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Rough Set Based Fuzzy Modeling by Occupancy Degree and Optimal Partition of Projection

  • Chang-Woo Park
  • Young-Wan Cho
  • Jun-Hyuk Choi
  • Ha-Gyeong Sung
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3066)

Abstract

The rough set theory suggested by Pawlak has a property that it can represent the degree of consistency between condition and decision attributes of data pairs which don’t have linguistic information. In this paper, by using this ability of rough set theory, we define a measure called occupancy degree which can represent a consistency degree of premise and consequent variables in fuzzy rules describing experimental data pairs. We also propose a method by which we partition the projected data on input space and find an optimal fuzzy rule table and membership functions of input and output variables from data without preliminary linguistic information.

Keywords

Membership Function Fuzzy Rule Optimal Partition Fuzzy Partition Consequent Variable 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Chang-Woo Park
    • 1
  • Young-Wan Cho
    • 2
  • Jun-Hyuk Choi
    • 1
  • Ha-Gyeong Sung
    • 1
  1. 1.Precision Machinery Research CenterKorea Electronics Technology InstitutePuchon-Si, Kyunggi-DoKorea
  2. 2.Dept. of Electrical and Electronic Eng.Yonsei Univ 

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