An efficient similarity measure for intuitionistic fuzzy sets
- 494 Downloads
We introduce a new methodology for measuring the degree of similarity between two intuitionistic fuzzy sets. The new method is developed on the basis of a distance defined on an interval by the use of convex combination of endpoints and also focusing on the property of min and max operators. It is shown that among the existing methods, the proposed method meets all the well-known properties of a similarity measure and has no counter-intuitive examples. The validity and applicability of the proposed similarity measure is illustrated with two examples known as pattern recognition and medical diagnosis.
KeywordsIntuitionistic fuzzy sets Similarity measures Distance measure Pattern recognition
The author thanks the editor-in-chief professor Antonio Di Nola and the referees for their helpful suggestions which improved the presentation of the paper.
- Atanassov KT (1999) Intuitionistic fuzzy sets: theory and application, studies in fuzziness and soft computing, vol 35. Physica, HeidelbergGoogle Scholar
- Huang GS, Liu YS, Wang XD (2005) Some new distances between intuitionistic fuzzy sets. In: Proceedings of the international conference on machine learning and cybernetics (ICMLC 05), pp 2478–2482, Guangzhou, ChinaGoogle Scholar
- Pal SK, King RA (1981) Image enhancement using smoothing with fuzzy sets. IEEE Trans Syst Man Cybernet 11:495–501Google Scholar
- Szmidt E, Kacprzyk J (2005) A new concept of a similarity measure for intuitionistic fuzzy sets and its use in group decision making. In: Torra V, Narukawa Y, Miyamoto S (eds) Modelling decision for artificial intelligence, LNAI 3558, Springer 272–282Google Scholar
- Wei GW, Lan G (2008) Grey relational analysis method for interval-valued intuitionistic fuzzy multiple attribute decision making. In: Fifth international conference on fuzzy systems and knowledge discovery, pp 291–295Google Scholar