scholarly journals Customer Satisfaction with Banking Services. Simulating the Influence of Customer Satisfaction Determinants Using Artificial Neural Network Algorithms

2021 ◽  
Vol 55 (4/2021) ◽  
pp. 101-115
Author(s):  
BADEA LEONARDO ◽  
MORARU ANDREEA-DANIELA ◽  
ILIE CONSTANTIN ◽  
DUHNEA CRISTINA ◽  
PANAIT IULIAN
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.


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