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Intuitionistic fuzzy linear regression analysis

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Abstract

Linear regression analysis in an intuitionistic fuzzy environment using intuitionistic fuzzy linear models with symmetric triangular intuitionistic fuzzy number (STriIFN) coefficients is introduced. The goal of this regression is to find the coefficients of a proposed model for all given input–output data sets. The coefficients of an intuitionistic fuzzy regression (IFR) model are found by solving a linear programming problem (LPP). The objective function of the LPP is to minimize the total fuzziness of the IFR model which is related to the width of IF coefficients. An illustrative example is also presented to depict the solution procedure of the IFR problem by using STriIFNs.

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Authors and Affiliations

  1. Department of Mathematics, Vellalar College for Women, Erode, Tamilnadu, 638012, India

    R. Parvathi

  2. Department of Mathematics, Gobi Arts and Science College, Gobi, Tamilnadu, 638456, India

    C. Malathi

  3. Punjab University College of Information Technology, University of the Punjab, Old Campus, Lahore, 54000, Pakistan

    M. Akram

  4. Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria

    Krassimir T. Atanassov

Authors
  1. R. Parvathi
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  2. C. Malathi
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  3. M. Akram
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  4. Krassimir T. Atanassov
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Correspondence to M. Akram.

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Parvathi, R., Malathi, C., Akram, M. et al. Intuitionistic fuzzy linear regression analysis. Fuzzy Optim Decis Making 12, 215–229 (2013). https://doi.org/10.1007/s10700-012-9150-9

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  • DOI: https://doi.org/10.1007/s10700-012-9150-9

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