The inclusion measure, the similarity measure, and the fuzziness of fuzzy sets are three important measures in fuzzy set theory. In this article, we investigate the relations among inclusion measures, similarity measures, and the fuzziness of fuzzy sets, prove eight theorems that inclusion measures, similarity measures, and the fuzziness of fuzzy sets can be transformed by each other based on their axiomatic definitions, and propose some new formulas to calculate inclusion measures, similarity measures, and the fuzziness of fuzzy sets. These results can be applied in many fields, such as pattern recognition, image processing, fuzzy neural networks, fuzzy reasoning, and fuzzy control. © 2006 Wiley Periodicals, Inc.
CITATION STYLE
Zeng, W., & Li, H. (2006). Inclusion measures, similarity measures, and the fuzziness of fuzzy sets and their relations. International Journal of Intelligent Systems, 21(6), 639–653. https://doi.org/10.1002/int.20152
Mendeley helps you to discover research relevant for your work.