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Matrix Approaches for Variable Precision Rough Approximations

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Rough Sets and Knowledge Technology (RSKT 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9436))

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Abstract

Many generalizations of variable precision rough set models(VPRS) have been proposed since Ziarko introduced VPRS. This paper proposes the concept of general VPRS approximations which unifies earlier definitions of variant VPRS and gives an efficient matrix formulae for computing approximations of VPRS. This formulae can simplify the calculation of approximations of VPRS.

This work is supported by the National Natural Science Foundation of China (Nos. 60973148 and 61272031).

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Authors and Affiliations

  1. School of Information Science, Beijing Language and Culture University, Beijing, 100083, China

    Guilong Liu

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  1. Guilong Liu
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Correspondence to Guilong Liu .

Editor information

Editors and Affiliations

  1. University of Milano-Bicocca, Milano, Italy

    Davide Ciucci

  2. Chongqing University of Posts and Telecommunications, Chongqing, China

    Guoyin Wang

  3. Indian Statistical Institute, Kolkata, India

    Sushmita Mitra

  4. Zhejiang Ocean University, Zhejiang, China

    Wei-Zhi Wu

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Liu, G. (2015). Matrix Approaches for Variable Precision Rough Approximations. In: Ciucci, D., Wang, G., Mitra, S., Wu, WZ. (eds) Rough Sets and Knowledge Technology. RSKT 2015. Lecture Notes in Computer Science(), vol 9436. Springer, Cham. https://doi.org/10.1007/978-3-319-25754-9_19

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  • DOI: https://doi.org/10.1007/978-3-319-25754-9_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25753-2

  • Online ISBN: 978-3-319-25754-9

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