Fuzzy ARTVar: an improved fuzzy ARTMAP algorithm

Author

Dagher, I. ; Georgiopoulos, M. ; Heileman, G.L. ; Bebis, G.

Author_Institution

Dept. of Electr. & Comput. Eng., Central Florida Univ., Orlando, FL, USA

Volume

3

fYear

1998

fDate

4-9 May 1998

Firstpage

1688

Abstract

We introduce a variation of the performance phase of fuzzy ARTMAP which is called Fuzzy ARTVar. Experimental results have shown that Fuzzy ARTVar exhibits superior generalization performance, compared to fuzzy ARTMAP, for a variety of machine learning databases. Furthermore, experimental results have also demonstrated that Fuzzy ARTVar compares favourably with other existing variations of fuzzy ARTMAP, such as ARTEMAP (power rule), ARTEMAPQ (Q-max rule), and Gaussian ARTMAP. The performance of Fuzzy ARTVar is independent of the tuning of network parameters, which is in contrast with the ARTEMAP, ARTEMAPQ, and Gaussian ARTMAP algorithms, whose performance depends on the choice of certain network parameters

Keywords

ART neural nets; fuzzy neural nets; generalisation (artificial intelligence); learning (artificial intelligence); pattern classification; performance evaluation; Fuzzy ARTVar; fuzzy ARTMAP algorithm; fuzzy neural networks; generalization; machine learning; pattern classification; performance evaluation; Computer science; Databases; Fuzzy logic; Lapping; Neural networks; Pattern classification; Radar; Reactive power; Sonar applications; Subspace constraints;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on

Conference_Location

Anchorage, AK

ISSN

1098-7576

Print_ISBN

0-7803-4859-1

Type

conf

DOI

10.1109/IJCNN.1998.687110

Filename

687110