A Comparison for Grain Size Calculation of Cu-Zn Alloys with Genetic Programming and Neural Networks

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dc.authoridOZDEMIR, RASIM/0000-0003-1439-0444
dc.contributor.authorKarahan, I. H.
dc.contributor.authorOzdemir, R.
dc.date.accessioned2024-09-18T21:01:53Z
dc.date.available2024-09-18T21:01:53Z
dc.date.issued2015
dc.departmentHatay Mustafa Kemal Üniversitesien_US
dc.descriptionInternational Conference on Computational and Experimental Science and Engineering (ICCESEN) -- OCT 25-29, 2014 -- Antalya, TURKEYen_US
dc.description.abstractNeural Networks (NN) and Genetic Programming (GP) were used as a new method for formulation of grain size of electrodeposited Cu1-xZnx alloys as a function of Zinc and Copper content both electrolyte and the alloy films produced by electrodeposition technique. To predict grain size a great number of different expression models genetic programming and neural network were conducted. Each model differs from the other with their linking function, number of genes, head size, and chromosomes. To generate databases for the new grain size formulations, testing and training sets in total of 134 samples were selected at different Zn and Cu ratios of components. 6 different input parameters were selected and the output parameter was grain size of the electrodeposited Cu-Zn alloys. The testing and training sets consisted of randomly selected 106 and 28 for the proposed models. All results in the models indicated an applicable performance for predicting grain size of the alloys and found reliable. The predicted model showed that all of the input parameters effected on the resulting grain size. The NN and GEP based formulation results are compared with experimental results and found to be quite reliable with a very high correlation (R2 = 0.995 for GEP and 0.999 for NN).en_US
dc.identifier.doi10.12693/APhysPolA.128.B-427
dc.identifier.endpageB431en_US
dc.identifier.issn0587-4246
dc.identifier.issn1898-794X
dc.identifier.issue2Ben_US
dc.identifier.scopus2-s2.0-84947810081en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpageB427en_US
dc.identifier.urihttps://doi.org/10.12693/APhysPolA.128.B-427
dc.identifier.urihttps://hdl.handle.net/20.500.12483/13061
dc.identifier.volume128en_US
dc.identifier.wosWOS:000363011700129en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherPolish Acad Sciences Inst Physicsen_US
dc.relation.ispartofActa Physica Polonica Aen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectFormulationen_US
dc.subjectPredictionen_US
dc.titleA Comparison for Grain Size Calculation of Cu-Zn Alloys with Genetic Programming and Neural Networksen_US
dc.typeConference Objecten_US

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