Wastewater treatment plant performance evaluation using artificial neural network model

The final protection of wastewater pollutants to the environment is wastewater treatment plant (WWTP). This Research paper intends to develop a model from the past operational data of WWTP using artificial neural network (ANN) for the evaluation of the plant performance. The model was developed usin...

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Main Authors: Mujeli, Mustapha, Jami, Mohammed Saedi, Kabbashi, Nassereldeen Ahmed
Format: Proceeding Paper
Language:English
Published: 2010
Subjects:
Online Access:http://irep.iium.edu.my/3255/1/A08_Mustapha_Mujeli.pdf
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author Mujeli, Mustapha
Jami, Mohammed Saedi
Kabbashi, Nassereldeen Ahmed
author_facet Mujeli, Mustapha
Jami, Mohammed Saedi
Kabbashi, Nassereldeen Ahmed
author_sort Mujeli, Mustapha
collection IIUM
description The final protection of wastewater pollutants to the environment is wastewater treatment plant (WWTP). This Research paper intends to develop a model from the past operational data of WWTP using artificial neural network (ANN) for the evaluation of the plant performance. The model was developed using four years’ operational data of Bandar Tun Razak sewerage treatment plant (STP) Kuala Lumpur, Malaysia. Matlab version 2008b software was used in training the ANN model. The model shows a high prediction capacity for multiple parallel outputs of effluent biochemical oxygen demand (BODe), chemical oxygen demand (CODe), suspended solid (SSe) and Ammonical nitrogen (NH3-Ne) than single output of each of the parameters individually. The coefficient of determination (R) and mean square error of the best model were 0.9449 and 2.86 respectively.
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spelling oai:generic.eprints.org:32552011-10-07T07:25:47Z http://irep.iium.edu.my/3255/ Wastewater treatment plant performance evaluation using artificial neural network model Mujeli, Mustapha Jami, Mohammed Saedi Kabbashi, Nassereldeen Ahmed TD159 Municipal engineering The final protection of wastewater pollutants to the environment is wastewater treatment plant (WWTP). This Research paper intends to develop a model from the past operational data of WWTP using artificial neural network (ANN) for the evaluation of the plant performance. The model was developed using four years’ operational data of Bandar Tun Razak sewerage treatment plant (STP) Kuala Lumpur, Malaysia. Matlab version 2008b software was used in training the ANN model. The model shows a high prediction capacity for multiple parallel outputs of effluent biochemical oxygen demand (BODe), chemical oxygen demand (CODe), suspended solid (SSe) and Ammonical nitrogen (NH3-Ne) than single output of each of the parameters individually. The coefficient of determination (R) and mean square error of the best model were 0.9449 and 2.86 respectively. 2010-10-11 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/3255/1/A08_Mustapha_Mujeli.pdf Mujeli, Mustapha and Jami, Mohammed Saedi and Kabbashi, Nassereldeen Ahmed (2010) Wastewater treatment plant performance evaluation using artificial neural network model. In: International Postgraduate Conference on Engineering (IPCE 2010), 16 - 17 October 2010, Perlis, Malaysia.
spellingShingle TD159 Municipal engineering
Mujeli, Mustapha
Jami, Mohammed Saedi
Kabbashi, Nassereldeen Ahmed
Wastewater treatment plant performance evaluation using artificial neural network model
title Wastewater treatment plant performance evaluation using artificial neural network model
title_full Wastewater treatment plant performance evaluation using artificial neural network model
title_fullStr Wastewater treatment plant performance evaluation using artificial neural network model
title_full_unstemmed Wastewater treatment plant performance evaluation using artificial neural network model
title_short Wastewater treatment plant performance evaluation using artificial neural network model
title_sort wastewater treatment plant performance evaluation using artificial neural network model
topic TD159 Municipal engineering
url http://irep.iium.edu.my/3255/1/A08_Mustapha_Mujeli.pdf
work_keys_str_mv AT mujelimustapha wastewatertreatmentplantperformanceevaluationusingartificialneuralnetworkmodel
AT jamimohammedsaedi wastewatertreatmentplantperformanceevaluationusingartificialneuralnetworkmodel
AT kabbashinassereldeenahmed wastewatertreatmentplantperformanceevaluationusingartificialneuralnetworkmodel