Antalya Bilim University, Vocational School of Health Services, Department of Medical Imaging Techniques, 07190, Antalya, Turkey.
Akdeniz University, Vocational School of Technical Sciences, Department of Biomedical Equipment Technology, 07070, Antalya, Turkey.
Appl Radiat Isot. 2021 Mar;169:109581. doi: 10.1016/j.apradiso.2020.109581. Epub 2021 Jan 5.
In this study; Giant Dipole Resonance (GDR) parameters of the spherical nucleus have been estimated by using artificial neural network (ANN) algorithms. The ANN training has been carried out with the Levenberg-Marquardt feed-forward algorithm in order to provide fast convergence and stability in ANN training and experimental data, taken from Reference Input Parameter Library (RIPL). R values of the system have been found as 0.99636, 0.94649, and 0.98318 for resonance energy, full width half maximum, and resonance cross-section, respectively. Obtained results have been compared with the GDR parameters which are taken from the literature. To validate our findings, newly acquired GDR parameters were then replaced with the existing GDR parameters in the TALYS 1.95 code and Nd(γ,n)Nd reaction cross-sections have been calculated and compared with the experimental data taken from the literature. As a result of the study, it has been shown that ANN algorithms can be used to calculate the GDR parameters in the absence of the experimental data.
在这项研究中，使用人工神经网络（ANN）算法估计了球形核的巨偶极共振（GDR）参数。为了在 ANN 训练和实验数据中提供快速收敛和稳定性，使用了 Levenberg-Marquardt 前馈算法进行 ANN 训练，实验数据取自参考输入参数库（RIPL）。对于共振能量、全宽半最大值和共振截面，系统的 R 值分别为 0.99636、0.94649 和 0.98318。获得的结果与文献中的 GDR 参数进行了比较。为了验证我们的发现，然后将新获得的 GDR 参数替换到 TALYS 1.95 代码中的现有 GDR 参数中，并计算了 Nd(γ,n)Nd 反应截面，并与文献中取自实验的数据进行了比较。研究结果表明，在没有实验数据的情况下，可以使用 ANN 算法来计算 GDR 参数。
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