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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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 |
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TD Environmental technology. Sanitary engineering TP248.13 Biotechnology |
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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 |
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. |
format |
Article |
author |
Jami, Mohammed Saedi Mujeli, Mustapha Kabbashi, Nassereldeen Ahmed |
author_facet |
Jami, Mohammed Saedi Mujeli, Mustapha Kabbashi, Nassereldeen Ahmed |
author_sort |
Jami, Mohammed Saedi |
title |
Simulation of ammoniacal nitrogen effluent using feedforward multilayer neural networks |
title_short |
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_sort |
simulation of ammoniacal nitrogen effluent using feedforward multilayer neural networks |
publisher |
Academic Journals |
publishDate |
2011 |
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 |
first_indexed |
2023-09-18T20:22:43Z |
last_indexed |
2023-09-18T20:22:43Z |
_version_ |
1777408214550183936 |