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. Howeve...Show MoreMetadata
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 the initial parameter values and to patterns that have relatively short distances between the prototypes. To overcome theses drawbacks, we propose an interval type-2 fuzzy approach to PCM by considering uncertainty in the fuzzy parameter m in the PCM algorithm.
Published in: 2009 IEEE International Conference on Fuzzy Systems
Date of Conference: 20-24 August 2009
Date Added to IEEE Xplore: 02 October 2009
ISBN Information:
Print ISSN: 1098-7584