Fuzzy Adaptive Resonance Theory Combining Overlapped Category in consideration of connections

Abstract— Adaptive Resonance Theory (ART) is an unsupervised neural network. Fuzzy ART (FART) is a variation of ART, allows both binary and continuous input patterns. However, Fuzzy ART has the category proliferation problem. In this study, to solve this problem, we propose a new Fuzzy ART algorithm: Fuzzy ART Combining Overlapped Category in consideration of connections (C-FART). C-FART has two important features. One is to make connections between similar categories. The other is to combine overlapping categories into with connections one category. We investigate the behavior of C-FART, and compare C-FART with the conventional FART.

• Type: Conference
• Year: 2008
• Where: IJCNN
• Authors: Haruka Isawa, Haruna Matsushita, Yoshifumi Nishio
• Keywords: Artificial Intelligence, Category Proliferation Problem, Fuzzy ART, Fuzzy ART Algorithm, IJCNN 2008