FUZZY-RULE-BASED APPROXIMATORS IDENTIFICATION USING HYBRID QUANTUM-BEHAVED PARTICLE SWARM OPTIMIZATION
This paper focuses on using the hybrid particle quantum swarm algorithm to tune the parameters of fuzzy approximators. Simulation results confirm that the algorithm is a useful tool for tuning fuzzy systems to achieve better performance.
Keywords: identification, fuzzy approximator, quantum-behaved particle swarm optimization, cultural algorithm.
