Issue:Ranking intuitionistic fuzzy alternatives

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Title of paper: Inequalities with intuitionistic fuzzy topological and Gokhan Çuvalcioğlu's operators Author(s): Eulalia Szmidt Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01—447 Warsaw, Poland szmidt@ibspan.waw.pl Janusz Kacprzyk Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01—447 Warsaw, Poland kacprzyk@ibspan.waw.pl Presented at: 12th ICIFS, Sofia, 17—18 May 2008 Published in: "Notes on Intuitionistic Fuzzy Sets", Volume 14 (2008) Number 1, pages 48—56 Download:  PDF (166  Kb, File info) Abstract: We propose a method for ranking alternatives represented by Atanassov's intuitionistic fuzzy sets (A-IFSs) which takes into account not only the amount of information related to an alternative (expressed by a distance from the ideal positive alternative) but also the reliability of information (how sure the information is). We stress (like in our previous papers) that taking into account all three functions (membership, non-membership and hesitation) in the description of A-IFSs is the necessary condition to obtain results we intuitively expect. Keywords: Intuitionistic fuzzy set References: Atanassov K. (1983), Intuitionistic Fuzzy Sets. VII ITKR Session. Sofia (Centr. Sci.-Techn. Libr. of Bulg. Acad. of Sci., 1697/84) (in Bulgarian). Atanassov K. (1986) Intuitionistic fuzzy sets. Fuzzy Sets and Systems, 20, 87—96. Atanassov K. (1999), Intuitionistic Fuzzy Sets: Theory and Applications. Springer-Verlag. Chen S. M. and Tan J.M. (1994) Handling multi-criteria fuzzy decision-making problems based on vague-set theory. Fuzzy Sets and Systems 67(2), 163—172. Hong D.H. and Choi C.H. (2000) Multicriteria fuzzy decision making problems based on vague set theory. Fuzzy Sets and Systems 114, 103—113. Li F., Lu A., and Cai L. (2001) Methods of multi-criteria fuzzy decision making base on vague sets. 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Fuzzy Sets and Systems, 118 (3), 467—477. Szmidt E. and Kacprzyk J. (2002) 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, 57—70. 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, 1859—1865. Szmidt E. and Kacprzyk J. (2005) A New Concept of a Similarity Measure for Intuitionistic Fuzzy Sets and its Use in Group DecisionMaking. In V. Torra, Y. Narukawa, S. Miyamoto (Eds.): Modelling Decisions for Artificial Intelligence. LNAI 3558, 272—282. Szmidt E. and Kacprzyk J. (2006) Distances Between Intuitionistic Fuzzy Sets: Straightforward Approaches may not work. IEEE IS’06, 716—721. Szmidt E. and Kacprzyk J. (2006) An Application of Intuitionistic Fuzzy Set Similarity Measures to a Multi-criteria Decision Making Problem. ICAISC 2006, LNAI 4029, Springer-Verlag, 314—323. Szmidt E. and Kacprzyk J. (2007). Some problems with entropy measures for the Atanassov intuitionistic fuzzy sets. Applications of Fuzzy Sets Theory. LNAI 4578, 291—297. Springer-Verlag. Szmidt E. and Kacprzyk J. (2007a). A New Similarity Measure for Intuitionistic Fuzzy Sets: Straightforward Approaches may not work. 2007 IEEE Conf. on Fuzzy Systems, 481—486. Szmidt E. and Kacprzyk J. (2008). Ranking alternatives expressed via intuitionistic fuzzy sets. In press. Szmidt E. and Kukier M. (2006). Classification of Imbalanced and Overlapping Classes using Intuitionistic Fuzzy Sets. IEEE IS’06, London, 722-727. Szmidt E. and Kukier M. A New Approach to Classification of Imbalanced Classes via Atanassov’s Intuitionistic Fuzzy Sets. In Press. A chapter in ”Intelligent Data Analysis: Developing New Methodologies Through Pattern Discovery and Recovery. (Ed. Hsiao-Fan Wang). Zadeh L.A. (1965) Fuzzy sets. Information and Control, 8, 338—353. Citations: The list of publications, citing this article may be empty or incomplete. If you can provide relevant data, please, write on the talk page.