Facebook metrics classifications using whale optimization algorithm and artificial neural network

This paper explores the official hybridization of two Artificial intelligence approaches for the ‘whale’ ‘optimization’ ‘algorithm’ (‘WOA’) and ‘artificial’ ‘neural’ ‘network’ (‘ANN’) on the Facebook metrics Estimate. The Whale optimization algorithm is a global search technique, while a local search method is the method of gradient backpropagation. In order to reduce the chances that an ANN slowly mixed with the local limit and converging to the global ideal, ANN has calculated the relationship between inputs and output variables, using the stochastic search power. The results of this study show that in contrast to the traditional neural back-propagation network (BPNN), the proposed model increase the convergence rate as well as predictable accuracy for the hybrid model (WOA-ANN).