DocumentCode
1917584
Title
A hierarchical neuro-fuzzy system based on S-implications
Author
Nowicki, Robert ; Scherer, Rafal ; Rutkowski, Leszek
Author_Institution
Dept. of Comput. Eng., Tech. Univ. Czestochowa, Poland
Volume
1
fYear
2003
fDate
20-24 July 2003
Firstpage
321
Abstract
In this paper, we present a neuro-fuzzy structure of the hierarchical prioritized structure (HPS) proposed by Yager. The HPS allows for easy hierarchization of a fuzzy rule-base. Our neuro-fuzzy system can be learned by the backpropagation algorithm and is relatively computationally efficient.
Keywords
backpropagation; fuzzy neural nets; hierarchical systems; S-implications; backpropagation algorithm; computationally efficient algorithm; fuzzy rule-base; hierarchical neuro-fuzzy system; hierarchical prioritized structure; Artificial intelligence; Backpropagation algorithms; Fuzzy neural networks; Fuzzy sets; Fuzzy systems; Hierarchical systems; Telephony;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2003. Proceedings of the International Joint Conference on
ISSN
1098-7576
Print_ISBN
0-7803-7898-9
Type
conf
DOI
10.1109/IJCNN.2003.1223365
Filename
1223365
Link To Document