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http://dx.doi.org/10.5391/JKIIS.2006.16.4.499

Fuzzy regression using regularlization method based on Tanaka's model  

Hong Dug-Hun (Department of Mathematics, Myongji University)
Kim Kyung-Tae (Department of Electronics and Electrical Information Engineering, Kyungwon University)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.16, no.4, 2006 , pp. 499-505 More about this Journal
Abstract
Regularlization approach to regression can be easily found in Statistics and Information Science literature. The technique of regularlization was introduced as a way of controlling the smoothness properties of regression function. In this paper, we have presented a new method to evaluate linear and non-linear fuzzy regression model based on Tanaka's model using the idea of regularlization technique. Especially this method is a very attractive approach to model non -linear fuzzy data.
Keywords
Fuzzy inference systems; Fuzzy regression; Regularlization methods;
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