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.
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© 2012 Springer-Verlag Berlin Heidelberg
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Kim, WD., Oh, SK., Kim, HK. (2012). Context FCM-Based Radial Basis Function Neural Networks with the Aid of Fuzzy Clustering. In: Wang, J., Yen, G.G., Polycarpou, M.M. (eds) Advances in Neural Networks – ISNN 2012. ISNN 2012. Lecture Notes in Computer Science, vol 7367. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31346-2_3
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DOI: https://doi.org/10.1007/978-3-642-31346-2_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31345-5
Online ISBN: 978-3-642-31346-2
eBook Packages: Computer ScienceComputer Science (R0)