对基于不完备样本集的参数学习，则首先计算参数值的上限值和下限值，再利用某种策略，如平均值法，得到参数的最终估计值。
The upper limit and the lower limit is computed first when inducing the CPTs from uncompleted dataset, and the point value is estimated by some method such as averaging.
在进行风险分析和评估过程中，经常遇到样本信息不充分，数据不完备，即小样本问题。
During analyzing and estimating the risk, we often meet with the situation of inadequate sample information and incomplete data, that is, small-sample problem.
但是大型的动态系统很难形成完备的样本集，所以应用上述两种方法在原理上无法保证诊断结果的正确性，容易陷入局部最小。
And when a system like NPP's is studied, the FD results based on the above methods even can not be proved in theory.
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