The weight information has been playing a key role in information fusion and dynamic decision making process. Most existing methods for determining weights under dynamic environments only derive the period weights by using the distribution functions of time series, but there is little investigation of the determination of dynamic attribute weights over time. To solve this issue, we first develop an intuitionistic fuzzy Bayesian network to obtain the practical attribute weights under uncertain environment. Then, we propose a conceptual framework for dynamic intuitionistic fuzzy decision making, and based on which, we develop a dynamic decision making approach integrating the prospect theory to solve the risk decision making problems. Furthermore, a case study involving the mine emergency decision making problem is presented to illustrate the application of our approach. Finally, we discuss the characteristics and limitations of our approach in detail.

中文翻译：

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基于直觉模糊贝叶斯网络的动态权重确定方法及其在应急决策中的应用

权重信息在信息融合和动态决策过程中一直发挥着关键作用。现有的动态环境下的权重确定方法大多只是利用时间序列的分布函数来推导周期权重，而对动态属性权重随时间的确定研究很少。为了解决这个问题，我们首先开发了一个直觉模糊贝叶斯网络来获得不确定环境下的实用属性权重。然后，我们提出了动态直觉模糊决策的概念框架，并在此基础上，我们开发了一种结合前景理论的动态决策方法来解决风险决策问题。此外，介绍了一个涉及矿山应急决策问题的案例研究，以说明我们方法的应用。最后，我们详细讨论了我们方法的特点和局限性。