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在传统的贝叶斯法则概率计算中,偶然与认知不确定性没有区分,而在广义贝叶斯法则中,偶然不确定性表述为概率测量,认知不确定性通过区间来描述。以机床轴承热误差分析为例说明了广义贝叶斯法则概率应用的有效性。与传统的贝叶斯法则进行了比较。结果表明:用广义贝叶斯法则能更好地描述热误差。
In traditional Bayesian rule probability calculation, there is no distinction between occasional and cognitive uncertainty, while in generalized Bayes rule, occasional uncertainty is expressed as probability measurement, and cognitive uncertainty is described by interval. The thermal error analysis of machine tool bearings is taken as an example to illustrate the validity of the generalized Bayesian rule probability. Compared with the traditional Bayes rule. The results show that the generalized Bayesian law can better describe the thermal error.