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Redundant Data Processing Based on Rough-Fuzzy Approach

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Rough Sets and Knowledge Technology (RSKT 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4062))

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Abstract

In this paper, we will try to use fuzzy approach to deal with either incomplete or imprecise even ill-defined database and to use the concepts of rough sets to define equivalence class encoding input data, and eliminate redundant or insignificant attributes in data sets, and incorporate the significant factor of the input feature corresponding to output pattern classification to constitute a class membership function which enhances a mapping characteristic for each of object in the input space belonging to consequent class in the output space.

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Author information

Authors and Affiliations

  1. Electronics and Information Engineering Department, Sichuan University of Science & Engineering, Zigong, Sichuan, 643000, P.R. China

    Huanglin Zeng

  2. Department of Mathematics, Sichuan University of Science & Engineering, Zigong, Sichuan, 643000, P.R. China

    Hengyou Lan

  3. Department of Electronics and Engineering, Chengdu University of Information Technology, Chengdu, Sichuan, 610225, P.R. China

    Xiaohui Zeng

Authors
  1. Huanglin Zeng
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  2. Hengyou Lan
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  3. Xiaohui Zeng
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Editor information

Editors and Affiliations

  1. College of Computer Science and Technology, Chongqing, University of Posts and Telecommunication, 400065, Chongqing, P.R. China

    Guo-Ying Wang

  2. Department of Electrical and Computer Engineering, University of Manitoba, R3T 5V6, Winnipeg, Manitoba, Canada

    James F. Peters

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

    Andrzej Skowron

  4. Department of Computer Science, University of Regina, Regina,, S4S 0A2, Saskatchewan, Canada

    Yiyu Yao

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© 2006 Springer-Verlag Berlin Heidelberg

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Zeng, H., Lan, H., Zeng, X. (2006). Redundant Data Processing Based on Rough-Fuzzy Approach. In: Wang, GY., Peters, J.F., Skowron, A., Yao, Y. (eds) Rough Sets and Knowledge Technology. RSKT 2006. Lecture Notes in Computer Science(), vol 4062. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11795131_23

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  • DOI: https://doi.org/10.1007/11795131_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-36297-5

  • Online ISBN: 978-3-540-36299-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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