Artificial neural network approach to predict the mechanical properties of Cu-Sn-Pb-Zn-Ni cast alloys

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dc.contributor.authorOzerdem, Mehmet Sirac
dc.contributor.authorKolukisa, Sedat
dc.date.accessioned2024-04-24T16:15:26Z
dc.date.available2024-04-24T16:15:26Z
dc.date.issued2009
dc.departmentDicle Üniversitesien_US
dc.description.abstractIn this study, an artificial neural network approach is employed to predict the mechanical properties of Cu-Sn-Pb-Zn-Ni cast alloys. In artificial neural network (ANN), multi layer perceptron (MLP) architecture with back-propagation algorithm is utilized. In Artificial Neural Network training module, Cu-Sn-Pb-Zn-Ni (wt%) contents were employed as input while yield strength, tensile strength and elongation were employed as outputs. ANN system was trained using the prepared training set (also known as learning set). After training process, the test data were used to check system accuracy, As a result of the study neural network was found successful for the prediction of yield strength, tensile strength and elongation of Cu-Sn-Pb-Zn-Ni alloys. (C) 2008 Elsevier Ltd. All rights reserved.en_US
dc.description.sponsorshipDicle University Research Committee [DUAPK 03-MF-86]; TUBITAK (The Scientific and Technological Research Council of Turkey)en_US
dc.description.sponsorshipThe author would like to thank to Dicle University Research Committee since a part of this study is supported through Grant DUAPK 03-MF-86. Special thanks to TUBITAK (The Scientific and Technological Research Council of Turkey) for their unfailing support to the researchers.en_US
dc.identifier.doi10.1016/j.matdes.2008.05.019
dc.identifier.endpage769en_US
dc.identifier.issn0264-1275
dc.identifier.issn1873-4197
dc.identifier.issue3en_US
dc.identifier.scopus2-s2.0-57149118632
dc.identifier.scopusqualityQ1
dc.identifier.startpage764en_US
dc.identifier.urihttps://doi.org/10.1016/j.matdes.2008.05.019
dc.identifier.urihttps://hdl.handle.net/11468/15800
dc.identifier.volume30en_US
dc.identifier.wosWOS:000262869100049
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoenen_US
dc.publisherElsevier Sci Ltden_US
dc.relation.ispartofMaterials & Design
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectArtificial Neural Networken_US
dc.subjectPrediction Of Mechanical Propertiesen_US
dc.subjectCu-Sn-Pb-Zn-Ni Cast Alloysen_US
dc.titleArtificial neural network approach to predict the mechanical properties of Cu-Sn-Pb-Zn-Ni cast alloysen_US
dc.titleArtificial neural network approach to predict the mechanical properties of Cu-Sn-Pb-Zn-Ni cast alloys
dc.typeArticleen_US

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