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A multistage risk decision making method for normal cloud model considering behavior characteristics

机译:考虑行为特征的普通云模型的多级风险决策方法

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摘要

It is difficult to make scientific decisions for multistage risk decision-making problems, which are mainly influenced by these challenges, such as uncertainty of information, the passage of time and complexity of the problems The multistage risk decision-making problem is analyzed for normal cloud model considering behavior characteristics in this paper. Firstly, considering the fuzziness and randomness of multi-stage risk decision-making information, the relative entropy and modified relative entropy are defined as the distance measures for the normal cloud model from the perspective of full utilization of information. Secondly, the prospect theory is extended to normal cloud model environment. Considering the behavior characteristics of reference dependence, two reference points are set up considering the short-term development and long-term development. Thirdly, the optimization model is built to obtain the attribute weights and stage weights based on the principle of maximizing the difference between ranking values. The ranking of alternatives is determined by the final ranking values. The case analysis and the method comparison illustrate the feasibility and rationality of the proposed method. (C) 2019 Elsevier B.V. All rights reserved.
机译:难以为多级风险决策问题做出科学决策,主要受这些挑战的影响,例如信息的不确定性,时间和复杂性的问题对普通云进行分析多级风险决策问题的时间和复杂性考虑本文行为特征的模型。首先,考虑到多阶段风险决策信息的模糊和随机性,从充分利用信息的角度定义为正常云模型的距离测量。其次,展望理论延伸到正常的云模型环境。考虑到参考依赖的行为特征,考虑到短期开发和长期发展,建立了两个参考点。第三,建立优化模型以基于最大化排名值之间的差异的原理来获得属性权重和阶段权重。替代品的排名由最终排名值确定。案例分析和方法比较说明了所提出的方法的可行性和合理性。 (c)2019年Elsevier B.V.保留所有权利。

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