Dose and fading time estimation of glass ceramic by using artificial neural networkmethod

dc.contributor.authorIşık, İbrahim
dc.contributor.authorIşık, Esme
dc.contributor.authorToktamış, Hüseyin
dc.date.accessioned2022-12-06T08:40:36Z
dc.date.available2022-12-06T08:40:36Z
dc.date.issued2021
dc.departmentİnönü Üniversitesien_US
dc.description.abstractCeramic materials commonly used for dental prosthetics and restorations shows luminescent properties.Dental ceramics are considered the most natural-looking restorative materials for aesthetic rehabilitationdue to their transparency. They are commonly used for dose response and fading assessment by usingthermoluminescence method in various fields of dosimetric applications. In present study, we useartificial neural networks (ANN) toolbox of Matlab to predict irradiation dose and fading time usingglow curve data from dental glass ceramic which is thermoluminescent (TL) dosimetric material.Temperature, dose value and fading time are used for input and TL intensity used for output component of the proposed ANN model. 18 neurons are used for hidden layer to analyze the experimental results ofthe model. Experimental and simulation results are compared and similarity is found as about 99 % inthis present study.en_US
dc.identifier.citationIŞIK İ, IŞIK E, TOKTAMIŞ H (2021). Dose and fading time estimation of glass ceramic by using artificial neural networkmethod. Dicle Üniversitesi Mühendislik Fakültesi Mühendislik Dergisi, 12(1), 47 - 52. 10.24012/dumf.703171en_US
dc.identifier.doi10.24012/dumf.703171en_US
dc.identifier.endpage52en_US
dc.identifier.issn1309-8640
dc.identifier.issn2146-4391
dc.identifier.issue1en_US
dc.identifier.startpage47en_US
dc.identifier.trdizinid482618en_US
dc.identifier.urihttps://doi.org/10.24012/dumf.703171
dc.identifier.urihttps://hdl.handle.net/11616/85627
dc.identifier.urihttps://search.trdizin.gov.tr/yayin/detay/482618
dc.identifier.volume12en_US
dc.indekslendigikaynakTR-Dizinen_US
dc.language.isoenen_US
dc.relation.ispartofDicle Üniversitesi Mühendislik Fakültesi Mühendislik Dergisien_US
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.titleDose and fading time estimation of glass ceramic by using artificial neural networkmethoden_US
dc.typeArticleen_US

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