A novel two-stage algorithm of Fuzzy C-Means clustering

Fuzzy C-Means is one of the clustering algorithms based on optimizing an objective function. The selection of the initial parameters of the number and the initial cluster centers play an important influence in the performance of the FCM. This paper proposes a new FCM clustering algorithm with two stages. The proposed algorithm not only resolves the problem of the initial choice of the cluster center effectively, but also decreases the time when clustering large volume of data. The computer simulation results show the effectivity and the superiority of the new algorithm.

[1]  Lawrence O. Hall,et al.  Fast fuzzy clustering , 1998, Fuzzy Sets Syst..

[2]  Hung-Wei Liang.  A modified fuzzy C-means(MFCM) clustering algorithm , 2003 .

[3]  W. T. Tucker,et al.  Convergence theory for fuzzy c-means: Counterexamples and repairs , 1987, IEEE Transactions on Systems, Man, and Cybernetics.

[4]  Modified fast fuzzy C-means clustering algorithm , 2007 .

[5]  Qu Yingjie.  Design and Analysis of Interconnection Network of Reconfigurable Cryptographic Processor , 2009, 2009 Second International Workshop on Computer Science and Engineering.

[6]  Lawrence O. Hall,et al.  Fast Accurate Fuzzy Clustering through Data Reduction , 2003 .

[7]  Masahiro Oya,et al.  Stable adaptive fuzzy control of nonlinear systems preceded by unknown backlash-like hysteresis , 2003, IEEE Trans. Fuzzy Syst..

[8]  Jian Qiu Zhang,et al.  Improvement and optimization of a fuzzy C-means clustering algorithm , 2001, IMTC 2001. Proceedings of the 18th IEEE Instrumentation and Measurement Technology Conference. Rediscovering Measurement in the Age of Informatics (Cat. No.01CH 37188).

[9]  Don-Lin Yang,et al.  An efficient Fuzzy C-Means clustering algorithm , 2001, Proceedings 2001 IEEE International Conference on Data Mining.

[10]  S. Chiu,et al.  A cluster estimation method with extension to fuzzy model identification , 1994, Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference.