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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| Published in: | Radiation effects and defects in solids Vol. 176; no. 9-10; pp. 765 - 776 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
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Abingdon
Taylor & Francis
03.10.2021
Taylor & Francis Ltd |
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| ISSN: | 1042-0150, 1029-4953 |
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| 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. |
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| AbstractList | 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. 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. |
| Author | Isik, Esme Isik, Ibrahim Toktamis, Hüseyin |
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| SubjectTerms | 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 |
| Title | Analysis and estimation of fading time from thermoluminescence glow curve by using artificial neural network |
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