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This paper introduces a new structure of radial basis function networks (RBFNs) that can successfully model symbolic interval-valued data. In the proposed structure, to handle symbolic interval data, the Gaussian functions required in the RBFNs are modified to consider interval distance measure, and the synaptic weights of the RBFNs are replaced by linear interval regression weights. In the linear...
In this study, the novel robust clustering algorithm, robust interval competitive agglomeration (RICA) clustering algorithm, is proposed to overcome the problems of the outliers and the numbers of cluster in the competitive agglomeration clustering algorithm for the symbolic interval-values data. The Euclidean distance measure is considered in the proposed RICA clustering algorithm. Moreover, the...
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