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Information Journal Paper

Title

ESTIMATING THE PARAMETERS OF A FUZZY LINEAR REGRESSION MODEL

Pages

  1-19

Abstract

FUZZY LINEAR REGRESSION models are used to obtain an appropriate linear relation between a dependent variable and several independent variables in a fuzzy environment. Several methods for evaluating fuzzy coefficients in linear regression models have been proposed. The first attempts at estimating the parameters of a fuzzy regression model used mathematical programming methods. In this thesis, we generalize the metric defined by Diamond and use it as a criterion to ESTIMATE these parameters. Our method, is not only computationally easy to handle, but, when compared with earlier methods, has a smaller the sum of errors of estimation.

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  • Cite

    APA: Copy

    ARAB POUR, A.R., & TATA, M.. (2008). ESTIMATING THE PARAMETERS OF A FUZZY LINEAR REGRESSION MODEL. IRANIAN JOURNAL OF FUZZY SYSTEMS, 5(2), 1-19. SID. https://sid.ir/paper/113359/en

    Vancouver: Copy

    ARAB POUR A.R., TATA M.. ESTIMATING THE PARAMETERS OF A FUZZY LINEAR REGRESSION MODEL. IRANIAN JOURNAL OF FUZZY SYSTEMS[Internet]. 2008;5(2):1-19. Available from: https://sid.ir/paper/113359/en

    IEEE: Copy

    A.R. ARAB POUR, and M. TATA, “ESTIMATING THE PARAMETERS OF A FUZZY LINEAR REGRESSION MODEL,” IRANIAN JOURNAL OF FUZZY SYSTEMS, vol. 5, no. 2, pp. 1–19, 2008, [Online]. Available: https://sid.ir/paper/113359/en

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