Fuzzy linear regression using rank transform method

Citations

WEB OF SCIENCE

44
Citations

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49

초록

In regression analysis, the rank transform (RT) method is known to be neither dependent on the shape of the error distribution nor sensitive to outliers. In this paper, we construct a so-called α-level fuzzy regression model based on the resolution identity theorem and apply RT method to this model. Fuzzy regression models with crisp input/fuzzy output and fuzzy input/fuzzy output are investigated to show the effectiveness of the proposed method. To compare its effectiveness with existing methods, we introduce a new performance measure. In addition, we propose a method to obtain a predicted output with respect to a specific target value and show that our model is more robust compared with other methods when the data contain some outliers.

키워드

PROGRAMMING APPROACHOUTLIERS DETECTIONMODELSINPUT
제목
Fuzzy linear regression using rank transform method
저자
JUNG, HYE YOUNGYoon, Jin HeeChoi, Seung Hoe
DOI
10.1016/j.fss.2014.11.004
발행일
2015-09
저널명
Fuzzy Sets and Systems
274
페이지
97 ~ 108