Title :
A Fuzzy Inference Method for Systems with Large Number of Rules
Author :
Bustan, Danyal ; Moodi, Hoda ; Pariz, Naser ; Azmoodeh, Nika
Author_Institution :
Ferdowsi Univ. of Mashhad
Abstract :
In this paper, a new fuzzy inference method which is suitable for systems with large number of rules, is proposed. As we know, there are two well-known fuzzy inference systems, Mamdani and TSK. Each one has its own drawbacks and advantages but both of them have been encountered with problem while tuning their parameters especially when there is large number of rules in the system. Mamdani type systems faced to a huge amount of calculation and TSK type faced to large number of parameters. In our proposed method a combination of these two systems, is used. So it has small number of parameters for tuning as Mamdani has and it is as fast as TSK. We called this system extended TSK because it is based upon it
Keywords :
fuzzy logic; fuzzy reasoning; fuzzy systems; Mamdani type systems; extended TSK type; fuzzy inference method; fuzzy modelling; Application software; Fuzzy logic; Fuzzy sets; Fuzzy systems; Humans; Input variables;
Conference_Titel :
Fuzzy Information Processing Society, 2006. NAFIPS 2006. Annual meeting of the North American
Conference_Location :
Montreal, Que.
Print_ISBN :
1-4244-0363-4
Electronic_ISBN :
1-4244-0363-4
DOI :
10.1109/NAFIPS.2006.365442