DocumentCode
3119346
Title
An interval-based approach to fuzzy regression for fuzzy input-output data
Author
Chachi, Jalal ; Taheri, Sayed Mostafa ; Pazhand, H. Rezaei ; Geotechnical, Maharab
Author_Institution
Dept. of Math. Sci., Isfahan Univ. of Technol., Isfahan, Iran
fYear
2011
fDate
27-30 June 2011
Firstpage
2859
Lastpage
2863
Abstract
A novel approach is introduced to construct a fuzzy regression model when the data available of independent and dependent variables are fuzzy numbers. The approach, consisting on the least-squares method, uses the α-level sets of fuzzy observations to estimate the crisp parameters of the model. A competitive study shows the performance and efficiency of the proposed approach with respect to some well-known methods.
Keywords
fuzzy set theory; least squares approximations; regression analysis; α-level sets; fuzzy input-output data; fuzzy numbers; fuzzy observations; fuzzy regression model; interval based approach; least squares method; Data models; Estimation; Level set; Linear regression; Load modeling; Mathematical model; Numerical models; capability index; fuzzy regression; hydrology; interval arithmetic; least squares method;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems (FUZZ), 2011 IEEE International Conference on
Conference_Location
Taipei
ISSN
1098-7584
Print_ISBN
978-1-4244-7315-1
Electronic_ISBN
1098-7584
Type
conf
DOI
10.1109/FUZZY.2011.6007457
Filename
6007457
Link To Document