Analysis and estimation of fading time from thermoluminescence glow curve by using artificial neural network. Issue 9 (3rd October 2021)

• Record Type: Journal Article
• Authors: Isik, Esme; Isik, Ibrahim; Toktamis, Hüseyin
• Is Part Of: Radiation effects and defects in solids. Volume 176:Issue 9/10(2021)
• Page Start: 765
• Page End: 776
• Publication Date: 2021-10-03
• Subjects: Thermoluminescence -- fading -- Artificial neural network -- glow curve; Radiation chemistry -- Periodicals; Crystals -- Defects -- Periodicals; Crystal lattices -- Periodicals; 530.416
• DOI: 10.1080/10420150.2021.1954000
• Languages: English
• ISSNs: 1042-0150

Abstract

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 ( R 2 ) 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.