An efficient genetic algorithm for TSK‐type neural fuzzy identifier design
Cheng‐Jian Lin, Chi‐Yung Lee, Yongji Xu · Journal of the Chinese Institute of Engineers · 2006
In this paper, an efficient genetic algorithm (EGA) of the Takagi‐Sugeno‐Kang (TSK) ‐type neural fuzzy identifier (TNFI) is proposed for solving various identification problems. For the proposed EGA method, the better chromosomes will be initially generated while the better mutation points will be determined to perform efficient mutation. The advantages of the proposed learning algorithm are that, first, it converges quickly and the obtained fuzzy rules are precise. Secondly, the proposed EGA method only requires a small population sizes.