An approach to adjustment of relativistic mean field model parameters
[ X ]
Tarih
2017
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
E D P Sciences
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
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 Ni-58 and Pb-208 have been found in agreement with the literature values.
Açıklama
International Conference on Nuclear Data for Science and Technology (ND) -- SEP 11-16, 2016 -- Bruges, BELGIUM
Anahtar Kelimeler
Hartree-Bogoliubov Theory, Ground-State Properties
Kaynak
Nd 2016: International Conference On Nuclear Data For Science and Technology
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
Cilt
146
