ARTIFICIAL NEURAL NETWORK AND GENETIC ALGORITHM HYBRID TECHNIQUE FOR NUCLEUS-NUCLEUS 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 C(12), O(16), Si(28), and S(32) 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 GA-ANN simulation results prove a strong presence modeling in heavy ion collisions.
neural network genetic algorithm heavy ion collisions