DocumentCode
2234112
Title
Adjusting fuzzy weights in fuzzy neural nets
Author
Feuring, Thomas ; Buckley, James J. ; Hayashi, Yoichi
Author_Institution
Inst. fur Inf., Munster Univ., Germany
Volume
2
fYear
1998
fDate
21-23 Apr 1998
Firstpage
402
Abstract
In order to train fuzzy neural nets fuzzy number weights have to be adjusted. Because fuzzy arithmetic automatically leads to monotonic increasing outputs a direct fuzzification of the backpropagation method does not work. Therefore, the focus is on other strategies like evolutionary algorithms. In this paper we suggest a backpropagation based method of adjusting the weights. Furthermore we can show that for the proposed method convergence can be guaranteed
Keywords
backpropagation; convergence; fuzzy neural nets; backpropagation based method; fuzzy arithmetic; fuzzy neural net training; fuzzy number weight adjustment; guaranteed convergence; monotonically increasing outputs; Arithmetic; Backpropagation algorithms; Computer science; Convergence; Error analysis; Fuzzy neural networks; Fuzzy sets; Fuzzy systems; Mathematics; Neural networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Knowledge-Based Intelligent Electronic Systems, 1998. Proceedings KES '98. 1998 Second International Conference on
Conference_Location
Adelaide, SA
Print_ISBN
0-7803-4316-6
Type
conf
DOI
10.1109/KES.1998.725940
Filename
725940
Link To Document