Fuzzy ARTMAP dynamic decay adjustment: An improved fuzzy ARTMAP model with a conflict resolving facility

Authors:
Shing Chiang Tan;M. V. C. Rao;Chee Peng Lim
Affiliations:
Faculty of Information Science and Technology, Multimedia University, Malaysia;Faculty of Engineering and Technology, Multimedia University, Malaysia;School of Electrical and Electronic Engineering, University of Science Malaysia, Malaysia
Venue:
Applied Soft Computing
Year:
2008

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Abstract

This paper presents a hybrid neural network classifier of fuzzy ARTMAP (FAM) and the dynamic decay adjustment (DDA) algorithm. The proposed FAMDDA model is a conflict-resolving classifier that can perform stable and incremental learning while settling overlapping of hyper-rectangular prototypes of different classes in minimizing misclassification rates. The performance of FAMDDA is evaluated using a number of benchmark data sets. The results are analyzed and compared with those from FAM and a number of machine learning classifiers. The outcomes show that FAMDDA has a better generalization capability than FAM, and its performance is comparable with those from other classifiers. The effectiveness of FAMDDA is also demonstrated in an application pertaining to condition monitoring of a circulating water system in a power generation station. Implications on the effectiveness of FAMDDA from the application point of view are discussed.