期刊
INFORMATION SCIENCES
卷 177, 期 4, 页码 988-1006出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2006.06.008
关键词
computing with words; fuzzistics; interval type-2 fuzzy sets; type-2 fuzzy sets; inverse problems
Words mean different things to different people, and so are uncertain. We, therefore, need a fuzzy set model for a word that has the potential to capture their uncertainties. In this paper I propose that an interval type-2 fuzzy set (IT2 FS) be used as a FS model of a word, because it is characterized by its footprint of uncertainty (FOU), and therefore has the potential to capture word uncertainties. Two approaches are presented for collecting data about a word from a group of subjects and then mapping that data into a FOU for that word. The person MF approach, in which each person provides their FOU for a word, is limited to fuzzy set experts because it requires the subject to be knowledgeable about fuzzy sets. The interval end-points approach, in which each person provides the end-points for an interval that they associate with a word on a prescribed scale is not limited to fuzzy set experts. Both approaches map data collected from subjects into a parsimonious parametric model of a FOU, and illustrate the combining of fuzzy sets and statistics-type-2 fuzzistics. (C) 2006 Elsevier Inc. All rights reserved.
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