The application of fast clustering and statistic information optimal criterion to fuzzy modeling

A fast clustering method is presented, which can get cluster centering of sample data. The antecedent membership degree of T-S model is obtained by Gaussian membership function, then some important rules using orthogonal least-square and "objective" statistical information criterion are selected to reduce fuzzy model, and improve the pricision and genereli-zation ability of the fuzzy model. And the singular value decomposition is used to get consequent parameters. Finally, the effectiveness of this method is demonstrated by simulation.