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<p>The significance of correlation in predicting relationships between variables is highlighted within multi-criteria group decision-making (MCGDM) settings. In this study, novel correlation coefficient (CC) formulas are introduced for intuitionistic 2-tuple fuzzy linguistic (I2TFL) information, utilizing Dice and Cosine similarity measures to identify optimal alternatives. In addition, weighted correlation coefficients (WCCs) are introduced to address the varying importance among criteria. Key properties of the proposed CCs are validated, and a numerical example is presented to demonstrate the method’s effectiveness across diverse scenarios. Comparative analysis with traditional approaches underscores the potential benefits of this method in enhancing decision-making (DM) accuracy.</p>

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Correlation Coefficient Estimation in Intuitionistic 2-Tuple Fuzzy Linguistic Environment Using Dice and Cosine Similarity Measures

  • 期刊论文

  • 发表日期：

    2025年10月26日

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  • Muhammad Sajjad,
  • Shahzad Faizi,
  • Muhammad Ismail

摘要

The significance of correlation in predicting relationships between variables is highlighted within multi-criteria group decision-making (MCGDM) settings. In this study, novel correlation coefficient (CC) formulas are introduced for intuitionistic 2-tuple fuzzy linguistic (I2TFL) information, utilizing Dice and Cosine similarity measures to identify optimal alternatives. In addition, weighted correlation coefficients (WCCs) are introduced to address the varying importance among criteria. Key properties of the proposed CCs are validated, and a numerical example is presented to demonstrate the method’s effectiveness across diverse scenarios. Comparative analysis with traditional approaches underscores the potential benefits of this method in enhancing decision-making (DM) accuracy.