新的犹豫模糊集相关系数及多属性决策应用

Novel Correlation Coefficients Between Hesitant Fuzzy Sets and Their Applications in Multi-attribute Decision Making

为解决犹豫模糊集相关系数违背统计学和随机过程直觉的问题,分析了现有相关系数的局限性,基于更严谨的数学相关系数定义模式,通过定义犹豫模糊集的方差和协方差提出新的犹豫模糊集相关系数计算方法.并考虑犹豫模糊属性权重的影响将其拓展为加权相关系数,最后将所提出的方法应用到多传感器多属性决策问题中.仿真试验验证了新的犹豫模糊集相关系数决策的有效性,并对比分析了相关系数计算性能和属性权重对的决策结果的影响.

In order to solve the problem that the traditional correlation coefficients between hesitant fuzzy sets are not conform to the statistics and the random process intuition,considering the more precise definition of correlation coefficient in mathematics we point out the drawbacks of the existing correlation coefficients and propose two correlation coefficient methods between hesitant fuzzy sets based on the variance and covariance of them. Meanwhile taking the attribute weight into account,we further extend the correlation coefficients into the weight correlation coefficients and apply them in multi-sensor decisionmaking problem. The validity of the proposed correlation coefficients to the decision making is illustrated in the simulation example and the capability of the two correlation coefficients as well as the influence of the attribute weight are also compared.