Automatic fuzzy rule extraction based on Tabu Search
Wei Zhang · Journal of Chongqing College of Education · 2007
In this paper,a hybrid Tabu Search algorithm based on fuzzy neural network(FNN-HTS) was proposed to generate an appropriate fuzzy rule set automatically through structure and parameters optimization of fuzzy neural network,where an intensification and diversification strategy was used to improve performance of primitive Tabu Search.In FNN-HTS,Tabu Search was used to optimize the network structure and membership function simultaneously,after which,Least Squares was used for the consequent parameters of the fuzzy rules.A simulation for a nonlinear function approximation was presented and the experimental results showed that the proposed algorithm can generate more refined rules with a lower average percentage error.