Amelioration of carbon removal prediction for an activated sludge process using an artificial neural network (ANN)

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dc.contributor.authorGueclue, Duenyamin
dc.contributor.authorDursun, Suekrue
dc.date.accessioned2020-03-26T17:26:23Z
dc.date.available2020-03-26T17:26:23Z
dc.date.issued2008
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractA dynamic simulation model of the Ankara central wastewater treatment plant (ACWTP) was evaluated for the prediction of effluent COD concentrations. Firstly, a mechanistic model of the municipal wastewater treatment process was developed based on Activated Sludge Model No. 1 (ASM1) by using a GPS-X computer program. Then, the mechanistic model was combined with a feed-forward back-propagation neural network in parallel configuration. The appropriate architecture of the neural network models was determined through several iterative steps of training and testing of the models. Both models were run with the data obtained from the plant operation and laboratory analysis to predict the dynamic behavior of the process. Using these two models, effluent COD concentrations were predicted and the results were compared for the purpose of evaluation of treatment performance. It was observed that the ASM1 ANN model approach gave better results and better described the operational conditions of the plant than ASM1.en_US
dc.description.sponsorshipSelcuk University Research FundSelcuk University [2005-101018]en_US
dc.description.sponsorshipThis study was supported by the Selcuk University Research Fund (BAP) (Project No: 2005-101018). The authors would also like to thank ASKI, Ankara, Turkey, for their help during the study and for or providing WWTP process data.en_US
dc.identifier.doi10.1002/clen.200700155en_US
dc.identifier.endpage787en_US
dc.identifier.issn1863-0650en_US
dc.identifier.issn1863-0669en_US
dc.identifier.issue9en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage781en_US
dc.identifier.urihttps://dx.doi.org/10.1002/clen.200700155
dc.identifier.urihttps://hdl.handle.net/20.500.12395/22191
dc.identifier.volume36en_US
dc.identifier.wosWOS:000259523800009en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherWILEYen_US
dc.relation.ispartofCLEAN-SOIL AIR WATERen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectactivated sludge modelen_US
dc.subjectartificial neural networken_US
dc.subjectchemical oxygen demanden_US
dc.subjectmodelingen_US
dc.subjectwastewater treatment planten_US
dc.titleAmelioration of carbon removal prediction for an activated sludge process using an artificial neural network (ANN)en_US
dc.typeArticleen_US

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