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JACIII Vol.2 No.2 pp. 54-61
doi: 10.20965/jaciii.1998.p0054
(1998)

Paper:

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

Youngwan Cho, Kichul Lee and Mignon Park

ICS Lab., Dept. of Electronic Eng., Yonsei Univ.
134, Shinchon-dong, Seodaemun-ku, Seoul, Korea

Received:
October 29, 1997
Accepted:
March 16, 1998
Published:
April 20, 1998
Keywords:
Rough set, Occupancy degree, Partitioning, Premise and consequent variables
Abstract

The rough set theory suggested by Pawlak represents the degree of consistency between conditions and decision attributes of data pairs that have no linguistic information. In this paper, by using this representation feature, we define a measure called the occupancy degree that represents the consistency degree of a 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. We examine the validity of the proposed method by modeling data pairs randomly generated by a fuzzy system.

Cite this article as:
Youngwan Cho, Kichul Lee, and Mignon Park, “Fuzzy Modeling by Occupancy Degree and Optimal Partition of Projection Using Rough Set Theory,” J. Adv. Comput. Intell. Intell. Inform., Vol.2, No.2, pp. 54-61, 1998.
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