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

被引:9
|
作者
Isik, Esme [1 ]
Isik, Ibrahim [2 ]
Toktamis, Huseyin [3 ]
机构
[1] Malatya Turgut Ozal Univ, Dept Optician, Malatya, Turkey
[2] Inonu Univ, Dept Elect & Elect Engn, Malatya, Turkey
[3] Gaziantep Univ, Dept Engn Phys, Gaziantep, Turkey
来源
RADIATION EFFECTS AND DEFECTS IN SOLIDS | 2021年 / 176卷 / 9-10期
关键词
Thermoluminescence; fading; Artificial neural network; glow curve;
D O I
10.1080/10420150.2021.1954000
中图分类号
TL [原子能技术]; O571 [原子核物理学];
学科分类号
0827 ; 082701 ;
摘要
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 beta-source at 70 Gy for stored in 64 h at room temperature.
引用
收藏
页码:765 / 776
页数:12
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