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New Similarity Measures on Intuitionistic Fuzzy Sets

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Fuzzy Information and Engineering

Part of the book series: Advances in Soft Computing ((AINSC,volume 40))

Abstract

Intuitionistic fuzzy sets, proposed by Atanassov, have gained attention from researchers for their applications in various fields. Then similarity measures between intuitionistic fuzzy sets were developed. In this paper, some examples are applied to show that some existing similarity measures are not effective in some cases. Then, based on the kind of geometrical background, we propose several new similarity measures of IFSs in which we consider three parameters describing a IFS. Finally, we apply these measures to pattern recognition.

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Author information

Authors and Affiliations

  1. Division of Mathematical Sciences, Pukyong National University, Pusan 608-737, South Korea

    Jin Han Park & Ki Moon Lim

  2. Department of Mathematics Education, Chinju National University of Education, Chinju 660-756, South Korea

    Jong Seo Park

  3. Department of Mathematics, Dong-A University, Pusan 604-714, South Korea

    Young Chel Kwun

Authors
  1. Jin Han Park
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  2. Jong Seo Park
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  3. Young Chel Kwun
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  4. Ki Moon Lim
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Editor information

Bing-Yuan Cao

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© 2007 Springer-Verlag Berlin Heidelberg

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Park, J.H., Park, J.S., Kwun, Y.C., Lim, K.M. (2007). New Similarity Measures on Intuitionistic Fuzzy Sets. In: Cao, BY. (eds) Fuzzy Information and Engineering. Advances in Soft Computing, vol 40. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71441-5_3

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  • DOI: https://doi.org/10.1007/978-3-540-71441-5_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-71440-8

  • Online ISBN: 978-3-540-71441-5

  • eBook Packages: EngineeringEngineering (R0)

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