A Regression Model for Fuzzy Initial Data

Authors:
V. G. Domrachev;O. M. Poleshuk
Affiliations:
Moscow State Forestry University, Mytishchi, Russia;Moscow State Forestry University, Mytishchi, Russia
Venue:
Automation and Remote Control
Year:
2003

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Abstract

A fuzzy combined linear regression model for fuzzy initial data, which are tolerant (L-R)-numbers with constraints on the functions L and R, is designed. The model is called combined since it is a combination of two regression models—a fuzzy model and a classical model. Its coefficients are determined as unimodal (L-R)-numbers. The solution method consists in determining weighted intervals for the tolerant (L-R)-numbers and then applying of the least-squares method.