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基于前景理论的风险型语言决策方法

机译:基于前景理论的风险型语言决策方法

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基于前景理论方法,提出了一种语言风险型决策方法.首先,采用语言术语的形式对每一种风险状态下的各个选项进行评价;并据此构建语言决策矩阵.其次,将语言术语转化为三角模糊数;并将语言评价信息转化为数值型数据.然后,根据前景理论的思想,计算出概率权重函数与语言值函数,进而得到各选项的加权前景值.最后,根据加权前景值对各选项进行排序,并做出最优选择.该决策方法将决策者的心理偏好行为融入到实际决策过程中,并通过一个股票选择的应用实例验证了该方法的有效性.%Based on the prospect theory, a novel linguistic decision method under risk is proposed. First, the alternatives under each risk state are rated using linguistic terms, and the linguistic decision matrix is constructed. Secondly, the linguistic terms are transformed into triangular fuzzy numbers, so that the linguistic evaluations can be changed into numerical forms. Thirdly, with the aid of the prospect theory, the probability weight functions and the linguistic value functions can be computed, based on which the prospective values of the alternatives are obtained. Finally, the alternatives are ranked with respect to the prospective values combined of probability weight and linguistic value functions. Thus, the optimal choice is made. The decision process takes the psychological preferences of the decision maker into consideration. The practicality of the proposed method is illustrated through an application on stock selection problems.
机译:基于前景理论方法,提出了一种语言风险型决策方法.首先,采用语言术语的形式对每一种风险状态下的各个选项进行评价;并据此构建语言决策矩阵.其次,将语言术语转化为三角模糊数;并将语言评价信息转化为数值型数据.然后,根据前景理论的思想,计算出概率权重函数与语言值函数,进而得到各选项的加权前景值.最后,根据加权前景值对各选项进行排序,并做出最优选择.该决策方法将决策者的心理偏好行为融入到实际决策过程中,并通过一个股票选择的应用实例验证了该方法的有效性.%Based on the prospect theory, a novel linguistic decision method under risk is proposed. First, the alternatives under each risk state are rated using linguistic terms, and the linguistic decision matrix is constructed. Secondly, the linguistic terms are transformed into triangular fuzzy numbers, so that the linguistic evaluations can be changed into numerical forms. Thirdly, with the aid of the prospect theory, the probability weight functions and the linguistic value functions can be computed, based on which the prospective values of the alternatives are obtained. Finally, the alternatives are ranked with respect to the prospective values combined of probability weight and linguistic value functions. Thus, the optimal choice is made. The decision process takes the psychological preferences of the decision maker into consideration. The practicality of the proposed method is illustrated through an application on stock selection problems.

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