Artificial neural network approach to predict the electrical conductivity and density of Ag-Ni binary alloys

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dc.contributor.authorOzerdem, Mehmet Sirac
dc.date.accessioned2024-04-24T16:15:10Z
dc.date.available2024-04-24T16:15:10Z
dc.date.issued2008
dc.departmentDicle Üniversitesien_US
dc.description.abstractin this study, artificial neural network (ANN) approach was done to predict electrical conductivity and density of silver-nickel binary alloys using aback-propagation neural network that uses gradient descent learning algorithm. in ANN training module, Ag%. and Ni% (weight) contents were employed as input and electrical conductivity, calculated and typical density were used 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 the neural network was found successful for the prediction of electrical conductivity and density of silver nickel binary alloys. (C) 2008 Elsevier B.V. All rights reserved.en_US
dc.description.sponsorshipDicle University Research Committee [DUAPK 03-MF-86]en_US
dc.description.sponsorshipThe author would like to thank 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.jmatprotec.2008.01.016
dc.identifier.endpage476en_US
dc.identifier.issn0924-0136
dc.identifier.issue1-3en_US
dc.identifier.scopus2-s2.0-52949147141
dc.identifier.scopusqualityQ1
dc.identifier.startpage470en_US
dc.identifier.urihttps://doi.org/10.1016/j.jmatprotec.2008.01.016
dc.identifier.urihttps://hdl.handle.net/11468/15681
dc.identifier.volume208en_US
dc.identifier.wosWOS:000260690500062
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoenen_US
dc.publisherElsevier Science Saen_US
dc.relation.ispartofJournal of Materials Processing Technology
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectArtificial Neural Networken_US
dc.subjectElectrical Conductivityen_US
dc.subjectDensityen_US
dc.subjectSilver-Nickel Binary Alloysen_US
dc.titleArtificial neural network approach to predict the electrical conductivity and density of Ag-Ni binary alloysen_US
dc.titleArtificial neural network approach to predict the electrical conductivity and density of Ag-Ni binary alloys
dc.typeArticleen_US

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