Title :
Hybrid regression analysis for uncertainty modeling
Author :
Oscar Chang, Y.-H. ; Ayyub, Bilal M.
Author_Institution :
Maryland Univ., College Park, MD, USA
Abstract :
Hybrid regression analysis is proposed for modeling randomness and fuzziness in a regression model. For regression analysis involving fuzzy numbers, weighted fuzzy arithmetic is defined and used as a replacement for conventional fuzzy arithmetic. A method of hybrid least-squares linear regression is developed. Reliability measures for hybrid regression are also defined. A numerical example of hybrid regression is presented and compared with classical regression. Also, applications of hybrid regression for uncertainty modeling are summarized
Keywords :
arithmetic; fuzzy set theory; least squares approximations; modelling; reliability; statistical analysis; uncertainty handling; fuzziness; fuzzy numbers; hybrid least-squares linear regression; hybrid regression analysis; randomness; reliability measures; uncertainty modeling; weighted fuzzy arithmetic; Arithmetic; Educational institutions; Equations; Estimation error; Fuzzy sets; Humans; Linear regression; Probability; Regression analysis; Uncertainty;
Conference_Titel :
Fuzzy Information Processing Society, 1996. NAFIPS., 1996 Biennial Conference of the North American
Conference_Location :
Berkeley, CA
Print_ISBN :
0-7803-3225-3
DOI :
10.1109/NAFIPS.1996.534710
