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Symbolic fuzzy classification is proposed using fuzzy radial basis function network, with fuzzy c-medoids clustering at the hidden layer. Symbolic objects include linguistic, nominal, boolean and interval-type of features, along with quantitative attributes. Classification and clustering in this domain involve the use of symbolic dissimilarity between the(More)
This article constitutes a new method of clustering. The classical concept of fuzzy logic provides the means to represent approximate knowledge. Therefore the elements which lie in the boundaries of several sets are forced to belong to any of the sets. Introduction to fuzzy sets undoubtedly increases the computational burden, so there is an extension into(More)
This paper describes problem regarding pixel identification for image segmentation methodologies for big image dataset for real robust applications. For medical, urban or satellite images, segmentation process can done through high computing nodes for high I/O performance, low computing time by considering low overhead of transmission rate. Multi(More)
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