Skip to main content

Hybrid: A New Multigranulation Rough Set Approach

  • Conference paper
  • 1506 Accesses

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7414))

Abstract

Multigranulation is a new developing approach, which can be used for the constructing approximations of target concept. Optimistic multigranulation rough set is consistent to the disjunctive explanation of multigranulation structure while pessimistic multigranulation rough set is consistent to the conjunctive explanation of multigranulation structure. To study the multigranulation structure with both disjunctive and conjunctive explanations, the concept of hybrid multigranulation structure is firstly proposed. The hybrid multigranulation rough set is also proposed. The hybrid multigranulation structure and the corresponding rough set are generalizations of traditional multigranulation structures and rough sets, respectively.

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

Buying options

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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Pawlak, Z.: Rough sets–theoretical aspects of reasoning about data. Kluwer Academic Publishers (1992)

    Google Scholar 

  2. Yao, Y.Y.: Triarchic theory of granular computing. In: Zhang, Y.P., Luo, B., Yao, Y.Y., et al. (eds.) Quotient Space Theory and Granular Computing, Theory and Practice of Structured Problem Solving, pp. 115–143. Science Press, Beijing (2010) (in Chinese)

    Google Scholar 

  3. Qian, Y.H., Liang, J.Y., Dang, C.Y.: Incomplete multigranulation rough set. IEEE Transactions on Systems, Man and Cybernetics, Part A 20, 420–431 (2010)

    Article  Google Scholar 

  4. 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  MATH  Google Scholar 

  5. Qian, Y.H., Liang, J.Y., Wei, W.: Pessimistic rough decision. In: Second International Workshop on Rough Sets Theory, Zhoushan, P.R. China, October 19-21, pp. 440–449 (2010)

    Google Scholar 

  6. Xu, W.H., Wang, Q.R., Zhang, X.T.: Multi–granulation fuzzy rough sets in a fuzzy tolerance approximation space. International Journal of Fuzzy Systems 13, 246–259 (2011)

    Google Scholar 

  7. Yang, X.B., Song, X.N., Chen, Z.H., Yang, J.Y.: On multigranulation rough sets in incomplete information system. International Journal of Machine Learning and Cybernetics, doi:10.1007/s13042-011-0054-8

    Google Scholar 

  8. Yang, X.B., Song, X.N., Dou, H.L., Yang, J.Y.: Multi–granulation rough set: from crisp to fuzzy case. Annals of Fuzzy Mathematics and Informatics 1, 55–70 (2011)

    MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Yang, X., Yan, C., Chen, C., Yang, J. (2012). Hybrid: A New Multigranulation Rough Set Approach. In: Li, T., et al. Rough Sets and Knowledge Technology. RSKT 2012. Lecture Notes in Computer Science(), vol 7414. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31900-6_52

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-31900-6_52

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31899-3

  • Online ISBN: 978-3-642-31900-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics