Affiliation:
1. Systems Research Institute Polish Academy of Sciences , ul. Newelska 6 , Warsaw , Poland
2. Warsaw School of Information Technology , ul. Newelska 6 , Warsaw , Poland
Abstract
Abstract
We discuss some aspects of similarity measures in the context of Atanassov’s intuitionistic fuzzy sets (IFSs, for short). IFSs, proposed in 1983, are a relatively new tool for the modeling and simulation and, because of their construction, present us with new challenges as far the similarity measures are concerned. Specifically, we claim that the distances alone are not a proper measure of similarity for the IFSs. We stress the role of a lack of knowledge concerning elements (options, decisions, etc.) and point out the role of the opposing (complementing) elements. We also pay attention to the fact that it is not justified to talk about similarity when one has not enough knowledge about the compared objects/elements. Some novel measures of similarity are presented.
Reference52 articles.
1. Atanassov, K. (1983) Intuitionistic Fuzzy Sets. VII ITKR Session. Sofia (Centr. Sci.-Techn. Libr. of Bulg. Acad. of Sci., 1697/84) (in Bulgarian).
2. Atanassov, K. T. (1999) Intuitionistic Fuzzy Sets: Theory and Applications. Springer-Verlag.10.1007/978-3-7908-1870-3
3. Atanassov, K.T. (2012) On Intuitionistic Fuzzy Sets Theory. Springer.10.1007/978-3-642-29127-2
4. Atanassova, V. (2004) Strategies for Decision Making in the Conditions of Intuitionistic Fuzziness. Int. Conf. 8th Fuzzy Days, Dortmund, Germany, 263–269.
5. Bujnowski, P., Szmidt, E. and Kacprzyk, J. (2014) Intuitionistic Fuzzy Decision Trees - a new Approach. In: L. Rutkowski et al., eds.: Artificial Intelligence and Soft Computing, Part I. Springer, Switzerland, 181–192.10.1007/978-3-319-07173-2_17
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献