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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, 1997Accepted:March 16, 1998Published: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:Y. Cho, K. Lee, and M. 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.Data files:
