Skip to main content
SpringerLink
Log in

Formulation and Simplification of Multi-Granulation Covering Rough Sets

  • Conference paper
Book cover Rough Sets and Intelligent Systems Paradigms

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8537))

Abstract

The theory of multi-granulation rough sets is one kind of effective methods for knowledge discovery in multiple granular structures. Based on rough sets on a single granular structure, various kinds of multi-granulation rough set models are proposed in the past decades. In this paper, according to two kinds of covering rough sets on single-granulation covering approximation spaces, four types of multi-granulation covering rough set models are defined. Properties of new models are examined in detail, comparison of multi-granulation covering approximation operators is done. Finally, simplification of four types of multi-granulation covering rough sets is investigated.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Chen, D.G., Wang, C.Z., Hu, Q.H.: A new approach to attribute reduction of consistent and inconsistent covering decision systems with covering rough sets. Information Sciences 177, 3500–3518 (2007)

    Article  MathSciNet  Google Scholar 

  2. Li, T.-J.: Rough approximation operators in covering approximation spaces. In: Greco, S., Hata, Y., Hirano, S., Inuiguchi, M., Miyamoto, S., Nguyen, H.S., Słowiński, R. (eds.) RSCTC 2006. LNCS (LNAI), vol. 4259, pp. 174–182. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  3. Lin, G., Liang, J., Qian, Y.: Multigranulation rough sets: From partition to covering. Information Sciences 241, 101–118 (2013)

    Article  MathSciNet  Google Scholar 

  4. Lin, G., Qian, Y., Li, J.: NMGRS: Neighborhood-based multigranulation rough sets. International Journal of Approximate Reasoning 53, 1080–1093 (2012)

    Article  MathSciNet  Google Scholar 

  5. Liu, C., Miao, D., Qian, J.: On multi-granulation covering rough sets. International Journal of Approximate Reasoning (2014), http://dx.doi.org/10.1016/j.ijar.2014.01.002

  6. Ma, L.W.: On some types of neighborhood-related covering rough sets. International Journal of Approximate Reasoning 53, 901–911 (2012)

    Article  MathSciNet  Google Scholar 

  7. Pawlak, Z.: Rough sets. International Journal of Computer and Information Sciences 11, 341–356 (1982)

    Article  MathSciNet  Google Scholar 

  8. Pomykala, J.A.: Approximation Operations in Approximation Space. Bulletin of the Polish Academy of Sciences: Mathematics 35, 653–662 (1987)

    MathSciNet  MATH  Google Scholar 

  9. Qian, Y.H., Liang, J.Y., Yao, Y.Y., Dang, C.Y.: MGRS: A multi-granulation rough set. Information Sciences 180, 949–970 (2010)

    Article  MathSciNet  Google Scholar 

  10. Qian, Y.H., Liang, J.Y., Wei, W.: Pessimistic rough decision. In: Second International Workshop on Rough Sets Theory, pp. 440–449 (2010)

    Google Scholar 

  11. Qian, Y., Zhang, H., Sang, Y., Liang, J.: Multigranulation decision-theoretic rough sets. International Journal of Approximate Reasoning 55, 225–237 (2014)

    Article  MathSciNet  Google Scholar 

  12. She, Y., He, X.: On the structure of the multigranulation rough set model. Knowledge-Based Systems 36, 81–92 (2012)

    Article  Google Scholar 

  13. Yang, X., Dou, H., Yang, J.: Hybrid multigranulation rough sets based on equivalence relation. Computer Science 39, 165–169 (2012) (A Chinese journal)

    Google Scholar 

  14. Yao, Y.Y., Wong, S.K.M.: A decision theoretic framework for approximating concepts. International Journal of Man-machine Studies 37, 793–809 (1992)

    Article  Google Scholar 

  15. Yao, Y.Y.: Relational interpretations of neighborhood operators and rough set approximation operators. Information Sciences 101, 239–259 (1998)

    Article  MathSciNet  Google Scholar 

  16. Yao, Y.Y., Yao, B.: Covering based rough set approximations. Information Sciences 200, 91–107 (2012)

    Article  MathSciNet  Google Scholar 

  17. Zakowski, W.: Approximations in the space (U, P). Demonstratio Mathematica IXV, 761–769 (1983)

    Google Scholar 

  18. Zhang, M., Tang, Z., Xu, W., Yang, X.: Variable multigranulation rough set model. Pattern Recognition and Artificial Intelligence 25, 709–720 (2012) (A Chinese journal)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Mathematics, Physics and Information Science, Zhejiang Ocean University, Zhoushan, Zhejiang, 316022, P.R. China

    Tong-Jun Li, Xing-Xing Zhao & Wei-Zhi Wu

Authors
  1. Tong-Jun Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xing-Xing Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Wei-Zhi Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Institute of Computer Science, Warsaw University of Technology, Nowowiejska 15/19, 00-665, Warsaw, Poland

    Marzena Kryszkiewicz  & Zbigniew W. Raś  & 

  2. Department of Computer Science and Artificial Intelligence, University of Granada, Calle del Periodista Daniel Saucedo Aranda s/n, 18071, Granada, Spain

    Chris Cornelis

  3. DISCo, Università di Milano – Bicocca, Viale Sarca 336 – U14, 20126, Milano, Italy

    Davide Ciucci

  4. Dpt. de Matemáticas, University of Càdiz, Spain

    Jesús Medina-Moreno

  5. School of Computing and Information Systems, University of Tasmania, Japan

    Hiroshi Motoda

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Li, TJ., Zhao, XX., Wu, WZ. (2014). Formulation and Simplification of Multi-Granulation Covering Rough Sets. In: Kryszkiewicz, M., Cornelis, C., Ciucci, D., Medina-Moreno, J., Motoda, H., Raś, Z.W. (eds) Rough Sets and Intelligent Systems Paradigms. Lecture Notes in Computer Science(), vol 8537. Springer, Cham. https://doi.org/10.1007/978-3-319-08729-0_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-08729-0_12

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08728-3

  • Online ISBN: 978-3-319-08729-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation