An approach to adjustment of relativistic mean field model parameters


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Bayram T. , AKKOYUN S.

2016 International Conference on Nuclear Data for Science and Technology, ND 2016, Bruges, Belgium, 11 - 16 September 2016, vol.146 identifier identifier

Abstract

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.