Title :
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
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;
Conference_Titel :
Fuzzy Information Processing Society (NAFIPS), 2012 Annual Meeting of the North American
Conference_Location :
Berkeley, CA
Print_ISBN :
978-1-4673-2336-9
Electronic_ISBN :
pending
DOI :
10.1109/NAFIPS.2012.6290970
