1
Master's student, Department of Statistics, Faculty of Mathematical Sciences, University of Guilan
2
Professor, Department of Statistics, Faculty of Mathematical Sciences, University of Guilan
Abstract
In this article, the difference between classical regression and fuzzy regression is discussed. In fuzzy regression, both non-fuzzy and fuzzy data can be used for modeling. While in classical regression, only non-fuzzy data is used. The aim of the study is to examine the probabilistic regression method, the least squares regression method based on probabilistic regression, and the hybrid least squares linear regression method based on weighted fuzzy arithmetic for non-fuzzy input and fuzzy output using symmetrical triangular fuzzy numbers. In the following, the reliability measure, confidence interval, and goodness of fit criterion for selecting the optimal model are presented. Finally, the behavior of the proposed methods is examined by providing examples and the optimality of the hybrid fuzzy linear least squares regression model is shown.
Ehsani Jokandan, S. M. & Fathi vajirgah, B. (2020). Examining the capability of hybrid fuzzy regression based on comparison with other regression methods. Andishe_ye Amari, 24(2), 105-113.
MLA
Ehsani Jokandan, S. M., & Fathi vajirgah, B. "Examining the capability of hybrid fuzzy regression based on comparison with other regression methods", Andishe_ye Amari, 24, 2, 2020, 105-113.
HARVARD
Ehsani Jokandan S. M., Fathi vajirgah B. (2020). 'Examining the capability of hybrid fuzzy regression based on comparison with other regression methods', Andishe_ye Amari, 24(2), pp. 105-113.
CHICAGO
S. M. Ehsani Jokandan & B. Fathi vajirgah, "Examining the capability of hybrid fuzzy regression based on comparison with other regression methods," Andishe_ye Amari, 24 2 (2020): 105-113,
VANCOUVER
Ehsani Jokandan S. M., Fathi vajirgah B. Examining the capability of hybrid fuzzy regression based on comparison with other regression methods. Andishe_ye Amari. 2020;24(2):105-113 (In Persian).
