DocumentCode
2271118
Title
Importance of membership functions: a comparative study on different learning methods for fuzzy inference systems
Author
Lotfi, A. ; Tsoi, A.C.
Author_Institution
Dept. of Electr. Eng., Queensland Univ., Brisbane, Qld., Australia
fYear
1994
fDate
26-29 Jun 1994
Firstpage
1791
Abstract
This paper investigates different adaptive structures for fuzzy inference systems. We examine the effect of membership functions on reasoning process when the number of rules is fixed. Three commonly used membership function shapes have been employed in this study. It has been shown that membership functions have the dominant effect on reasoning process rather than number of rules or inference mechanism. We compare our adaptive membership function scheme with two already proposed by others
Keywords
fuzzy systems; inference mechanisms; learning (artificial intelligence); adaptive structures; fuzzy inference systems; learning methods; membership function shapes; reasoning process; Fuzzy neural networks; Fuzzy reasoning; Fuzzy sets; Fuzzy systems; Inference mechanisms; Learning systems; Marine vehicles; Neural networks; Production; Shape;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems, 1994. IEEE World Congress on Computational Intelligence., Proceedings of the Third IEEE Conference on
Conference_Location
Orlando, FL
Print_ISBN
0-7803-1896-X
Type
conf
DOI
10.1109/FUZZY.1994.343588
Filename
343588
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