Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

On generalised intutionistic fuzzy divergence

On generalised intutionistic fuzzy divergence Atanassov (1986) defined the notion of intuitionistic fuzzy sets (IFS), which is a generalisation of the concept of fuzzy sets, introduced by the Zadeh (1965). Decision makers may not be able to accurately express their view for the problem as they may not possess a precise or sufficient knowledge of the problem or the decision makers are unable to discriminate explicitly the degree to which one alternative are better than others in such cases, the decision maker may provide their preferences for alternatives to certain degree, but it is possible that they are not so sure about it. Thus, it is very suitable to express the decision maker preference values with the use of fuzzy/intuitionistic fuzzy values rather than exact numerical values or linguistic variables (Szmidt and Kacprzyk, 2001, 1997, 2000). In the present communication, generalised measures of intutionistic fuzzy divergence with the proof of their validity are introduced. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Applied Systemic Studies Inderscience Publishers

On generalised intutionistic fuzzy divergence

Loading next page...
 
/lp/inderscience-publishers/on-generalised-intutionistic-fuzzy-divergence-NMz082Dgu1
Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd
ISSN
1751-0589
eISSN
1751-0597
DOI
10.1504/IJASS.2018.096119
Publisher site
See Article on Publisher Site

Abstract

Atanassov (1986) defined the notion of intuitionistic fuzzy sets (IFS), which is a generalisation of the concept of fuzzy sets, introduced by the Zadeh (1965). Decision makers may not be able to accurately express their view for the problem as they may not possess a precise or sufficient knowledge of the problem or the decision makers are unable to discriminate explicitly the degree to which one alternative are better than others in such cases, the decision maker may provide their preferences for alternatives to certain degree, but it is possible that they are not so sure about it. Thus, it is very suitable to express the decision maker preference values with the use of fuzzy/intuitionistic fuzzy values rather than exact numerical values or linguistic variables (Szmidt and Kacprzyk, 2001, 1997, 2000). In the present communication, generalised measures of intutionistic fuzzy divergence with the proof of their validity are introduced.

Journal

International Journal of Applied Systemic StudiesInderscience Publishers

Published: Jan 1, 2018

There are no references for this article.