Simulation of ammoniacal nitrogen effluent using feedforward multilayer neural networks

Ammoniacal nitrogen in domestic wastewater treatment plants has recently been added as the monitoring parameter by the Department of Environment, Malaysia. It is necessary to obtain a suitable model for the simulation of ammonical nitrogen in the effluent stream of sewage treatment plant in order...

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Main Authors: Jami, Mohammed Saedi, Mujeli, Mustapha, Kabbashi, Nassereldeen Ahmed
Format: Article
Language:English
Published: Academic Journals 2011
Subjects:
Online Access:http://irep.iium.edu.my/13577/
http://irep.iium.edu.my/13577/1/Jami_et_al_published.pdf
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author Jami, Mohammed Saedi
Mujeli, Mustapha
Kabbashi, Nassereldeen Ahmed
author_facet Jami, Mohammed Saedi
Mujeli, Mustapha
Kabbashi, Nassereldeen Ahmed
author_sort Jami, Mohammed Saedi
building IIUM Repository
collection Online Access
description Ammoniacal nitrogen in domestic wastewater treatment plants has recently been added as the monitoring parameter by the Department of Environment, Malaysia. It is necessary to obtain a suitable model for the simulation of ammonical nitrogen in the effluent stream of sewage treatment plant in order to meet the new environmental laws. Therefore, this study explores the robust capability of artificial neural network in solving complex problems, which are similar to physical, chemical and biological conditions of wastewater treatment plant. Data obtained from Bandar Tun Razak Sewage Treatment plant was used for the model design. The simulation of ammoniacal nitrogen in the effluent stream by model shows a satisfactory result because the mean square error and correlation coefficients were 0.1591 and 0.7980, respectively.
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spelling iium-135772012-01-03T02:21:39Z http://irep.iium.edu.my/13577/ Simulation of ammoniacal nitrogen effluent using feedforward multilayer neural networks Jami, Mohammed Saedi Mujeli, Mustapha Kabbashi, Nassereldeen Ahmed TD Environmental technology. Sanitary engineering TP248.13 Biotechnology Ammoniacal nitrogen in domestic wastewater treatment plants has recently been added as the monitoring parameter by the Department of Environment, Malaysia. It is necessary to obtain a suitable model for the simulation of ammonical nitrogen in the effluent stream of sewage treatment plant in order to meet the new environmental laws. Therefore, this study explores the robust capability of artificial neural network in solving complex problems, which are similar to physical, chemical and biological conditions of wastewater treatment plant. Data obtained from Bandar Tun Razak Sewage Treatment plant was used for the model design. The simulation of ammoniacal nitrogen in the effluent stream by model shows a satisfactory result because the mean square error and correlation coefficients were 0.1591 and 0.7980, respectively. Academic Journals 2011-12-16 Article PeerReviewed application/pdf en http://irep.iium.edu.my/13577/1/Jami_et_al_published.pdf Jami, Mohammed Saedi and Mujeli, Mustapha and Kabbashi, Nassereldeen Ahmed (2011) Simulation of ammoniacal nitrogen effluent using feedforward multilayer neural networks. African Journal of Biotechnology, 10 (81). pp. 18755-18762. ISSN 1684–5315 http://www.academicjournals.org/AJB/PDF/pdf2011/16DecConf/Jami%20et%20al.pdf DOI: 10.5897/AJB11.2748
spellingShingle TD Environmental technology. Sanitary engineering
TP248.13 Biotechnology
Jami, Mohammed Saedi
Mujeli, Mustapha
Kabbashi, Nassereldeen Ahmed
Simulation of ammoniacal nitrogen effluent using feedforward multilayer neural networks
title Simulation of ammoniacal nitrogen effluent using feedforward multilayer neural networks
title_full Simulation of ammoniacal nitrogen effluent using feedforward multilayer neural networks
title_fullStr Simulation of ammoniacal nitrogen effluent using feedforward multilayer neural networks
title_full_unstemmed Simulation of ammoniacal nitrogen effluent using feedforward multilayer neural networks
title_short Simulation of ammoniacal nitrogen effluent using feedforward multilayer neural networks
title_sort simulation of ammoniacal nitrogen effluent using feedforward multilayer neural networks
topic TD Environmental technology. Sanitary engineering
TP248.13 Biotechnology
url http://irep.iium.edu.my/13577/
http://irep.iium.edu.my/13577/
http://irep.iium.edu.my/13577/
http://irep.iium.edu.my/13577/1/Jami_et_al_published.pdf