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International Conference on Rough Sets and Intelligent Systems Paradigms

RSEISP 2007: Rough Sets and Intelligent Systems Paradigms pp 381–390Cite as

Attribute Reduction Based on Fuzzy Rough Sets

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4585))

Abstract

In T −fuzzy rough sets a fuzzy T −similarity relation is employed to describe the similar degree between two objects and to construct lower and upper approximations for arbitrary fuzzy sets. The existing researches on T −fuzzy rough sets mainly concentrate on constructive and axiomatic approaches of lower and upper approximation operators. In this paper we define attribute reduction based on T −fuzzy rough sets. The structure of proposed attribute reduction is investigated in detail by the approach of discernibility matrix. At last an example is proposed to illustrate our idea in this paper.

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Author information

Authors and Affiliations

  1. Department of Mathematics and Physics, North China Electric Power University, Beijing, 102206, P.R. China

    Degang Chen

  2. Department of Mathematics and Computer Science, Hebei University, Baoding, Hebei, 071002, P.R. China

    Xizhao Wang & Suyun Zhao

Authors
  1. Degang Chen
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  2. Xizhao Wang
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  3. Suyun Zhao
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Editor information

Marzena Kryszkiewicz James F. Peters Henryk Rybinski Andrzej Skowron

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© 2007 Springer-Verlag Berlin Heidelberg

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Chen, D., Wang, X., Zhao, S. (2007). Attribute Reduction Based on Fuzzy Rough Sets. In: Kryszkiewicz, M., Peters, J.F., Rybinski, H., Skowron, A. (eds) Rough Sets and Intelligent Systems Paradigms. RSEISP 2007. Lecture Notes in Computer Science(), vol 4585. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73451-2_40

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  • DOI: https://doi.org/10.1007/978-3-540-73451-2_40

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73450-5

  • Online ISBN: 978-3-540-73451-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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