Browse > Article
http://dx.doi.org/10.5391/JKIIS.2009.19.1.102

An Interval Type-2 Fuzzy PCM Algorithm for Pattern Recognition  

Min, Ji-Hee (한양대학교 전자 컴퓨터 제어 계측 공학과)
Rhee, Frank Chung-Hoon (한양대학교 전자 컴퓨터 제어 계측 공학과)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.19, no.1, 2009 , pp. 102-107 More about this Journal
Abstract
The Possibilistic C-means(PCM) was proposed to overcome some of the drawbacks associated with the Fuzzy C-means(FCM) such as improved performance for noise data. However, PCM possesses some drawbacks such as sensitivity in initial parameter values and to patterns that have relatively short distances between the prototypes. To overcome these drawbacks, we propose an interval type 2 fuzzy approach to PCM by considering uncertainty in the fuzzy parameter m in the PCM algorithm.
Keywords
PCM; Type 2 Fuzzy Sets; Interval Type 2 Fuzzy Sets; Fuzzy Clustering;
Citations & Related Records
연도 인용수 순위
  • Reference
1 M. Bami, V. Cappellini, and A. Mecocci, 'Comments on 'A possibilistic approach to clustering,' IEEE Trans. Fuzzy Syst., Vol. 4, pp. 393-396, June 1996   DOI   ScienceOn
2 R. Krishnapuram and J. Keller, 'The Possibilistic C-means Algorithm.Insights and recommendations,' IEEE Trans. Fuzzy Sys., Vol. 4, pp. 385-393, 1996   DOI   ScienceOn
3 F. Rhee and C. Hwang, 'A type-2 fuzzy C-means clustering algorithm,' in Proc. 2001 Joint Conf. IFSA/NAFIPS, pp. 1926-1919, Jul 2001
4 F. Rhee and C. Hwang, 'An interval type-2 fuzzy C' spherical shells algorithm,' in Proc. 2004 Int. Conf. Vol. 2, pp. 11 Jul 2004
5 F. Rhee, 'Uncertain fuzzy clustering: insights and recommendations,' IEEE Computational Intelligence Magazine, Vol. 2, No.1, Feb 2007
6 F. Rhee and C. Hwang, 'An interval type-2 fuzzy perceptron,' in Proc. 2002 Int. Conf. Fuzzy Syst., Vol. 2, pp. 1331-1335, May 2001
7 N. Kamik, J Mendel, and Q. Liang. 'Type-2 fuzzy logic systems,' IEEE Trans. Fuzzy Syst., Vol. 7, pp. 643-658, Dec 1999   DOI   ScienceOn
8 F. Rhee and C. Hwang, 'Uncertain fuzzy clustering: interval type-2 fuzzy approach to ' IEEE Trsns. Fuzzy Vol. 15, No.1, pp. 107-120. Feb 2007   DOI   ScienceOn
9 F. Rhee and C. Hwang, 'An interval fuzzy J(-nearest neighbor,' in Proc. 2003 Int. Conf. Fuzzy Syst., Vol. 2, pp. 802-807. May 2003
10 R. Krishnapuram and J. Keller, 'The Possibilistic Approach to Clustering,' IEEE Trans. Fuzzy Syst., Vol. 1, No.2, pp. 98-110, May 1993   DOI   ScienceOn
11 J. S. Zhang and Y. W. Leung, 'Improved possibilistic c-means clustering algorithms,' IEEE Trans. Fuzzy Sys,. Vol. 12, No.2, April 2004
12 J. Mendel, Uncertain Rule-Based Fuzzy Logic Systems: Introduction and New Directions, Prentice Hall, 2001
13 J. Mendel, and It. John, 'Type-2 fuzzy set made simple,' IEEE Trans. Fuzzy Syst., Vol. 10, No. 2, April 2002
14 J. Bezdek, Pattern Recognition with Fuzzy Objective Function Algorithms, Plenum, 1981
15 Adam Schneider, 'Weighted Possibilistic c-Means Clustering Algorithms,' IEEE Int. Conf. Fuzzy Systems, Vol. 1, pp. 176-180, May 2000