Accelerated fuzzy C-means clustering algorithm

Doron Hershfinkel; Its'hak Dinstein

doi:10.1117/12.243263

14 June 1996 Accelerated fuzzy C-means clustering algorithm

Doron Hershfinkel, Its'hak Dinstein

Proceedings Volume 2761, Applications of Fuzzy Logic Technology III; (1996) https://doi.org/10.1117/12.243263
Event: Aerospace/Defense Sensing and Controls, 1996, Orlando, FL, United States

Abstract

The proposed accelerated fuzzy c-means (AFCM) clustering algorithm is an improved version of the fuzzy c-mean (FCM) algorithm. Each iteration of the proposed algorithm consists of the regular operations of the FCM algorithm followed by an improvement stage. Once the cluster center locations are updated by the regular FCM algorithm operations, the improvement stage shifts each cluster center farther in its respective update direction. A number of possible strategies for the shift size control are studied and evaluated. The AFCM was applied to a number of data sets, using hundreds of different initial cluster center sets, yielding reductions of 37% to 65% in the number of iterations required for convergence by a similar FCM algorithm.

Citation Download Citation

Doron Hershfinkel and Its'hak Dinstein "Accelerated fuzzy C-means clustering algorithm", Proc. SPIE 2761, Applications of Fuzzy Logic Technology III, (14 June 1996); https://doi.org/10.1117/12.243263

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