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The Use of NARX Neural Network for Modeling of Adsorption of Zinc Ions Using Activated Almond Shell as a Potential Biosorbent

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dc.authorscopusid12144397300
dc.authorscopusid35726694300
dc.authorscopusid22953804000
dc.authorscopusid35567972100
dc.contributor.authorÇoruh, S.
dc.contributor.authorGeyikçi, F.
dc.contributor.authorKilic, E.
dc.contributor.authorÇoruh, U.
dc.date.accessioned2020-06-21T14:04:06Z
dc.date.available2020-06-21T14:04:06Z
dc.date.issued2014
dc.departmentOndokuz Mayıs Üniversitesien_US
dc.department-temp[Çoruh] Semra, Department of Environmental Engineering, Ondokuz Mayis Üniversitesi, Samsun, Turkey; [Geyikçi] Feza, Department of Chemical Engineering, Ondokuz Mayis Üniversitesi, Samsun, Turkey; [Kilic] Erdal, Department of Computer Engineering, Ondokuz Mayis Üniversitesi, Samsun, Turkey; [Çoruh] Ufuk, Department of Computer Education and Instructional Technology, Ondokuz Mayis Üniversitesi, Samsun, Turkeyen_US
dc.description.abstractIn this study, nonlinear autoregressive model processes with exogenous input (NARX) are applied for the prediction of percentage adsorption efficiency for the removal of zinc ions from wastewater by activated almond shell. The effect of operational parameters such as pH, dosage, particle size and initial metal ions concentration are studied to optimize the conditions for maximum removal of zinc ions. The model is first developed using a two layer NARX network. A comparison between the model results and experimental data showed that the NARX model is able to predict the removal of zinc ions from wastewater. The outcomes of suggested NARX modeling were then compared to batch experimental studies. The results show that activated almond shell is an efficient sorbent and NARX network, which is easy to implement and is able to model the batch experimental system. © 2013 Elsevier Ltd.en_US
dc.identifier.doi10.1016/j.biortech.2013.10.019
dc.identifier.endpage410en_US
dc.identifier.issn0960-8524
dc.identifier.issn1873-2976
dc.identifier.pmid24446542
dc.identifier.scopus2-s2.0-84897083721
dc.identifier.scopusqualityQ1
dc.identifier.startpage406en_US
dc.identifier.urihttps://doi.org/10.1016/j.biortech.2013.10.019
dc.identifier.volume151en_US
dc.identifier.wosWOS:000330085800059
dc.identifier.wosqualityQ1
dc.language.isoenen_US
dc.publisherElsevier Ltden_US
dc.relation.ispartofBioresource Technologyen_US
dc.relation.journalBioresource Technologyen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAlmond Shellen_US
dc.subjectBiosorptionen_US
dc.subjectIsothermen_US
dc.subjectNARX Neural Networken_US
dc.subjectZincen_US
dc.titleThe Use of NARX Neural Network for Modeling of Adsorption of Zinc Ions Using Activated Almond Shell as a Potential Biosorbenten_US
dc.typeArticleen_US
dspace.entity.typePublication

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