In this study, we utilized high-dimensional ANN proposed by for potential training. Such ANNs commonly operate in a feed-forward manner, transmitting signals in one direction through the layers. The ANN structure consists of interconnected nodes linked by weights, arranged in layers including input, hidden, and output layers. Firstly, atomic coordinate representations are fed into the input layer by converting each atomic position into a set of atomic symmetry functions {G i }, describing the chemical environment of the atom.