Skip to main content

New Approach for Basic Rough Set Concepts

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3641))

Abstract

The standard rough set theory has been introduced in 1982 [5]. In this paper we use a topological concepts to investigate a new definitions for the lower and upper approximation operators. This approach is a generalization for Pawlak approach and the generalizations in [2, 7, 10, 12, 13, 14, 15, 16]. Properties of the suggested concepts are obtained. Also comparison between our approach and previous approaches are given. In this case, we show that the generalized approximation space is a topological space for any reflexive relation.

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   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
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. Allam, A.A., Bakeir, M.Y., Abo-Tabl, E.A.: A relational view to some basic topological concepts (submitted)

    Google Scholar 

  2. Kim, D.: Data classification based on tolerant rough set. Pattern Recognition 34, 1613–1624 (2001)

    Article  MATH  Google Scholar 

  3. Bloch, I.: On links between mathematical morphology and rough sets. Pattern Recognition 33, 1487–1496 (2000)

    Article  Google Scholar 

  4. Kortelainen, J.: On relationship between modified sets, topological spaces and rough sets. Fuzzy sets and systems 61, 91–95 (1994)

    Article  MATH  MathSciNet  Google Scholar 

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

    Article  MATH  MathSciNet  Google Scholar 

  6. Pawlak, Z.: Rough sets. In: Theoretical Aspects of Reasoning about Data. Kluwer Academic Publishers, Dordrecht (1991)

    Google Scholar 

  7. Pomykala, J.A.: Approximation operations in approximation space. Bulletin of the Polish Academy of Sciences, Mathematics 35, 653–662 (1987)

    MATH  MathSciNet  Google Scholar 

  8. Rasiowa, H.: An algebraic approach to non-classical logics. North-Holland, Amsterdam (1974)

    MATH  Google Scholar 

  9. Slowinski, R., Vanderpooten, D.: A Generalized Definition of Rough Approximations Based on Similarity. IEEE Transactions on Knowledge and Data Engineering 12(2), 331–336 (2000)

    Article  Google Scholar 

  10. Wybraniec-Skardowska, U.: On a generalization of approximation space. Bulletin of the Polish Academy of Sciences, Mathematics 37, 51–61 (1989)

    MATH  MathSciNet  Google Scholar 

  11. Yao, Y.Y.: Two views of the theory of rough sets in finite universes. International Journal of Approximation Reasoning 15, 291–317 (1996)

    Article  MATH  Google Scholar 

  12. Yao, Y.Y.: Constructive and algebraic methods of the theory of rough sets. Information Sciences 109, 21–47 (1998)

    Article  MATH  MathSciNet  Google Scholar 

  13. Yao, Y.Y.: Generalized rough set models. In: Polkowski, L., Skowron, A. (eds.) Rough Sets in Knowledge Discovery, pp. 286–318. Physica, Heidelberg (1998)

    Google Scholar 

  14. Yao, Y.Y.: Relational interpretations of neighborhood operators and rough set approximation operators. Information Sciences 111, 239–259 (1998)

    Article  MATH  MathSciNet  Google Scholar 

  15. Yao, Y.Y., Lin, T.Y.: Generalized of rough sets using model logic. Intelligent Automation and Soft Computing 2, 103–120 (1996)

    Google Scholar 

  16. Yao, Y.Y., Wong, S.K.M., Lin, T.Y.: A review of rough set models. In: Lin, T.Y., Cercone, N. (eds.) Rough Sets and Data Mining: Analysis for Imprecise Data, pp. 47–75. Kluwer Academic Publishers, Boston (1997)

    Google Scholar 

  17. Electronic Bulletin of Rough Set Community, http://www.cs.uregina.ca/~roughset

  18. Rough Set Database System, http://rsds.wsiz.rzeszow.pl/rsds.php

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Allam, A.A., Bakeir, M.Y., Abo-Tabl, E.A. (2005). New Approach for Basic Rough Set Concepts. In: Ślęzak, D., Wang, G., Szczuka, M., Düntsch, I., Yao, Y. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. RSFDGrC 2005. Lecture Notes in Computer Science(), vol 3641. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11548669_7

Download citation

  • DOI: https://doi.org/10.1007/11548669_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28653-0

  • Online ISBN: 978-3-540-31825-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics