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Multiattribute decision making based on probability density functions and the variances and standard deviations of largest ranges of evaluating interval-valued intuitionistic fuzzy values

机译:基于概率密度函数的多元决策以及评估间隔内直觉模糊值最大范围的差异和标准偏差

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摘要

In this paper, we propose a new multiattribute decision making (MADM) method based on probability density functions (PDFs) and the variances and standard deviations of the largest ranges of evaluating interval-valued intuitionistic fuzzy values (IVIFVs). First, the proposed MADM method gets the largest range of each evaluating IVIFV in the decision matrix and calculates the average value of the largest ranges of each attribute. Then, it gets the PDF of the largest range of each evaluating IVIFV in the decision matrix, calculates the variance of each largest range and calculates the standard deviation of the largest ranges of each attribute. Then, it constructs the z-score decision matrix and gets the transformed weight of the interval-valued intuitionistic fuzzy (IVIF) weight of each attribute. Finally, it calculates the weighted score of each alternative based on the obtained z-score decision matrix and the transformed weight of the IVIF weight of each attribute. The larger the value of the weighted score, the better the preference order (PO) of the alternative. The proposed MADM method can overcome the drawbacks of the existing MADM methods. (C) 2019 Elsevier Inc. All rights reserved.
机译:在本文中,我们提出了一种基于概率密度函数(PDF)的新的多元决策(MADM)方法和评估间隔值直觉模糊值(IVIFV)的最大范围的差异和标准偏差。首先,所提出的MADM方法在决策矩阵中获得每个评估IVIFV的最大范围,并计算每个属性的最大范围的平均值。然后,它获得了决策矩阵中每个评估IVIFV的最大范围的PDF,计算每个最大范围的方差,并计算每个属性的最大范围的标准偏差。然后,它构造z评分判定矩阵,并获得每个属性的间隔值直觉模糊(IVIF)权重的转换权重。最后,它基于所获得的z评分判定矩阵和每个属性的IVIF权重的变换权重计算每个替代方案的加权分数。加权分数的值越大,替代方案的偏好顺序(PO)越好。拟议的MADM方法可以克服现有MADM方法的缺点。 (c)2019 Elsevier Inc.保留所有权利。

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