Prediction of nano metal matrix composites based on hybrid approach

This manuscript proposes a hybrid method to predict the optimal nano-metal matrix composites. The proposed hybrid technique is the wrapper of the Fire-Hawk Optimizer (FHO) and Spiking Neural Network (SNN). Commonly it is known as FHO-SNN method. The main objective of the proposed method is to improve the method parameters for better enhancement in mechanical properties. FHO approach is used to improve the process parameters of stirring squeeze casting method. The SNN predicts optimal parameters. Moreover, the problem based on the casting is reduced. By then the proposed hybrid technique performance is performed in the MATLAB platform and associated with various existing approaches. The proposed system shows the high tensile strength, impact energy and hardness compared with other existing methods.