Hybrid Fuzzy Regression Analysis Using the F-Transformopen access
- Authors
- Jung, Hye-Young; Lee, Woo-Joo; Choi, Seung Hoe
- Issue Date
- Oct-2020
- Publisher
- MDPI
- Keywords
- hybrid algorithm; fuzzy regression model; least absolute deviations estimation; F-transform
- Citation
- Applied Sciences-basel, v.10, no.19, pp.1 - 13
- Indexed
- SCIE
SCOPUS
- Journal Title
- Applied Sciences-basel
- Volume
- 10
- Number
- 19
- Start Page
- 1
- End Page
- 13
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/855
- DOI
- 10.3390/app10196726
- Abstract
- This paper proposes a hybrid estimation algorithm for independently estimating the response function for the center and the response function for the spread in fuzzy regression model. The proposed algorithm combines the least absolute deviations estimation with discriminant analysis. In addition, the F-transform is used to convert spreads of the dependent variable into several groups. Two examples show that our method is superior to the existing methods based on the fuzzy regression model that assumes the same function for spread and center.
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