Abstract
The paper introduces a new approach to subtractive clustering algorithm (SC) with the fuzzifier parameter m which controls the clustering results in SC. And to manage the uncertainty of the parameter m, we have expanded the SC algorithm to interval type-2 fuzzy subtractive clustering algorithms (IT2-SC) using two fuzzifiers parameters m 1 and m 2 which creates a footprint of uncertainty (FOU) for the fuzzifier. The experiments are done based on image segmentation with the statistics show that the depends greatly on the parameter m of SC and stability and accuracy of our IT2-SC.
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Ngo, L.T., Pham, B.H. (2012). A Type-2 Fuzzy Subtractive Clustering Algorithm. In: Zhang, T. (eds) Mechanical Engineering and Technology. Advances in Intelligent and Soft Computing, vol 125. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27329-2_54
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DOI: https://doi.org/10.1007/978-3-642-27329-2_54
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-27328-5
Online ISBN: 978-3-642-27329-2
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