  One of the fundamental ground-state properties of nuclei is binding energy.
In this study, we have employed artificial neural networks (ANNs) to obtain
binding energies based on the data calculated from Hartree-Fock-Bogolibov (HFB)
method with the two SLy4 and SKP Skyrme forces. Also, ANNs have been employed
to obtain two-neutron and two-proton separation energies of nuclei. Statistical
modeling of nuclear data using ANNs has been seen as to be successful in this
study. Such a statistical model can be possible tool for searching in
systematics of nuclei beyond existing experimental nuclear data.
