Neurofuzzy inference systems based on tribal particle swarm optimization for forecasting sunspot numbers

Abstract

This study presents tribal particle swarm optimization (TPSO) to optimize the parameters of the specific neurofuzzy inference system (NIS) for forecasting sunspot numbers. The proposed TPSO uses particle swarm optimization (PSO) as evolution strategies of the tribes optimization algorithm (TOA) to balance local and global exploration of the search space. Experimental results demonstrated that the proposed TPSO method converges quickly and yields a lower RMS error than other current methods.