Intuitionistic fuzzy set is a significance soft computing tool for curbing fuzziness embedded in decision‐making processes. To enhance the applicability of intuitionistic fuzzy sets in modelling practical real‐life problems, various computing methods have been proposed like distance measures, similarity measures and correlation measures. This paper proposes an intuitionistic fuzzy statistical correlation algorithm with applications to pattern recognition and diagnostic processes. This novel method assesses the magnitude of relationship and indicates whether the intuitionistic fuzzy sets under consideration are correlated in either positive or negative sense. We substantiate the proposed technique with some theoretical results and numerically validate it to be superior in terms of accuracy and reliability in contrast to some hitherto techniques. Finally, we determine decision‐making processes involving pattern recognition and diagnostic processes by using JAVA programming language to code the intuitionistic fuzzy statistical correlation measure.

中文翻译：

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直觉模糊统计相关算法在基于多准则的决策过程中的应用

直觉模糊集是一种重要的软计算工具，用于抑制决策过程中嵌入的模糊性。为了提高直觉模糊集在实际实际问题建模中的适用性，提出了各种计算方法，例如距离测度，相似度测度和相关度测度。本文提出了一种直观的模糊统计相关算法，并将其应用于模式识别和诊断过程。这种新颖的方法评估了关系的大小，并指出了所考虑的直觉模糊集是否在正向或负向相关。我们用一些理论结果证实了所提出的技术，并在数值上验证了它在准确性和可靠性方面优于某些迄今为止的技术。