A Study of Fuzzy C-Means Clustering Noise Processing Method 


Vol. 44,  No. 1, pp. 124-129, Jan.  2019
10.7840/kics.2019.44.1.124


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  Abstract

FCM(Fuzzy C-Means) algorithm finds the optimal solution through iterative optimization technique. In particular, the execution time differs depending on the initial center of clustering and the location and number of noise. In this paper, we propose a Delaunay Triangular-FCM(DT-FCM) noise canceling method to reduce the execution speed of FCM preprocessing. The triangle triangles are those that divide the space by connecting the points on the plane with triangles so that the minimum value of the interior angle of the triangles is the maximum. Experimental results show that the proposed method reduces execution time compared to existing FCM.

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  Cite this article

[IEEE Style]

K. Lee and J. Woo, "A Study of Fuzzy C-Means Clustering Noise Processing Method," The Journal of Korean Institute of Communications and Information Sciences, vol. 44, no. 1, pp. 124-129, 2019. DOI: 10.7840/kics.2019.44.1.124.

[ACM Style]

Kwang-Kyu Lee and Jung-Hyun Woo. 2019. A Study of Fuzzy C-Means Clustering Noise Processing Method. The Journal of Korean Institute of Communications and Information Sciences, 44, 1, (2019), 124-129. DOI: 10.7840/kics.2019.44.1.124.

[KICS Style]

Kwang-Kyu Lee and Jung-Hyun Woo, "A Study of Fuzzy C-Means Clustering Noise Processing Method," The Journal of Korean Institute of Communications and Information Sciences, vol. 44, no. 1, pp. 124-129, 1. 2019. (https://doi.org/10.7840/kics.2019.44.1.124)

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pISSN : 1226 - 4717
eISSN : 2287 - 3880