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

İbrahim IŞIK; Esme IŞIK; Hüseyin TOKTAMIŞ

doi:https://doi.org/10.24012/dumf.703171

Makale detayları

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

Yazarlar:

İbrahim IŞIK | Esme IŞIK | Hüseyin TOKTAMIŞ

Yayıncı:

Dicle University

Ana Başlıklar:

Mühendislik ve uygulamalı operasyonlar

Dergi:

Dicle Üniversitesi Mühendislik Fakültesi Mühendislik Dergisi 2021 Vol.12 Issue 1, pp.47-52

Belge Tipi:

Makale

Yayın Tarihi:

1/2021

Belge Dili:

İngilizce

Document ID (Org No.):

2000949922

Sıklık:

Üç Aylık

eISSN:

2146-4391

pISSN:

1309-8640

DOI:

https://doi.org/10.24012/dumf.703171

Anahtar kelimeler:

Özet:

 

Ceramic materials commonly used for dental prosthetics and restorations shows luminescent properties. Dental ceramics are considered the most natural-looking restorative materials for aesthetic rehabilitation due to their transparency. They are commonly used for dose response and fading assessment by using thermoluminescence method in various fields of dosimetric applications. In present study, we use artificial neural networks (ANN) toolbox of Matlab to predict irradiation dose and fading time using glow 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 of the model. Experimental and simulation results are compared and similarity is found as about 99 % in this present study.

 

Ceramic materials commonly used for dental prosthetics and restorations shows luminescent properties. Dental ceramics are considered the most natural-looking restorative materials for aesthetic rehabilitation due to their transparency. They are commonly used for dose response and fading assessment by using thermoluminescence method in various fields of dosimetric applications. In present study, we use artificial neural networks (ANN) toolbox of Matlab to predict irradiation dose and fading time using glow 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 of the model. Experimental and simulation results are compared and similarity is found as about 99 % in this present study.

Makale detayları

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

Yazarlar:

İbrahim IŞIK | Esme IŞIK | Hüseyin TOKTAMIŞ

Yayıncı:

Dicle University

Ana Başlıklar:

Mühendislik ve uygulamalı operasyonlar

Dergi:

Dicle Üniversitesi Mühendislik Fakültesi Mühendislik Dergisi 2021 Vol.12 Issue 1, pp.47-52

Belge Tipi:

Makale

Yayın Tarihi:

1/2021

Belge Dili:

İngilizce

Document ID (Org No.):

2000949922

Sıklık:

Üç Aylık

eISSN:

2146-4391

pISSN:

1309-8640

DOI:

https://doi.org/10.24012/dumf.703171

Thermoluminescence

Artificial Neural Network

Glow curve

fading

Sayı

Makale detayları

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

Yazarlar: İbrahim IŞIK | Esme IŞIK | Hüseyin TOKTAMIŞ

Yayıncı: Dicle University

Ana Başlıklar: Mühendislik ve uygulamalı operasyonlar

Dergi: Dicle Üniversitesi Mühendislik Fakültesi Mühendislik Dergisi 2021 Vol.12 Issue 1, pp.47-52

Belge Tipi: Makale

Yayın Tarihi: 1/2021

Belge Dili: İngilizce

Document ID (Org No.): 2000949922

Sıklık: Üç Aylık

eISSN: 2146-4391

pISSN: 1309-8640

DOI: https://doi.org/10.24012/dumf.703171

Thermoluminescence

Artificial Neural Network

Glow curve

fading

Sayı

Yazarlar:

İbrahim IŞIK | Esme IŞIK | Hüseyin TOKTAMIŞ

Yayıncı:

Dicle University

Ana Başlıklar:

Mühendislik ve uygulamalı operasyonlar

Dergi:

Dicle Üniversitesi Mühendislik Fakültesi Mühendislik Dergisi 2021 Vol.12 Issue 1, pp.47-52

Belge Tipi:

Makale

Yayın Tarihi:

1/2021

Belge Dili:

İngilizce

Document ID (Org No.):

2000949922

Sıklık:

Üç Aylık

eISSN:

2146-4391

pISSN:

1309-8640

DOI:

https://doi.org/10.24012/dumf.703171