Optimizations of friction stir welding of aluminum alloy by using genetically optimized neural network

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dc.authoriddemetgul, mustafa/0000-0001-9385-9305
dc.authoridYAPICI, Ahmet/0000-0003-4274-2697
dc.authoridOkuyucu, Hasan/0000-0002-4977-6980
dc.authoridTansel, Ibrahim/0000-0002-8808-9518
dc.contributor.authorTansel, Ibrahim N.
dc.contributor.authorDemetgul, Mustafa
dc.contributor.authorOkuyucu, Hasan
dc.contributor.authorYapici, Ahmet
dc.date.accessioned2024-09-18T20:52:54Z
dc.date.available2024-09-18T20:52:54Z
dc.date.issued2010
dc.departmentHatay Mustafa Kemal Üniversitesien_US
dc.description.abstractGenetically optimized neural network systems (GONNS) was developed to simulate the intelligent decision-making capability of human beings. After they are trained with experimental data or observations, GONNS use one or more artificial neural networks (ANN) to represent complex systems. The optimization is performed by one or more genetic algorithms (GA). In this study, the GONNS was used to estimate the optimal operating condition of the friction stir welding (FSW) process. Five separate ANNs represented the relationship between two identical input parameters and each one of the considered characteristics of the welding zone. GA searched for the optimized parameters to make one of the parameters maximum or minimum, while the other four are kept within the desired range. The GONNS was found as an excellent optimization tool for FSW.en_US
dc.identifier.doi10.1007/s00170-009-2266-6
dc.identifier.endpage101en_US
dc.identifier.issn0268-3768
dc.identifier.issn1433-3015
dc.identifier.issue1-4en_US
dc.identifier.scopus2-s2.0-77954213893en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage95en_US
dc.identifier.urihttps://doi.org/10.1007/s00170-009-2266-6
dc.identifier.urihttps://hdl.handle.net/20.500.12483/11481
dc.identifier.volume48en_US
dc.identifier.wosWOS:000275659200009en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringer London Ltden_US
dc.relation.ispartofInternational Journal of Advanced Manufacturing Technologyen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectOptimizationen_US
dc.subjectNeural networken_US
dc.subjectGenetic algorithmen_US
dc.subjectGONNSen_US
dc.subjectFriction stir weldingen_US
dc.titleOptimizations of friction stir welding of aluminum alloy by using genetically optimized neural networken_US
dc.typeArticleen_US

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