An Analysis of Uneven Granules Clustering Based on Quotient Space
Ling Zhang · Jisuanji gongcheng · 2005
The fuzzy granules clustering based on the quotient space is discussed by the metric space. The cluster is a combination of information obtained from different granules in information fusion. Clustering with uneven granules in this way represents samples sets. By this means, a fuzzy clustering (FCluster) is proposed. In the clustering, the distance measure function, which is defined with Gaussian function between samples, is employed other than membership functions, fuzzy matrix, and the Gaussian width parameters are ignored. As the experiment showed, the approach advantage is: (1) the cluster is observed in different viewpoints; (2) the computational and special cost is saved; (3) it is efficient for the large number of observations; (4) Gaussian distance is able to achieve better accuracy to the synthetic control chart time series data sets.