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A Similarity Measure for Intuitionistic Fuzzy Sets and Its Application in Supporting Medical Diagnostic Reasoning

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Artificial Intelligence and Soft Computing - ICAISC 2004 (ICAISC 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3070))

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Abstract

We propose a new similarity measure for intuitionistic fuzzy sets and show its usefulness in medical diagnostic reasoning. We point out advantages of this new concept over the most commonly used similarity measures being just the counterparts of distances. The measure we propose involves both similarity and dissimilarity.

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References

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Author information

Authors and Affiliations

  1. Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01–447, Warsaw, Poland

    Eulalia Szmidt & Janusz Kacprzyk

Authors
  1. Eulalia Szmidt
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  2. Janusz Kacprzyk
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Editor information

Editors and Affiliations

  1. Department of Artificial Intelligence, Academy of Humanities and Economics, Poland

    Leszek Rutkowski

  2. German Research Center of Artificial Intelligence (DFKI), Germany

    Jörg H. Siekmann

  3. Institute of Automatics, AGH University of Science and Technology, Al. Mickiewicza 30, PL-30-059, Kraków, Poland

    Ryszard Tadeusiewicz

  4. Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Initiative in Soft Computing (BISC), 94720-1776, Berkeley, CA

    Lotfi A. Zadeh

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© 2004 Springer-Verlag Berlin Heidelberg

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Szmidt, E., Kacprzyk, J. (2004). A Similarity Measure for Intuitionistic Fuzzy Sets and Its Application in Supporting Medical Diagnostic Reasoning. In: Rutkowski, L., Siekmann, J.H., Tadeusiewicz, R., Zadeh, L.A. (eds) Artificial Intelligence and Soft Computing - ICAISC 2004. ICAISC 2004. Lecture Notes in Computer Science(), vol 3070. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24844-6_56

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  • DOI: https://doi.org/10.1007/978-3-540-24844-6_56

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22123-4

  • Online ISBN: 978-3-540-24844-6

  • eBook Packages: Springer Book Archive

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