TSK-type recurrent fuzzy network design by the hybrid of genetic algorithm and particle swarm optimization

TSK-type recurrent fuzzy network (TRFN) design by the hybrid of genetic algorithm (GA) and particle swarm optimization (PSO), called HGAPSO, is proposed in this paper. In HGAPSO, individuals in a new generation are created, not only by crossover and mutation operation as in GA, but also by PSO. The concept of elite strategy is adopted in HGAPSO, and the group constituted by the elites is regarded as a swarm and is enhanced by PSO. These enhanced elites constitute half of the population in the new generation, whereas the other half is generated by performing crossover and mutation operations on these enhanced elites. Simulations on TRFN design by HGAPSO is compared to those by GA and PSO, demonstrating its superiority.