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Keywords: Interval type-2 fuzzy sets Ranking methods Similarity measures Uncertainty measures Computing with words a b s t r a c t Ranking methods, similarity measures and uncertainty measures are very important concepts for interval type-2 fuzzy sets (IT2 FSs). So far, there is only one ranking method for such sets, whereas there are many similarity and(More)
—In the previous paper, we have proposed linguistic weighted average (LWA) algorithms that can be used in distributed and hierarchical decision making. The original LWA algorithms were completely based on the representation theorem for interval type-2 fuzzy sets (IT2 FSs). In later usage, we found that when the lower membership functions (LMFs) of the(More)
Fuzzy logic is frequently used in computing with words (CWW). When input words to a CWW engine are modeled by interval type-2 fuzzy sets (IT2 FSs), the CWW engine's output can also be an IT2 FS, e A, which needs to be mapped to a linguistic label so that it can be understood. Because each linguistic label is represented by an IT2 FS e B i , there is a need(More)
—The perceptual computer (Per-C) is an architecture that makes subjective judgments by computing with words (CWWs). This paper applies the Per-C to hierarchical decision making, which means decision making based on comparing the performance of competing alternatives, where each alternative is first evaluated based on hierarchical criteria and subcriteria,(More)
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Abstract—Construction of interval type-2 fuzzy set models is the first step in the Perceptual Computer, an implementation of Computing with Words. The Interval Approach (IA) has been so far the only(More)