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Issue:A measure of similarity for intuitionistic fuzzy sets

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http://ifigenia.org/wiki/issue:eusflat-2003-206-209
Title of paper: Remark on a special class of intuitionistic fuzzy sets
Author(s):
Eulalia Szmidt
Systems Research lnstitute - Polish Academy of Sciences, ul. Newelska 6, OL-447 Warsaw, Poland
szmidt@ibspan.waw.pl
Janusz Kacprzyk
Systems Research lnstitute - Polish Academy of Sciences, ul. Newelska 6, OL-447 Warsaw, Poland
kacprzyk@ibspan.waw.pl
Presented at: 3rd Conference of the European Society for Fuzzy Logic and Technology, Zittau, Germany, September 10-12, 2003
Published in: Conference proceedings, pages 206-209
Download:  PDF (115  Kb, Info)
Abstract: In this article we propose a new measure of similarity for intuitionistic fuzzy sets. The proposed measure takes into account not only a pure distance between elements but measures the whole missing information which may be necessary to say if the considered elements are more similar or more dissimilar. It is shown that even if a distance between objects is small it can happen that the objects are completely dissimilar.
Keywords: Intuitionistic fuzzy sets, Intuitionistic fuzzy distance, Similarity measure.
References:
  1. Atanassov K. (1999), Intuitionistic Fuzzy Sets: Theory and Applications. Springer-Verlag.
  2. Cross V. and Sudkamp T. (2002) Similarity and Compatibility in Fuzzy Set Theory. Physica-Verlag.
  3. Szmidt E. (2000): Applications of Intuitionistic Fuzzy Sets in Decision Making. (D.Sc.dissertation) Techn. Univ., Sofia, 2000.
  4. Szmidt E. and Kacprzyk J. (2000) Distances between intuitionistic fuzzy sets, Fuzzy Sets and Systems, Vol.114, No.3, pp.505—518.
  5. Szmidt E., Kacprzyk J. (2001) Entropy for intuitionistic fuzzy sets. Fuzzy Sets and Systems, vol. 118, No. 3, pp. 467—477.
  6. Szmidt E. and Kacprzyk J. (2002) Analysis of Agreement in a Group of Experts via Distances Between Intuitionistic Fuzzy Preferences. Proc. 9th Int. Conf. IPMU 2002, Annecy, France, July 1—5, pp. 1859—1865.
  7. Szmidt E. and Kacprzyk J.(2002b) An Intuitionistic Fuzzy Set Based Approach to Intelligent Data Analysis (an application to medical diagnosis). In A. Abraham, L. Jain, J. Kacprzyk (Eds.): Recent Advances in Intelligent Paradigms and Applications. Springer-Verlag, pp. 57-70.
  8. Szmidt E. and Kacprzyk J. (2002c) Evaluation of Agreement in a Group of Experts via Distances Between Intuitionistic Fuzzy Sets. Proc. IS’2002 - Int. IEEE Symposium: Intelligent Systems, Varna, Bulgaria, IEEECatalog Number 02EX499, pp. 166-170.
  9. Tversky A. (1977) Features of similarity. Psychol. Rev. Vol. 84, pp. 327—352.
  10. L.A. Zadeh (1965) Fuzzy sets. Information and Control, 8, 338—353.
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