An Improved Fuzzy Reasoning Algorithm Based on TSK Model
Tao Wang, Yihui Tian, Yang Chen · 2009
In this paper, based on the traditional algorithm of TSK fuzzy reasoning model, a new fuzzy reasoning algorithm is proposed for two rules, two linguistic input variables and one output variable, in which the membership functions are Gaussian-type functions. By using neural network back-propagation algorithm, the parameters in the membership functions can be adjusted on-line without changing the rules. The proposed reasoning algorithm can overcome the weak firing or non-firing cases.