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In this paper, we present a novel fuzzy rule extraction approach by employing the Gaussian kernels and fuzzy concept lattices. First we introduce the Gaussian kernel to interval type-2 fuzzy rough sets to model fuzzy similarity relations and introduce a few concepts and theorems to improve the classification performance with fewer attributes accordingly. Based on this idea, we propose a novel attribute...
Context information plays an important role in text sequence recognition, but it is difficult to harness the uncertainty caused by conflicting implications. In this paper, we propose a novel Granular Transfer (GT) learning with type-2 fuzzy Hidden Markov Model (HMM) called GT2HMM, in which interpretable granules’ representation is introduced to describe the contextual uncertainty for its transfer...
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