| Issue |
EPJ Web Conf.
Volume 146, 2017
ND 2016: International Conference on Nuclear Data for Science and Technology
|
|
|---|---|---|
| Article Number | 12033 | |
| Number of page(s) | 3 | |
| Section | Theory of Nuclear Reactions and Structure, Models and Codes | |
| DOI | https://doi.org/10.1051/epjconf/201714612033 | |
| Published online | 13 September 2017 | |
https://doi.org/10.1051/epjconf/201714612033
An approach to adjustment of relativistic mean field model parameters
1 Department of Nuclear Energy Engineering, Sinop University, Sinop, Turkey
2 Department of Physics, Cumhuriyet University, Sivas, Turkey
a e-mail: t.bayram@ymail.com
b e-mail: serkan.akkoyun@gmail.com
Published online: 13 September 2017
The Relativistic Mean Field (RMF) model with a small number of adjusted parameters is powerful tool for correct predictions of various ground-state nuclear properties of nuclei. Its success for describing nuclear properties of nuclei is directly related with adjustment of its parameters by using experimental data. In the present study, the Artificial Neural Network (ANN) method which mimics brain functionality has been employed for improvement of the RMF model parameters. In particular, the understanding capability of the ANN method for relations between the RMF model parameters and their predictions for binding energies (BEs) of 58Ni and 208Pb have been found in agreement with the literature values.
© The Authors, published by EDP Sciences, 2017
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