A novel parametric correlation coefficient for intuitionistic fuzzy numbers

Articles in Press

Document Type : Original Article

Author
Zahra Behdani
Department of Mathematics and Statistics, Faculty of Energy and Data Sciences, Behbahan Khatam Alanbia University of Technology, Khouzestan, Iran.
10.22034/jirss.2026.2082115.1173
Abstract
Correlation coefficients are widely used to measure the relationship between variables, but existing approaches for intuitionistic fuzzy numbers (IFNs) often fail to capture negative dependence and lack flexibility. In this paper, we propose a novel parametric correlation coefficient for IFNs based on a newly defined difference operator. The proposed method allows the correlation value to vary within the interval $[-1, 1]$, enabling the representation of both positive and negative relationships. Moreover, by introducing parameters $\alpha$ and $\beta$, the method provides flexibility for decision-makers to evaluate correlations at different levels. Numerical examples and applications in medical diagnosis and multi-criteria decision-making demonstrate the effectiveness, robustness, and practical applicability of the proposed approach. Correlation coefficients are widely used to measure the relationship between variables, but existing approaches for intuitionistic fuzzy numbers (IFNs) often fail to capture negative dependence and lack flexibility.
Keywords
Intuitionistic fuzzy correlation
Difference operator
Multi criteria
Fuzzy number
Subjects
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Journal of the Iranian Statistical Society

Articles in Press, Accepted Manuscript
Available Online from 28 July 2026

  • Receive Date 26 December 2025
  • Revise Date 08 June 2026
  • Accept Date 08 July 2026