Fuzzy linear regression analysis from the point of view risk

Authors:
Mohammad Modarres;Ebrahim Nasrabadi;Mohammad Mehdi Nasrabadi
Affiliations:
Department of Industrial Engineering, Sharif University of Technology, Azadi Ave., Tehran 11365-8639, Iran;Faculty of Mathematics and Computer Science, Amirkabir University of Technology, No. 424, Hafez Ave. Tehran, Iran;Department of Mathematics, Payam Noor University of Birjand, Birjand, Iran
Venue:
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Year:
2005

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Abstract

In this paper, fuzzy linear regression models with fuzzy/crisp output, fuzzy/crisp input are considered. In this regard, we define risk-neutral, risk-averse and risk-seeking fuzzy linear regression models. In order to do that, two equality indices are applied to express the degree of equality between a pair of fuzzy numbers. We also develop three mathematical models to obtain the parameters of fuzzy linear regression models. Minimizing the difference between the total spread of the observed and estimated values is the objective of these models. The advantage of our proposed models is the simplicity in programming and computation.