在更新话题模型的过程中，尝试确定性和不确定性相结合的方式作为样本选择标准。
In the process of updating topic model, a method combining certainty and uncertainty is used to select samples.
支持向量机因其适用高维特征、小样本与不确定性问题的优越性，是一种极具潜力的高光谱遥感分类方法。
Support Vector Machines(SVM) is a potential hyperspectral remote sensing classification method because it is advantageous to deal with problems with high dimensions, small samples and uncertainty.
传统的测试性验证试验样本选取方法没有考虑测试对象的各故障模式之间的复杂性与不确定性关系。
The complex and uncertain relationship among failures is ignored in failure sample selection based on traditional testability demonstration experiment method.
以概率乘法公式为理论依据，根据训练样本的PC A结果对PNN进行结构优化，并引入学习算法减小pnn的参数不确定性。
A probability multiplication formula was used as the theoretical foundation. The PNN structure was optimized based on statistical results from the PCA for the training samples.
概括了影响地质储量评估的三个不确定性：油藏样本的局限性，技术的不确定性，经济的不确定性。
Three uncertainties affecting on OOIP including reservoir sampling limitation, technical uncertainty and commercial uncertainty were discussed.
以概率乘法公式为理论依据，根据训练样本的PCA结果对PNN进行结构优化，并引入学习算法减小PNN的参数不确定性。
The PNN structure was optimized based on statistical results from the PCA for the training samples. A learning algorithm was introduced into the PNN to reduce uncertainties parameter.
以概率乘法公式为理论依据，根据训练样本的PCA结果对PNN进行结构优化，并引入学习算法减小PNN的参数不确定性。
The PNN structure was optimized based on statistical results from the PCA for the training samples. A learning algorithm was introduced into the PNN to reduce uncertainties parameter.
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