A fuzzy linear regression model for interval type-2 fuzzy sets

Author

Poleshchuk, O. ; Komarov, E.

Author_Institution

Dept. of Electron. & Comput., Moscow State Forest Univ., Moscow, Russia

fYear

2012

fDate

6-8 Aug. 2012

Firstpage

1

Lastpage

5

Abstract

This paper presents a regression model for interval type-2 fuzzy sets based on the least squares estimation technique. Unknown coefficients are assumed to be triangular fuzzy numbers. The basic idea is to determine aggregation intervals for type-1 fuzzy sets, membership functions of whose are low membership function and upper membership function of interval type-2 fuzzy set. These aggregation intervals were called weighted intervals. Low and upper membership functions of input and output interval type-2 fuzzy sets for developed regression models are considered as piecewise linear functions.

Keywords

fuzzy set theory; least squares approximations; piecewise linear techniques; regression analysis; aggregation intervals; fuzzy linear regression model; interval type-2 fuzzy sets; least squares estimation technique; low membership function; piecewise linear functions; triangular fuzzy numbers; type-1 fuzzy sets; upper membership function; weighted intervals; Computational modeling; Data models; Frequency selective surfaces; Fuzzy sets; Linear regression; Support vector machines; fuzzy regression; hibrid fuzzy least-squares regression; interval type-2 fuzzy sets; weighted interval;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Information Processing Society (NAFIPS), 2012 Annual Meeting of the North American

Conference_Location

Berkeley, CA

ISSN

pending

Print_ISBN

978-1-4673-2336-9

Electronic_ISBN

pending

Type

conf

DOI

10.1109/NAFIPS.2012.6290970

Filename

6290970