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

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 ex...

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Bibliographic Details
Published in:Radiation effects and defects in solids Vol. 176; no. 9-10; pp. 765 - 776
Main Authors: Isik, Esme, Isik, Ibrahim, Toktamis, Hüseyin
Format: Journal Article
Language:English
Published: Abingdon Taylor & Francis 03.10.2021
Taylor & Francis Ltd
Subjects:
Algorithms
Artificial neural network
Artificial neural networks
Back propagation networks
Computer simulation
Crystals
Data processing
Fading
glow curve
Glow curves
Information processing
Nervous system
Neural networks
Optimization
Quartz
Quartz crystals
Room temperature
Thermoluminescence
Transfer functions
ISSN:1042-0150, 1029-4953
Online Access:Get full text
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Summary: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.
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ISSN:1042-0150
1029-4953
DOI:10.1080/10420150.2021.1954000