The new Belief C-Means (BCM) algorithm proposed in this paper follows this very simple principle. In BCM, the mass of belief of specific cluster for each object ...
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An extension of Fuzzy C-Means algorithm in belief functions ...
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Feb 1, 2012 · The new Belief C-Means (BCM) algorithm proposed in this paper follows this very simple principle. In BCM, the mass of belief of specific cluster ...
The well-known Fuzzy C-Means (FCM) algorithm for data clustering has been extended to Evidential C-Means (ECM) algorithm in order to work in the belief ...
Jun 14, 2021 · The well-known Fuzzy C-Means (FCM) algorithm for data clustering has been extended to Evidential. C-Means (ECM) algorithm in order to work ...
More precisely, the evidential version of fuzzy c-means (ECM) method has been proposed to deal with the clustering of proximity data based on an extension of ...
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Data clustering methods integrating information fusion techniques have been recently developed in the framework of belief functions.
A new clustering method called belief functions c-means (BFCM) is proposed, which outperforms ECM and FCM for the proximity data and Pignistic probability ...
In this paper, we extend the fuzzy rule in FRBCS with a belief rule structure and develop a belief rule-based classification system (BRBCS) to address imprecise ...
Jan 7, 2015 · ... C-Means (MECM), which is an extension of median c-means and median fuzzy c-means on the theoretical framework of belief functions is proposed.
Pan, Belief c-means: An extension of fuzzy c-means algorithm in belief functions framework, Pattern Recognition Letters, Vol. 33, pp. 291–. 300, 2012. [13] ...