Newly developed semi-empirical formulas for (p,α) at 17.9 MeV and (p, np) at 22.3 MeV reaction cross-sections

Pramana ◽  
2010 ◽  
Vol 74 (6) ◽  
pp. 931-943 ◽  
Author(s):  
Eyyup Tel ◽  
Abdullah Aydin ◽  
E. Gamze Aydin ◽  
Abdullah Kaplan ◽  
Ömer Yavaş ◽  
...  
2021 ◽  
pp. 2150168
Author(s):  
Hasan Özdoğan ◽  
Yiğit Ali Üncü ◽  
Mert Şekerci ◽  
Abdullah Kaplan

In this paper, calculations of the [Formula: see text] reaction cross-sections at 14.5 MeV have been presented by utilizing artificial neural network algorithms (ANNs). The systematics are based on the account for the non-equilibrium reaction mechanism and the corresponding analytical formulas of the pre-equilibrium exciton model. Experimental results, obtained from the EXFOR database, have been used to train the ANN with the Levenberg–Marquardt (LM) algorithm which is a feed-forward algorithm and is considered one of the well-known and most effective methods in neural networks. The Regression [Formula: see text] values for the ANN estimation have been determined as 0.9998, 0.9927 and 0.9895 for training, testing and for all process. The [Formula: see text] reaction cross-sections have been reproduced with the TALYS 1.95 and the EMPIRE 3.2 codes. In summary, it has been demonstrated that the ANN algorithms can be used to calculate the [Formula: see text] reaction cross-section with the semi-empirical systematics.


2009 ◽  
Vol 28 (4) ◽  
pp. 377-384 ◽  
Author(s):  
E. Tel ◽  
C. Durgu ◽  
A. Aydın ◽  
M. H. Bölükdemir ◽  
A. Kaplan ◽  
...  

2010 ◽  
Vol 73 (3) ◽  
pp. 412-419 ◽  
Author(s):  
E. Tel ◽  
E. G. Aydın ◽  
A. Aydın ◽  
A. Kaplan ◽  
M. H. Bölükdemir ◽  
...  

Author(s):  
Akash Hingu ◽  
Siddharth Parashari ◽  
Suraj K. Singh ◽  
Bhargav Soni ◽  
S. Mukherjee

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