Comparison with other tested heuristics verifies that the proposed random sampling method is significantly superior to other heuristics for scheduling resource-constrained multiple projects.
与其他多项目调度启发式算法的比较和统计检验，说明随机抽样算法显著优于这些常用的启发式算法。
The paper introduces multiple imputation (mi) for missing data in stratified random sampling, and discusses the ordinary method of mi with ignorable nonresponse, and illustrates the essential steps.
介绍分层随机抽样条件下多重插补法处理缺失数据的基本思想，分析可忽略无回答的分层随机抽样建立多重插补的常用方法，并通过实例加以说明。
This method can identify the transfer function of the system only using SOS, by sampling multiple outputs or oversampling a single output.
这一算法通过单输出的过采样或者多输出的采样，能够仅仅利用输出的SOS信息辨识出系统传输函数。
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