Title :
An Improved Fuzzy Reasoning Algorithm Based on TSK Model
Author :
Wang Tao ; Tian Yihui ; Chen Yang
Author_Institution :
Dept. of Basic Math., Liaoning Univ. of Technol., Jinzhou, China
Abstract :
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.
Keywords :
Gaussian processes; backpropagation; fuzzy reasoning; fuzzy set theory; neural nets; Gaussian type functions; TSK fuzzy reasoning model; neural network back propagation algorithm; nonfiring case; weak firing case; Backpropagation algorithms; Fuzzy logic; Fuzzy reasoning; Fuzzy set theory; Fuzzy sets; Gaussian processes; Input variables; Mathematical model; Mathematics; Neural networks;
Conference_Titel :
Innovative Computing, Information and Control (ICICIC), 2009 Fourth International Conference on
Conference_Location :
Kaohsiung
Print_ISBN :
978-1-4244-5543-0
DOI :
10.1109/ICICIC.2009.87
