Publication:
Prediction of optical parameters of sn doped cdo films using neural network

dc.contributor.authorKöse, S.
dc.contributor.authorAtay, F.
dc.contributor.authorBilgin, V.
dc.contributor.authorAkyuz, I.
dc.contributor.buuauthorErtürk, Kadir
dc.contributor.buuauthorHaciismailoglu, M. C.
dc.contributor.buuauthorHACIİSMAİLOĞLU, MUHAMMED CÜNEYT
dc.contributor.buuauthorKüçük, İ.
dc.contributor.buuauthorDerebaşı, Naim
dc.contributor.buuauthorDEREBAŞI, NAİM
dc.contributor.departmentBursa Uludağ Üniversitesi/Fen Edebiyat Fakültesi/Fizik Bölümü.
dc.contributor.orcid0000-0001-5650-9146
dc.contributor.orcid0000-0002-0880-5028
dc.contributor.orcid0000-0002-0781-3376
dc.contributor.orcid0000-0001-8483-7366
dc.contributor.orcid0000-0003-2546-0022
dc.contributor.researcheridAAG-5509-2019
dc.contributor.researcheridK-7950-2012
dc.contributor.researcheridABG-7537-2020
dc.contributor.researcheridA-1120-2010
dc.contributor.researcheridAAV-3055-2021
dc.contributor.researcheridABA-5148-2020
dc.contributor.researcheridAAI-2254-2021
dc.date.accessioned2024-10-10T05:19:02Z
dc.date.available2024-10-10T05:19:02Z
dc.date.issued2008-02-01
dc.descriptionBu çalışma, 05-07 Haziran 2007 tarihleri arasında Constanta[Romanya]’da düzenlenen 8. International Balkan Workshop on Applied Physics’da bildiri olarak sunulmuştur.
dc.description.abstractIn recent years, there was great interest and demand for the production and investigation of low cost and novel transparent conducting oxide films. CdO is a promising material among these films for future applications with its unique properties. A learning and generalization ability, real-time operation, and ease of implementation have made an artificial neural network popular in recent years. In this work we have produced CdO:Sn films by the ulrasonic spray pyrolysis technique which is economical and simple to process. Optical parameters of Sn doped CdO films with developed, have been estimated by the artificial neural network using experimental results as a training data. The correlation obtain from the artificial neural network was found to be 99% with the experimental results.
dc.identifier.endpage338
dc.identifier.issn1454-4164
dc.identifier.issue2
dc.identifier.startpage335
dc.identifier.urihttps://hdl.handle.net/11452/46155
dc.identifier.volume10
dc.identifier.wos000253691400024
dc.indexed.wosWOS.SCI
dc.indexed.wosWOS.ISTP
dc.language.isoen
dc.publisherNatl Inst Optoelectronics
dc.relation.journalJournal Of Optoelectronics And Advanced Materials
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectZno thin-films
dc.subjectUltrasonic spray-pyrolysis
dc.subjectPhysical-properties
dc.subjectTransparent
dc.subjectDeposition
dc.subjectNi
dc.subjectAl
dc.subjectCadmium oxide
dc.subjectSpray pyrolysis
dc.subjectOptical properties
dc.subjectNeural networks
dc.subjectGenetic algorithm
dc.subjectScience & technology
dc.subjectTechnology
dc.subjectPhysical sciences
dc.subjectMaterials science, multidisciplinary
dc.subjectOptics
dc.subjectPhysics, applied
dc.subjectMaterials science
dc.subjectPhysics
dc.titlePrediction of optical parameters of sn doped cdo films using neural network
dc.typeArticle
dc.typeProceedings Paper
dspace.entity.typePublication
relation.isAuthorOfPublication82584aef-f502-4b13-a805-f9de1bf37ec0
relation.isAuthorOfPublication0c85f61f-70fa-4f0d-83a0-a3a0ac50e069
relation.isAuthorOfPublication.latestForDiscovery82584aef-f502-4b13-a805-f9de1bf37ec0

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