论文信息 - A New Approach to Modifying Fuzzy ARTMAP Systems

A New Approach to Modifying Fuzzy ARTMAP Systems

A fuzzy ARTMAP system is a system for incremental supervised learning of recognition categories and multidimensional maps in response to arbitrary sequence of analog or binary input vectors. The original fuzzy ARTMAP system incorporates two fuzzy ART modules and an inter-ART module. Many different approaches have been proposed to modify fuzzy ARTMAP systems. In this paper, we proposed a new approach to modifying a fuzzy ARTMAP system. We referred to the new system as the Modified and Simplified Fuzzy ARTMAP (MSFAM) system. Two data sets were used for demonstrating the performance of the proposed MSFAM systems. Keyword: neural networks, learning algorithm, ART

[1] Catherine Blake,et al. UCI Repository of machine learning databases , 1998 .

[2] Stephen Grossberg,et al. Fuzzy ARTMAP: A neural network architecture for incremental supervised learning of analog multidimensional maps , 1992, IEEE Trans. Neural Networks.

[3] M C Su,et al. Use of neural networks as medical diagnosis expert systems. , 1994, Computers in biology and medicine.

[4] Mu-Chun Su,et al. A neuro-fuzzy approach to speech recognition without time alignment , 1998, Fuzzy Sets Syst..

[5] Shigeo Abe,et al. A method for fuzzy rules extraction directly from numerical data and its application to pattern classification , 1995, IEEE Trans. Fuzzy Syst..

[6] P. K. Simpson. Fuzzy Min-Max Neural Networks-Part 1 : Classification , 1992 .

[7] Stephen Grossberg,et al. ARTMAP: supervised real-time learning and classification of nonstationary data by a self-organizing neural network , 1991, [1991 Proceedings] IEEE Conference on Neural Networks for Ocean Engineering.

[8] Donald F. Specht,et al. Probabilistic neural networks , 1990, Neural Networks.

[9] Mu-Chun Su,et al. Neural-network-based fuzzy model and its application to transient stability prediction in power systems , 1999, IEEE Trans. Syst. Man Cybern. Part C.