A Vector Similarity Measure for Interval Type-2 Fuzzy Sets

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, 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 Bi, there is a need to compare the similarity of A and Bi to find the Bi most similar to A. In this paper, a vector similarity measure (VSM) is proposed for IT2 FSs, whose two elements measure the similarity in shape and proximity, respectively. A comparative study shows that the VSM gives more reasonable results than all other existing similarity measures for IT2 FSs.

• Type: Conference
• Year: 2007
• Where: FUZZIEEE
• Authors: Dongrui Wu, Jerry M. Mendel
• Keywords: CWW Engine, FUZZIEEE 2007, Fuzzy Logic, Linguistic Label, Type-2 Fuzzy Sets