Analysis and estimation of fading time from thermoluminescence glow curve by using artificial neural network

Abstract

The artificial neural network (ANN) is an information processing technology inspired by the information processing technique of the human brain. The way the simple biological nervous system works is imitated with ANN. In this study, an ANN model is proposed to analyze and simulate TL intensity of experimental data of quartz crystals with respect to the fading. In this model, network type and transfer function are chosen as the feed-forward backpropagation algorithm and Tansig respectively for the training of the proposed ANN model. The optimization process is also chosen as Levenberg–Marquardt in this study. The performance criteria of the proposed method were evaluated according to the coefficient of determination (R²) and mean-squared error (MSE) techniques. After simulation results are obtained, the TL glow curve of the prediction results of quartz crystal is obtained as a function of fading time irradiated with β-source at 70 Gy for stored in 64 h at room temperature.

KEYWORDS:

• Thermoluminescence
• fading
• Artificial neural network
• glow curve

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Esme Isik

Esme Isik interested in thermoluminescence, artificial neural network and sensor. She is working as an Assistant Prof at Malatya Turgut Ozal University since 2019.

Ibrahim Isik

Ibrahim Isik interested in molecular communication, artificial neural network and nano networks. He is working as an Assistant Prof at İnönü University since 2019.

Hüseyin Toktamis

Huseyin Toktamis interested in thermoluminescence, dosimeter and semiconductor. He is working as an Associate Prof at University of Gaziantep since 2016.