Automatic fuzzy rule extraction based on particle swarm optimization
Ming Ma, Chunguang Zhou, Libiao Zhang, Quansheng Dou · 2005
The extraction of fuzzy rules is always a difficult problem to fuzzy system. We have proposed a pruning algorithm to optimize fuzzy neural network based on particle swarm optimization algorithm. It can evolve both the fuzzy neural network's topology and weighting parameters. In a real problem, it can automatically obtain the near-optimal structure of fuzzy neural network according to the requirements. The experiment has proved that the method is applicable and efficient.