Context FCM-based radial basis function neural networks with the aid of fuzzy clustering

Authors:
Wook-Dong Kim;Sung-Kwun Oh;Hyun-Ki Kim
Affiliations:
Department of Electrical Engineering, The University of Suwon, Hwaseong-si, Gyeonggi-do, South Korea;Department of Electrical Engineering, The University of Suwon, Hwaseong-si, Gyeonggi-do, South Korea;Department of Electrical Engineering, The University of Suwon, Hwaseong-si, Gyeonggi-do, South Korea
Venue:
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part I
Year:
2012

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Abstract

In this paper, we introduce architecture of context FCM-based Radial Basis Function Neural Networks realized with the aid of information granulation using clustering algorithm based on FCM and context FCM. The output space is defined by FCM while the input space a clustered by means of context FCM. The connection weights of proposed model are represented as three types of polynomials. Weighted Least Square Estimation (WLSE) is used to estimate the coefficients of polynomial (connection weight). The performance of the proposed model are illustrated with by using two kinds of representative numerical dataset such as Automobile Miles per Gallon, (MPG dataset) and Boston Housing dataset and their results are compared with those reported in the previous studies.