Communications of the
Korean Mathematical Society
CKMS

ISSN(Print) 1225-1763 ISSN(Online) 2234-3024

Article

HOME ALL ARTICLES View

Commun. Korean Math. Soc. 2018; 33(3): 973-983

Online first article June 25, 2018      Printed July 31, 2018

https://doi.org/10.4134/CKMS.c170079

Copyright © The Korean Mathematical Society.

Fuzzy regression model with monotonic response function

Seung Hoe Choi, Hye-Young Jung, Woo-Joo Lee, Jin Hee Yoon

Korea Aerospace University, Seoul National University, Yonsei University, Sejong University

Abstract

Fuzzy linear regression model has been widely studied with many successful applications but there have been only a few studies on the fuzzy regression model with monotonic response function as a generalization of the linear response function. In this paper, we propose the fuzzy regression model with the monotonic response function and the algorithm to construct the proposed model by using $\alpha$-level set of fuzzy number and the resolution identity theorem. To estimate parameters of the proposed model, the least squares (LS) method and the least absolute deviation (LAD) method have been used in this paper. In addition, to evaluate the performance of the proposed model, two performance measures of goodness of fit are introduced. The numerical examples indicate that the fuzzy regression model with the monotonic response function is preferable to the fuzzy linear regression model when the fuzzy data represent the non-linear pattern.

Keywords: fuzzy regression model, monotonic response function, resolution identity theorem, LS method, LAD method

MSC numbers: 62J86

Stats or Metrics

Share this article on :

Related articles in CKMS

more +