Genetic programming modelling for the electrical resistivity of Cu-Zn thin films

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dc.authoridOZDEMIR, RASIM/0000-0003-1439-0444
dc.contributor.authorKarahan, Ismail Hakki
dc.contributor.authorOzdemir, Rasim
dc.date.accessioned2024-09-18T20:02:40Z
dc.date.available2024-09-18T20:02:40Z
dc.date.issued2018
dc.departmentHatay Mustafa Kemal Üniversitesien_US
dc.description.abstractElectrical resistivity measurement is an exact way to find defects in metals and alloys. Defects contribute to the residual resistivity, and determining their number is very important. Defining the inner electrical structure of an alloy is difficult, and especially it is unpredictable in alloys. This article offers a genetic programming formulation to learn how deposition conditions and alloy constituents affect the electrical resistivity of Cu-Zn alloy. Input parameters selected were: measurement temperature (K), Cu and Zn% content in the deposition bath and thin films, bath temperature, deposition potential, and the grain size of the samples. Electrical resistivity values were the output parameters. A total of 130 training and testing sets were selected. The comparative results prove the superior performance in predicting electrical resistivity of the films. The produced model proposes a close relationship for all the input parameters with the electrical resistivity property.en_US
dc.identifier.doi10.1007/s12043-018-1613-2
dc.identifier.issn0304-4289
dc.identifier.issn0973-7111
dc.identifier.issue3en_US
dc.identifier.scopus2-s2.0-85051120439en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.urihttps://doi.org/10.1007/s12043-018-1613-2
dc.identifier.urihttps://hdl.handle.net/20.500.12483/7950
dc.identifier.volume91en_US
dc.identifier.wosWOS:000440496200001en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherIndian Acad Sciencesen_US
dc.relation.ispartofPramana-Journal of Physicsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectArtificial intelligenceen_US
dc.subjectmetal and metallic alloysen_US
dc.subjectelectrodepositionen_US
dc.subjectelectrical resistivityen_US
dc.subjectgenetic programmingen_US
dc.subjectcomputer simulationen_US
dc.subjectCu-Zn alloysen_US
dc.subjectelectrolyte conditionsen_US
dc.titleGenetic programming modelling for the electrical resistivity of Cu-Zn thin filmsen_US
dc.typeArticleen_US

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