Enhanced interval type-2 fuzzy c-means algorithm with improved initial center

Pattern Recognition Letters

Volumn 38, Issue 1, 2014, Pages 86-92

  Qiu, Cunyong ^a   Xiao, Jian ^a   Han, Lu ^a   Naveed Iqbal, Muhammad ^a  

^a SOUTHWEST JIAOTONG UNIVERSITY   (China)

Author keywords

Fuzzy c means; Fuzzy clustering; Interval type 2 fuzzy set; Type reduction

Indexed keywords

CALCULATION TIME; CLUSTER CENTERS; COMPLEXITY OF ALGORITHM; FCM ALGORITHM; FUZZY C MEAN; INTERVAL TYPE-2 FUZZY; INTERVAL TYPE-2 FUZZY SETS; TYPE REDUCTION;

COPYING; FUZZY CLUSTERING; IMAGE PROCESSING; PATTERN RECOGNITION;

CLUSTERING ALGORITHMS;

EID: 84890812138     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patrec.2013.11.011     Document Type: Article

References (20)

1. A. Baraldi, and P. Blonda A survey of fuzzy clustering algorithms for pattern recognition. II IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 29 6 1999 786 801 (Pubitemid 32211616)
2. J.C. Bezdek Cluster validity with fuzzy sets Journal of Cybernetics 3 3 1973 58 73
3. J.C. Bezdek Fuzzy c-means cluster analysis Scholarpedia 6 7 2011 2057
4. O. Castillo, R. Martínez-Marroquín, P. Melin, F. Valdez, and J. Soria Comparative study of bio-inspired algorithms applied to the optimization of type-1 and type-2 fuzzy controllers for an autonomous mobile robot Information Sciences 192 2012 19 38
5. C. Hwang, and F.C.H. Rhee Uncertain fuzzy clustering: interval type-2 fuzzy approach to c-means IEEE Transactions on Fuzzy Systems 15 1 2007 107 120 (Pubitemid 46444307)
6. P.M. Kanade, and L.O. Hall Fuzzy ants and clustering IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans 37 5 2007 758 769 (Pubitemid 47323539)
7. N.N. Karnik, and J.M. Mendel Centroid of a type-2 fuzzy set Information Sciences 132 1 2001 195 220 (Pubitemid 32273094)
8. P. Kaur, A.K. Soni, and A. Gosain A robust kernelized intuitionistic fuzzy c-means clustering algorithm in segmentation of noisy medical images Pattern Recognition Letters 34 2 2012 163 175
9. A. Khosravi, S. Nahavandi, D. Creighton, and D. Srinivasan Interval type-2 fuzzy logic systems for load forecasting: a comparative study IEEE Transactions on Power Systems 27 3 2012 1274 1282
10. H.S. Kim, J.H. Kim, C.H. Ho, and P.S. Chu Pattern classification of typhoon tracks using the fuzzy c-means clustering method Journal Of Climate 24 2 2011 488 508
11. Q. Liang, and J.M. Mendel Interval type-2 fuzzy logic systems: theory and design IEEE Transactions on Fuzzy Systems 8 5 2000 535 550
12. Z. Liu, J. Dezert, G. Mercier, and Q. Pan Belief c-means: an extension of fuzzy c-means algorithm in belief functions framework Pattern Recognition Letters 33 3 2011 291 300
13. J.M. Mendel Uncertainty, fuzzy logic, and signal processing Signal processing 80 6 2000 913 933
14. J.M. Mendel Uncertain Rule-Based Fuzzy Logic Systems: Introduction and New Direction 2001 Prentice Hall Upper Saddle River, New Jersey, USA
15. J.M. Mendel Type-2 fuzzy sets and systems: an overview IEEE Computational Intelligence Magazine 2 1 2007 20 29
16. J.M. Pena, J.A. Lozano, and P. Larranaga An empirical comparison of four initialization methods for the k-means algorithm Pattern Recognition Letters 20 10 1999 1027 1040 (Pubitemid 32081295)
17. D. Wu, and J.M. Mendel Enhanced Karnik-Mendel algorithms IEEE Transactions on Fuzzy Systems 17 4 2009 923 934
18. M. Yedla, S.R. Pathakota, and T.M. Srinivasa Enhancing k-means clustering algorithm with improved initial center International Journal of Computer Science and Information Technologies 1 2 2010 121 125
19. M.E. Yuksel, and A. Basturk Application of type-2 fuzzy logic filtering to reduce noise in color images IEEE Computational Intelligence Magazine 7 3 2012 25 35
20. L.A. Zadeh The concept of a linguistic variable and its application to approximate reasoning - I Information Sciences 8 3 1975 199 249