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Generalized Correlation Coefficients of Intuitionistic Fuzzy Sets with Application to MAGDM and Clustering Analysis

机译:应用到MAGDM和聚类分析中的直观模糊集的广义相关系数

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摘要

Correlation coefficient between two variables plays an important role in statistics. Further, the perfection in quantification of correlation relies on data collected from the set of discourse. It is quite obvious that data collected for various statistical measures are full of ambiguity. In this communication, we propose one- and two-parametric generalization of correlation coefficient of intuitionistic fuzzy sets (IFSs). We show the application of one-parametric generalized correlation coefficient in multi-attribute group decision-making (MAGDM). We use normalized correlation efficiency as a measure of objective weights of the expertise of decision-experts in MAGDM problem. We also show the application of both generalized correlation coefficients in clustering analysis.
机译:两个变量之间的相关系数在统计数据中发挥着重要作用。此外,相关性的完美依赖于从谈话组中收集的数据。对于各种统计措施收集的数据充满了歧义是非常明显的。在这种通信中,我们提出了直觉模糊集(IFSS)的相关系数的一个和两个参数概括。我们展示了一个参数的广义相关系数在多属性组决策(MAGDM)中的应用。我们使用归一化相关效率作为MAGDM问题决策专家专业知识的客观权重的衡量标准。我们还展示了广义相关系数在聚类分析中的应用。

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