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Triangular intuitionistic fuzzy random decision making based on combination of parametric estimation, score functions, and prospect theory

机译:基于参数估计,得分函数和前景理论的三角直觉模糊随机决策

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摘要

This study investigates and improves the operational laws of triangular intuitionistic fuzzy numbers. The triangular intuitionistic fuzzy random variable (TIFRV) is introduced on the basis of the concepts of the triangular intuitionistic fuzzy number and triangular fuzzy random variable. Related properties of a TIFRV are also proposed and verified. To solve the problem of multi-criteria decision making on aspiration levels-a situation in which criterion weights are unknown and criterion values are given in terms of TIFRVs-this study proposes a triangular intuitionistic fuzzy random decision-making method based on a combination of parametric estimation, score functions, and prospect theory. In this method, the decision maker evaluates alternatives with triangular intuitionistic fuzzy numbers in different periods of decision making and thus enables the estimation of the parameters of the triangular intuitionistic fuzzy population and the creation of an intuitionistic triangular fuzzy random matrix. An expectation-variance intuitionistic fuzzy matrix is constructed on the basis of mean-variance analysis, and a fuzzy random score function is then defined to transform a normalized expectation-variance intuitionistic fuzzy matrix into a score function matrix. Prospect theory is used to calculate the values of prospect score functions, and the information entropy method is used to determine criterion weights. This procedure generates comprehensive prospect score function values that determine the final ranking of alternatives. A practical example is presented to show the feasibility and effectiveness of the proposed approach.
机译:本研究调查并改进了三角直觉模糊数的运算规律。在三角直觉模糊数和三角模糊随机变量的概念的基础上,介绍了三角直觉模糊随机变量(TIFRV)。还提出并验证了TIFRV的相关属性。为解决基于期望水平的多准则决策问题-在准则权重未知且以TIFRV给出准则值的情况下,本研究提出了一种基于参数组合的三角直觉模糊随机决策方法估计,得分函数和前景理论。在这种方法中,决策者在决策的不同阶段使用三角直觉模糊数评估备选方案,从而能够估计三角直觉模糊种群的参数并创建直觉三角模糊随机矩阵。在均值-方差分析的基础上构造了期望-方差直觉模糊矩阵,然后定义了模糊随机得分函数,将归一化的期望-方差直觉模糊矩阵转换为得分函数矩阵。前景理论用于计算前景得分函数的值,信息熵方法用于确定标准权重。此过程生成综合的前景得分函数值,这些函数确定替代方案的最终排名。给出了一个实际的例子来说明该方法的可行性和有效性。

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