order to meet the stringent environmental laws. Therefore, the study explores the robust capability of artificial neural network (ANN) in solving complex problems, as such similar to physical, chemical and biological environment of wastewater treatment plant. Data obtained from Bandar Tun Razak Sewerage Treatment Plant (STP) was used for development of the model. The prediction of ammoniacal nitrogen in the effluent stream using the developed model shows a satisfactory result for the reason that the mean square error (MSE) and correlation coefficient (R) were 0.1591 and 0.7980 respectively.