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Non-monotonic Fuzzy Measures and Intuitionistic Fuzzy Sets

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Modeling Decisions for Artificial Intelligence (MDAI 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3885))

Abstract

Non-monotonic fuzzy measures induced by an intuitinistic fuzzy set are introduced. Then, using the Choquet integral with respect to the non-monotonic fuzzy measure, the weighted distance between two intuitionistic fuzzy sets is defined. As it will be shown here, under some conditions, the weighted distance coincides with the Hamming distance.

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Author information

Authors and Affiliations

  1. Toho Gakuen, 3-1-10 Naka, Kunitachi, Tokyo, 186-0004, Japan

    Yasuo Narukawa

  2. Institut d’Investigació en Intel.ligència Artificial, Campus de Bellaterra, 08193, Bellaterra, Catalonia, Spain

    Vicenç Torra

Authors
  1. Yasuo Narukawa
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  2. Vicenç Torra
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Editor information

Editors and Affiliations

  1. IIIA, Artificial Intelligence Research Institute CSIC, Spanish National Research Council, Campus UAB s/n, Catalonia, 08193, Bellaterra, Spain

    Vicenç Torra

  2. Toho Gakuen, 3-1-10 Naka, 186-0004, Tokyo, Kunitachi, Japan

    Yasuo Narukawa

  3. Department of Computer Science and Mathematics Intelligent Technologies for Advanced Knowledge Acquisition Research Group,, University Rovira i Virgili, Av. Països Catalans, 26., 43007, Tarragona, Catalonia, Spain

    Aïda Valls

  4. Department of Computer Engineering and Mathematics, Universitat Rovira i Virgili, UNESCO Chair in Data Privacy, Av. Països Catalans 26, E-43007, Tarragona, Catalonia, Spain

    Josep Domingo-Ferrer

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© 2006 Springer-Verlag Berlin Heidelberg

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Narukawa, Y., Torra, V. (2006). Non-monotonic Fuzzy Measures and Intuitionistic Fuzzy Sets. In: Torra, V., Narukawa, Y., Valls, A., Domingo-Ferrer, J. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2006. Lecture Notes in Computer Science(), vol 3885. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11681960_16

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  • DOI: https://doi.org/10.1007/11681960_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-32780-6

  • Online ISBN: 978-3-540-32781-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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