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Nuclear shape transition has been actively studied in the past decade. Inparticular, the understanding of this phenomenon from a microscopic point ofview is of great importance. Because of this reason, many works have beenemployed to investigate shape phase transition in nuclei within therelativistic and non-relativistic mean field models by examining potentialenergy curves (PECs). In this paper, by using layered feed-forward neuralnetworks (LFNNs), we have constructed consistent empirical physical formulas(EPFs) for the PECs of 38-66Ti calculated in Hartree-Fock-Bogoliubov (HFB)method with SLy4 Skyrme forces. It has been seen that the PECs obtained byneural network method are compatible with those of HFB calculations.

Empirical physical formula for potential energy curves of 38-66Ti isotopes by using neural networks