Skip to main content
SpringerLink
Log in
SpringerLink
Log in

An Attribute Reduction of Rough Set Based on PSO

  • Conference paper
Rough Set and Knowledge Technology (RSKT 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6401))

Included in the following conference series:

Abstract

The basic concept of attribute reduction in Rough Sets Theory (RST) and the idea of Particle Swarm Optimization(PSO) are briefly combined. A new reduction algorithm based on PSO is developed. Furthermore, the thought of Cache is introduced into the proposed method, which reduces the algorithm complexity effectively, The experimental results demonstrate that the algorithm is simple and viable.

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 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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Zeng, H.L.: Rough set theory and its application (Revision). Chongqing University Press, Chongqing (1998)

    Google Scholar 

  2. Pawlak, Z.: Rough sets: Theoretical aspects of reasoning about data. Springer, Heidelberg (1991)

    MATH  Google Scholar 

  3. Sadiq, W., Orlowska, M.: Analyzing process models using graph reduction techniques. Information systems 25, 117–134 (2000)

    Article  Google Scholar 

  4. Huang, J., Liu, C., Ou, C., Yao, Y., Zhong, N.: Attribute reduction of rough sets in mining market value functions. In: IEEE/WIC International Conference on Web Intelligence, pp. 470–473. IEEE Press, New York (2003)

    Google Scholar 

  5. Pawlak, Z.: Rough set theory and its applications. Journal of Telecommunications and information technology 134, 35–42 (2002)

    Google Scholar 

  6. Wu, W.: Attribute reduction based on evidence theory in incomplete decision systems. Information Sciences 178, 1355–1371 (2008)

    Article  MATH  MathSciNet  Google Scholar 

  7. Zhang, W., Wei, L., Qi, J., Zhang, W., Wei, L., Qi, J.: Attribute reduction theory and approach to concept lattice. Science in China Series F: Information Sciences 48, 713–726 (2005)

    Article  MATH  MathSciNet  Google Scholar 

  8. Wong, S., Ziarko, W.: On optimal decision rules in decision tables. Bulletin of Polish Academy of Sciences 33, 693–696 (1985)

    MATH  MathSciNet  Google Scholar 

  9. Shao-Hui, L., Qiu-Jian, S., Bin, W., Zhong-Zhi, S., Fei, H.: Research on efficient algorithms for rough set methods. Chinese journal of computers 26, 524–529 (2003)

    Google Scholar 

  10. Liang, J.Y., Qu, K.S., Xu, Z.B.: Reduction of Attribute in Information Systems. Systems Engineering-Theory and Practice 21, 76–80 (2001)

    Google Scholar 

  11. Tao, Z., Xu, B.D., Wang, D.W.: Rough Set Knowledge Reduction Approach Based on GA. Systems Engineering 21(4), 116–122 (2003)

    Google Scholar 

  12. Wang, G.Y., Wang, D.C.: Decision Table Reduction based on Conditional Information Entropy. Chinese Journal of Computers 25(7), 759–766 (2002)

    MathSciNet  Google Scholar 

  13. Xia, K.W., Liu, M.X., Zhang, Z.W.: An Approach to Attribute Reduction Based on Attribute Similarity. Journal of Hebei Unviersity of Technology 34(4), 20–23 (2005)

    Google Scholar 

  14. Kennedy, J., Eberhart, R.: Particle swarm optimization. In: IEEE International Conforence on Neural Networks, Piscataway, NJ, pp. 1942–1948 (1995)

    Google Scholar 

  15. Lee, K., Jhang, J.: Application of particle swarm algorithm to the optimization of unequally spaced antenna arrays. Journal of Electromagnetic Waves and Applications 20(14), 2001–2012 (2006)

    Article  Google Scholar 

  16. Parsopoulos, K., Vrahatis, M.: Particle swarm optimization method in multiobjective problems, pp. 603–607. ACM, New York (2002)

    Google Scholar 

  17. Parsopoulos, K., Vrahatis, M.: On the computation of all global minimizers through particle swarm optimization. IEEE Transactions on Evolutionary Computation 8(3), 211–224 (2004)

    Article  MathSciNet  Google Scholar 

  18. Cheng, G.C., Yu, J.S.: Particle Swarm Optimization Algorithm. Information and Control 34(3), 318–324 (2005)

    Google Scholar 

  19. Shen, H.Y., Peng, X.Q.: A multi-modality function optimization based on PSO algorithm. Journal of Hunan University of Science and Technology(Natural Science Edition) 20(3), 10–14 (2005)

    MathSciNet  Google Scholar 

  20. Clerc, M.: Particle swarm optimization. ISTE, London (2006)

    Book  MATH  Google Scholar 

  21. Hoa, S.N., Son, H.N.: Some efficient algorithms for rough set methods. In: The sixth international conference, Information Procesing and Management of Uncertainty in Knowledge-Based Systems, Granada, Spain, pp. 1451–1456 (1996)

    Google Scholar 

  22. Cache-Wikipedia, the free encyclopedia, http://en.wikipedia.org/wiki/Cache

Download references

Author information

Authors and Affiliations

  1. Key laboratory of knowledge processing and networked manufacturing, college of hunan province, Xiangtan, 411201, China

    Hongyuan Shen, Shuren Yang & Jianxun Liu

  2. Institute of Information and Electrical Engineering, Hunan University of Science and technology, Xiangtan, 411201, China

    Hongyuan Shen & Shuren Yang

Authors
  1. Hongyuan Shen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Shuren Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jianxun Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. School of Computer and Information Technology, Beijing Jiaotong University, 100044, Beijing, China

    Jian Yu

  2. Faculty of Economics, University of Catania, Corso Italia, 55, 95129, Catania, Italy

    Salvatore Greco

  3. Department of Mathematics and Computing Science, Saint Mary’s University, B3H 3C3, Halifax, Nova Scotia, Canada

    Pawan Lingras

  4. Institute of Computer Science and Technology, Chongqing University of Posts and Telecommunications, 400065, Chongqing, China

    Guoyin Wang

  5. Institute of Mathematics, Warsaw University, Banacha 2, 02-097, Warsaw, Poland

    Andrzej Skowron

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Shen, H., Yang, S., Liu, J. (2010). An Attribute Reduction of Rough Set Based on PSO. In: Yu, J., Greco, S., Lingras, P., Wang, G., Skowron, A. (eds) Rough Set and Knowledge Technology. RSKT 2010. Lecture Notes in Computer Science(), vol 6401. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16248-0_94

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-16248-0_94

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16247-3

  • Online ISBN: 978-3-642-16248-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation