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Using an rtificial neural network approach for supplier evaluation process and a sectoral application

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dc.contributor.authorYAYLA, AYŞE
dc.contributor.authorHARTOMACIOĞLU, SELİM
dc.contributor.authorsYAYLA A., HARTOMACIOĞLU S.
dc.date.accessioned2023-02-02T06:02:41Z
dc.date.available2023-02-02T06:02:41Z
dc.date.issued2011-01-01
dc.description.abstractIn this study, a-three layered feed-forward backpropagation Artificial Neural Network (ANN) model is developed for the supplier firms in ceramic sector on the bases of user effectiveness for using concurrent engineering method. The developed model is also questioned for its usability in the supplier evaluation process. The network\"s independent variables of the developed model are considered as input variables of the network and dependent variables are used as output variables. The values of these variables are determined with factor analysis. For obtaining the date set to be used in the analysis, a questionnaire form with 34 questions explaining the network\"s input and output variables are prepared and sent out to 52 firms active in related sector. For obtaining more accurate results from the network, the questions having factor load below 0,6 are eliminated from the analysis. With the elimination of the questions from the analysis, the answers given for 22 questions explaining 8 input variables are used for the evaluation the network\"s inputs, the answers given for 3 questions explaining output variables are used for the evaluation the network\"s outputs. The data set of the network\"s are divided into four equal groups with k-fold method in order to get four different alternative network structures. As a conclusion, the forecasted firm scores giving the minimum error from the network test simulation and real firm scores are found to be very close to each other, thus, it is concluded that the developed artificial neural network model can be used effectively in the supplier evaluation process.
dc.identifier.citationYAYLA A., HARTOMACIOĞLU S., "Using an Artificial Neural Network Approach for Supplier Evaluation Process and a Sectoral Application", PAMUKKALE UNIVERSITY JOURNAL OF ENGINEERING SCIENCES-PAMUKKALE UNIVERSITESI MUHENDISLIK BILIMLERI DERGISI, cilt.17, sa.2, ss.97-107, 2011
dc.identifier.endpage107
dc.identifier.issn1300-7009
dc.identifier.issue2
dc.identifier.startpage97
dc.identifier.urihttps://hdl.handle.net/11424/285976
dc.identifier.volume17
dc.language.isoeng
dc.relation.ispartofPAMUKKALE UNIVERSITY JOURNAL OF ENGINEERING SCIENCES-PAMUKKALE UNIVERSITESI MUHENDISLIK BILIMLERI DERGISI
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectHarita Mühendisliği-Geomatik
dc.subjectMühendislik ve Teknoloji
dc.subjectGeotechnical Engineering
dc.subjectEngineering and Technology
dc.subjectMÜHENDİSLİK, ÇOK DİSİPLİNLİ
dc.subjectMühendislik
dc.subjectMühendislik, Bilişim ve Teknoloji (ENG)
dc.subjectENGINEERING, MULTIDISCIPLINARY
dc.subjectENGINEERING
dc.subjectEngineering, Computing & Technology (ENG)
dc.subjectGenel Mühendislik
dc.subjectMedya Teknolojisi
dc.subjectMühendislik (çeşitli)
dc.subjectFizik Bilimleri
dc.subjectGeneral Engineering
dc.subjectMedia Technology
dc.subjectEngineering (miscellaneous)
dc.subjectPhysical Sciences
dc.subjectSupplier evaluation
dc.subjectConcurrent engineering
dc.subjectArtificial neural network
dc.titleUsing an rtificial neural network approach for supplier evaluation process and a sectoral application
dc.typearticle
dspace.entity.typePublication
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local.indexed.atWOS
relation.isAuthorOfPublication803e23ed-bec9-4114-8a7e-36fdf199f2ef
relation.isAuthorOfPublication081dfaca-022c-4d9c-9bae-c10aa5f5a432
relation.isAuthorOfPublication.latestForDiscovery803e23ed-bec9-4114-8a7e-36fdf199f2ef

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