结合均匀设计和聚类思想提出的样本优选方法，在一定程度上解决了神经网络样本选择的问题。
Based on uniform design and the cluster theory, a optimum selecting method of sample is proposed to solve the problem of sample selection.
同时，将诊断输出值引入网络样本库， 组成了自适应智能诊断系统，提高了故障诊断结论的准确性。
Meanwhile, the diagnosing result was introduced network sample database to construct self-adaptive intelligent diagnosing system, thus, the accuracy of malfunction diagnosis improved as a result.
为确保对暴发的准确追踪，网络成员也在使样本采集、检测和结果解释的方法标准化。
To ensure accurate tracking of the outbreak, members of the network are also standardizing methods for sample collection, testing, and the interpretation of results.
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