A Learning Algorithm of Artificial Neural Network Based on GA - PSO

Abstract

In order to get over the insufficiency of back-propagation (BP) algorithm, after analyses of genetic algorithm (GA) and particle swarm optimization (PSO), a GA-PSO algorithm is proposed. In GA-PSO, individuals in a new generation are created, not only by crossover and mutation operation in GA, but also by PSO, based on redefined local optimization swarm. So it can both avoid local minimum and has good global search capacity. The performance of GA-PSO is compared to both GA and PSO in artificial neural networks weight training, demonstrating its superiority