Generalized possibilistic c-means clustering based on differential evolution algorithm

2009 International Workshop on Intelligent Systems and Applications, ISA 2009

Volumn , Issue , 2009, Pages

  Fuheng, Qu ^a   Siliang, Ma ^a   Yating, Hu ^a  

^a JILIN UNIVERSITY   (China)

Author keywords

Clustering; Differential evolution algorithm; Feasible region; Fuzzy cmeans; Possibilistic c means

Indexed keywords

CLUSTERING; DIFFERENTIAL EVOLUTION ALGORITHM; FEASIBLE REGION; FUZZY CMEANS; POSSIBILISTIC C-MEANS;

DAMPING; EVOLUTIONARY ALGORITHMS; FUZZY CLUSTERING; GLOBAL OPTIMIZATION; INTELLIGENT SYSTEMS; OPTIMIZATION; PULSE CODE MODULATION;

CLUSTERING ALGORITHMS;

EID: 70349551852     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IWISA.2009.5072884     Document Type: Conference Paper

References (15)

1. J.C. Bezdek, Pattern recognition with fuzzy objective function algorithms, Plenum Press, New York, 1981.
2. R. Krishnapuram, J.M. Keller, "A possibilistic approach to clustering," IEEE Trans. Fuzzy Syst., vol. 1, no. 2, pp. 98-110, 1993.
3. R. Krishnapuram and J. Keller, "The possibilistic C-means algorithm: Insights and recommendations," IEEE Trans. Fuzzy Syst., vol. 4, no. 3, pp. 385-393, 1996.
4. M. Barni, V. Cappeppini, and A. Mecocci, "Comments on "A possibilistic approach to clustering"," IEEE Trans. Fuzzy syst., vol. 4, pp. 393-396, 1996.
5. H. Timm, C. Borgelt, C. Doring, and R. Kruse, Fuzzy cluster analysis with cluster repulsion, presented at the Euro. Symp. Intelligent Technologies (EUNITE), Tenerife, Spain, 2001.
6. H. Timm and R. Kruse, A modification to improve possibilistic fuzzy cluster analysis, presented at the IEEE Int. Conf. Fuzzy Systems, FUZZIEEE 2002, Honolulu, HI, 2002.
7. H. Timm, C. Borgelt, C. Doring, and R. Kruse, "An extension to possibilistic fuzzy cluster analysis," Fuzzy Sets Syst., vol. 147, pp. 3-16, 2004.
8. J.S. Zhang and Y.W. Leung, "Improved possibilistic C-means clustering algorithms," IEEE Trans. Fuzzy Syst., vol. 12, no. 2, pp. 209-217, 2004.
9. N.R. Pal, K. Pal, J.M. Keller and J.C. Bezdek, "A possibilistic fuzzy cmeans clustering algorithm," IEEE Trans. Fuzzy Syst., vol. 13, no. 4, pp. 517-530, 2005.
10. M.S. Yang and K.L. Wu, "Unsupervised possibilistic clustering," Pattern Recognit., vol. 39, no. 1, pp. 5-21, 2006.
11. R. Hathaway, J. C. Bezdek, and W. Tucker, "An improved convergence theory for the fuzzy ISODATA clustering algorithms," in Analysis of Fuzzy Information, J. Bezdek, Ed. Boca Rota, FL: CRC Press vol. 3, pp. 123-132, 1987.
12. R. Storn and K. Price, Differential evolution-a simple and efficient heuristic for global optimization over continuous spaces, J. Glob. Optim. vol. 11, no. 4, pp. 4-359, 1997.
13. K. Price, R. Storn, J. Lampinen, Differential evolution-a practical approach to global optimization, Springer, Berlin, 2005.
14. U. K. Chakraborty, Advances in differential evolution, Springer, Berlin, 2008.
15. C.L. Blake, C.J. Merz, UCI repository of machine learning databases, a huge collection of artificial and real-world data sets, 1998. Available from: http://mlearn.ics.uci.edu/MLRepository.html.