A New Fast Algorithm for Fuzzy Rule Selection

Barbara Pizzileo, Kang Li
2007 IEEE International Fuzzy Systems conference proceedings  
This paper investigates the selection of fuzzy rules for fuzzy neural networks. The main objective is to effectively and efficiently select the rules and to optimize the associated parameters simultaneously. This is achieved by the proposal of a fast forward rule selection algorithm (FRSA), where the rules are selected one by one and a residual matrix is recursively updated in calculating the contribution of rules. Simulation results show that, the proposed algorithm can achieve faster
more » ... of fuzzy rules in comparison with conventional orthogonal least squares algorithm, and better network performance than the widely used error reduction ratio method (ERR). 1-4244-1210-2/07/$25.00 C 2007 IEEE.
doi:10.1109/fuzzy.2007.4295633 dblp:conf/fuzzIEEE/PizzileoL07 fatcat:r7qiasboavgpjfjf7gfpupxfsy