在现有成果的基础上,对CREAM方法中的人为差错概率量化进行了改进.介绍了CREAM基本法量化人为差错概率的基本思想；讨论了两种概率化认知控制模式的确定方法:贝叶斯网络法和模糊逻辑法,强调了概率化认知控制模式下量化人为差错概率的必要性.通过理论推导,构建了概率化认知控制模式下人为差错概率的量化方法.另外,为了提高计算效率,提供了人为差错概率的Monte Carlo仿真算法.通过示例分析,证明了方法的有效性.%The quantification of human error probability in CREAM waS improved based on available meterials.First,the basic method of CREAM was introduced.Second,two methods tO determine probabilisfic control modes were discussed,which are Bayesian nets and fuzzy logic.The necessity to quantify human error probability in probabilistic control modes was emphasized.Last,the method Was proposed to quantify the human error probability in probabilistic control modes by theoretical inference.In order to improve the computing effectiveness,the Monte Carlo algorithm Was provided.An example was presented and the validity of the proposed method was proved.
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