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FUZZY REGRESSION MODEL WITH MONOTONIC

Title
FUZZY REGRESSION MODEL WITH MONOTONIC
Author
정혜영
Issue Date
2018-07
Publisher
Korean Mathematical Society
Citation
Communications of the Korean Mathematical Society, v. 33, No. 3, Page. 973-983
Abstract
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 α-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.
URI
http://koreascience.or.kr/article/JAKO201823955285239.pagehttps://repository.hanyang.ac.kr/handle/20.500.11754/127561
ISSN
1225-1763; 2234-3024
DOI
10.4134/CKMS.c170079
Appears in Collections:
COLLEGE OF SCIENCE AND CONVERGENCE TECHNOLOGY[E](과학기술융합대학) > APPLIED MATHEMATICS(응용수학과) > Articles
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