Publication: Prediction of optical parameters of sn doped cdo films using neural network
dc.contributor.author | Köse, S. | |
dc.contributor.author | Atay, F. | |
dc.contributor.author | Bilgin, V. | |
dc.contributor.author | Akyuz, I. | |
dc.contributor.buuauthor | Ertürk, Kadir | |
dc.contributor.buuauthor | Haciismailoglu, M. C. | |
dc.contributor.buuauthor | HACIİSMAİLOĞLU, MUHAMMED CÜNEYT | |
dc.contributor.buuauthor | Küçük, İ. | |
dc.contributor.buuauthor | Derebaşı, Naim | |
dc.contributor.buuauthor | DEREBAŞI, NAİM | |
dc.contributor.department | Bursa Uludağ Üniversitesi/Fen Edebiyat Fakültesi/Fizik Bölümü. | |
dc.contributor.orcid | 0000-0001-5650-9146 | |
dc.contributor.orcid | 0000-0002-0880-5028 | |
dc.contributor.orcid | 0000-0002-0781-3376 | |
dc.contributor.orcid | 0000-0001-8483-7366 | |
dc.contributor.orcid | 0000-0003-2546-0022 | |
dc.contributor.researcherid | AAG-5509-2019 | |
dc.contributor.researcherid | K-7950-2012 | |
dc.contributor.researcherid | ABG-7537-2020 | |
dc.contributor.researcherid | A-1120-2010 | |
dc.contributor.researcherid | AAV-3055-2021 | |
dc.contributor.researcherid | ABA-5148-2020 | |
dc.contributor.researcherid | AAI-2254-2021 | |
dc.date.accessioned | 2024-10-10T05:19:02Z | |
dc.date.available | 2024-10-10T05:19:02Z | |
dc.date.issued | 2008-02-01 | |
dc.description | Bu çalışma, 05-07 Haziran 2007 tarihleri arasında Constanta[Romanya]’da düzenlenen 8. International Balkan Workshop on Applied Physics’da bildiri olarak sunulmuştur. | |
dc.description.abstract | In 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.endpage | 338 | |
dc.identifier.issn | 1454-4164 | |
dc.identifier.issue | 2 | |
dc.identifier.startpage | 335 | |
dc.identifier.uri | https://hdl.handle.net/11452/46155 | |
dc.identifier.volume | 10 | |
dc.identifier.wos | 000253691400024 | |
dc.indexed.wos | WOS.SCI | |
dc.indexed.wos | WOS.ISTP | |
dc.language.iso | en | |
dc.publisher | Natl Inst Optoelectronics | |
dc.relation.journal | Journal Of Optoelectronics And Advanced Materials | |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası | |
dc.rights | info:eu-repo/semantics/closedAccess | |
dc.subject | Zno thin-films | |
dc.subject | Ultrasonic spray-pyrolysis | |
dc.subject | Physical-properties | |
dc.subject | Transparent | |
dc.subject | Deposition | |
dc.subject | Ni | |
dc.subject | Al | |
dc.subject | Cadmium oxide | |
dc.subject | Spray pyrolysis | |
dc.subject | Optical properties | |
dc.subject | Neural networks | |
dc.subject | Genetic algorithm | |
dc.subject | Science & technology | |
dc.subject | Technology | |
dc.subject | Physical sciences | |
dc.subject | Materials science, multidisciplinary | |
dc.subject | Optics | |
dc.subject | Physics, applied | |
dc.subject | Materials science | |
dc.subject | Physics | |
dc.title | Prediction of optical parameters of sn doped cdo films using neural network | |
dc.type | Article | |
dc.type | Proceedings Paper | |
dspace.entity.type | Publication | |
relation.isAuthorOfPublication | 82584aef-f502-4b13-a805-f9de1bf37ec0 | |
relation.isAuthorOfPublication | 0c85f61f-70fa-4f0d-83a0-a3a0ac50e069 | |
relation.isAuthorOfPublication.latestForDiscovery | 82584aef-f502-4b13-a805-f9de1bf37ec0 |