Artificial neural network and genetic algorithm hybrid technique for nucleusnucleus collisions

Selecting the optimal topology of a neural network for a particular application is a difficult task. Genetic Algorithm (GA) has been used to find the optimal neural network (NN) solution (i.e., hybrid technique) to calculate the pseudo-rapidity distribution of the shower particles for C¹², O¹⁶, Si²⁸, and S³² on nuclear emulsion. An efficient NN has been designed by GA to predict the distributions that are not present in the training set and matched them effectively. The proposed method shows a better fitting with experimental data. The hybrid technique GAANN simulation results prove a strong presence modeling in heavy ion collisions.