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Grey-incidence clustering decision-making method with three-parameter interval grey number based on regret theory

机译:基于后悔理论的三参数区间灰数灰色关联聚类决策方法

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Aiming at the multiple attribute decision making problem with three-parameter interval grey numbers, a grey-incidence clustering decision making method based on regret theory is proposed in this paper. First, according to the idea of TOPSIS method, a kind of comprehensive grey interval incidence coefficient of three-parameter interval grey number is defined, and the “regret-rejoice” value is calculated out based on the grey interval relational coefficients, so the grey relational comprehensive perceptional utility of decision attribute value is obtained by adding the perceptive utility value of comprehensive grey interval incidence coefficient. Then, differing from the traditional grey-incidence clustering method, in this paper, grey clustering analysis is proceeded on the basis of the calculated matrix of comprehensive perceptional utility, so the comprehensive clustering results are achieved, and the ranking of the alternatives which are included in one class can be achieved too. Finally, the rationality and validity of the proposed method are verified by comparison analysis with an example.
机译:针对三参数区间灰数的多属性决策问题,提出了一种基于后悔理论的灰关联聚类决策方法。首先,根据TOPSIS法的思想,定义了一种三参数区间灰度数的综合灰度区间关联系数,并根据灰度区间相关系数计算出“后悔喜乐”值,因此决策属性值的关系综合感知效用是通过将综合灰色区间关联系数的感知效用值相加而获得的。然后,与传统的灰色关联聚类方法不同,本文在综合感知效用的计算矩阵的基础上进行了灰色聚类分析,从而获得了综合聚类结果,并对包括在内的替代方案进行了排序。一类也可以实现。最后,通过实例比较验证了所提方法的合理性和有效性。

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