Effect of the PSO Topologies on the Performance of the PSO-ELM

In recent years, the Extreme Learning Machine (ELM) has been hybridized with the Particle Swarm Optimization (PSO). This hybridization is named PSO-ELM. In most of these hybridizations, the PSO uses the global topology. However, other topologies were designed to improve the performance of the PSO. The performance of PSO depends on its topology, and there is not a best topology for all problems. Thus, in this paper, we investigate the effect of the PSO topology on performance of the PSO-ELM. In our study, we investigate five topologies: Global, Local, Von Neumann, Wheel and Four Clusters. The results showed that the Global topology can be more promising than all other topologies.