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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