Online FCMAC-BYY Model with Sliding Window

Authors:
Jiacai Fu;Thi Tra Dang;Minh Nhut Nguyen;Daming Shi
Affiliations:
School of Electrical and Information Engineering, Heilongjiang Institute of Science and Technology, Harbin, China;School of Computer Engineering, Nanyang Technological University, Singapore 639798;School of Computer Engineering, Nanyang Technological University, Singapore 639798;School of Computer Engineering, Nanyang Technological University, Singapore 639798
Venue:
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II
Year:
2009

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Abstract

The online Bayesian Ying Yang (BYY) learning using clustering algorithm has been recently applied to Fuzzy CMAC in order to find the optimal centroids and widths of the fuzzy clusters. However, this BYY model is based on wholly-database, in which each data has a uniform contribution in forecasting future value, but it is not suitable for online applications in which the recent data are considered as more relevant. This research aims to propose an online learning algorithm for FCMAC-BYY based on sliding window. The experimental results show that the proposed model outperforms the existing representative techniques.