Definition of initial tuning parameters by using fuzzy-exceeding ball clustering method
Wenyuan Liu, Kun Ma, Cheng-Yu Deng, Baowen Wang, Yan Hui Shi, Shu-Fen Fang · 2004
Very few of the suitable initial values of tuning parameters are argued in neuro-fuzzy algorithms, which are often used, so this can affect the nicety of the neuro-fuzzy algorithm. Although we can design initial tuning parameters by using the fuzzy c-means clustering algorithm before learning the corresponding fuzzy rules, the number of pattern collection must be known firstly. Thereby, we band the idea of fuzzy-exceeding ball with neuro-fuzzy network together, and adjust number, centers and widths of the ball, optimize the border pattern collection to confirm the weight values of parameters. We can minimize error and improve nicety of algorithm by using it.