DocumentCode
2743503
Title
Investigation of automatic rule generation for hierarchical fuzzy systems
Author
Holve, Rainer
Author_Institution
Bavarian Res. Center for Knowledge-Based Syst., Erlangen, Germany
Volume
2
fYear
1998
fDate
4-9 May 1998
Firstpage
973
Abstract
The paper is based upon a method for the automatic generation of rules for hierarchical fuzzy associative memories (HIFAM). The effectiveness and termination of a general description of a training algorithm for HIFAMs is proved and experimental results on how HIFAMs evolve during training are given as well as a comparison with other machine learning techniques
Keywords
content-addressable storage; function approximation; fuzzy neural nets; fuzzy systems; inference mechanisms; learning (artificial intelligence); pattern classification; automatic rule generation; hierarchical fuzzy associative memories; hierarchical fuzzy systems; machine learning techniques; training algorithm; Associative memory; Binary trees; Fuzzy sets; Fuzzy systems; Knowledge based systems; Machine learning; Machine learning algorithms; Quantization; Training data; Tree data structures;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on
Conference_Location
Anchorage, AK
ISSN
1098-7584
Print_ISBN
0-7803-4863-X
Type
conf
DOI
10.1109/FUZZY.1998.686250
Filename
686250
Link To Document