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Rough Set Based Uncertain Knowledge Expressing and Processing

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Book cover Rough Sets, Fuzzy Sets, Data Mining and Granular Computing (RSFDGrC 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6743))

Abstract

Uncertainty exists almost everywhere. In the past decades, many studies about randomness and fuzziness were developed. Many theories and models for expressing and processing uncertain knowledge, such as probability & statistics, fuzzy set, rough set, interval analysis, cloud model, grey system, set pair analysis, extenics, etc., have been proposed. In this paper, these theories are discussed. Their key idea and basic notions are introduced and their difference and relationship are analyzed. Rough set theory, which expresses and processes uncertain knowledge with certain methods, is discussed in detail.

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Author information

Authors and Affiliations

  1. Institute of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China

    Guoyin Wang

Authors
  1. Guoyin Wang
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Editor information

Editors and Affiliations

  1. State University Higher School of Economics, Pokrovskiy Bd. 11, 109028, Moscow, Russia

    Sergei O. Kuznetsov

  2. Institute of Mathematics, University of Warsaw, ul. Banacha 2, 02-097, Warsaw, Poland

    Dominik Ślęzak

  3. Department of Computer Science, University of Regina, 3737 Wascana Parkway, S4S 0A2, Regina, SK, Canada

    Daryl H. Hepting

  4. Birbeck University of London, Malet Street, WC1E 7HX, London, UK

    Boris G. Mirkin

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© 2011 Springer-Verlag Berlin Heidelberg

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Wang, G. (2011). Rough Set Based Uncertain Knowledge Expressing and Processing. In: Kuznetsov, S.O., Ślęzak, D., Hepting, D.H., Mirkin, B.G. (eds) Rough Sets, Fuzzy Sets, Data Mining and Granular Computing. RSFDGrC 2011. Lecture Notes in Computer Science(), vol 6743. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21881-1_3

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  • DOI: https://doi.org/10.1007/978-3-642-21881-1_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21880-4

  • Online ISBN: 978-3-642-21881-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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