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An Exponential-Type Entropy Measure on Intuitionistic Fuzzy Sets

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Artificial Intelligence and Soft Computing (ICAISC 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9119))

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Abstract

Entropy of an intuitionistic fuzzy set (IFS) is used to indicate the degree of fuzziness for IFSs. In this paper we deal with entropies of IFSs. We first review some existing entropies of IFSs and then propose a new entropy measure based on exponential operations for an IFS. Finally, comparisons are made with some existing entropies to show the effectiveness of our proposed one.

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Author information

Authors and Affiliations

  1. Department of Applied Mathematics, Chung Yuan Christian University, Chung-Li, 32023, Taiwan

    Yessica Nataliani & Miin-Shen Yang

  2. Department of Applied Mathematics, Chinese Culture University, Yangminshan, Taipei, Taiwan

    Chao-Ming Hwang

Authors
  1. Yessica Nataliani
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  2. Chao-Ming Hwang
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  3. Miin-Shen Yang
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Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  3. Częstochowa University of Technology, Częstochowa, Poland

    Rafal Scherer

  4. AGH University of Science and Technology, Krakow, Poland

    Ryszard Tadeusiewicz

  5. University of California, Berkeley, California, USA

    Lotfi A. Zadeh

  6. University of Louisville, Louisville, Kentucky, USA

    Jacek M. Zurada

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© 2015 Springer International Publishing Switzerland

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Nataliani, Y., Hwang, CM., Yang, MS. (2015). An Exponential-Type Entropy Measure on Intuitionistic Fuzzy Sets. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2015. Lecture Notes in Computer Science(), vol 9119. Springer, Cham. https://doi.org/10.1007/978-3-319-19324-3_20

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  • DOI: https://doi.org/10.1007/978-3-319-19324-3_20

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19323-6

  • Online ISBN: 978-3-319-19324-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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