文章对测量不确定度的定义，分类及来源进行了阐述，并且讲述了测量不确定度的评定方法和步骤。
This paper introduces the definition, classification and sources of the measurement uncertainty, as well as the methods and steps of the evaluation of measurement uncertainty.
SVMFN中采用了一种新的模糊密度定义，同时考虑了分类器的精确度和不确定性，提高了识别的可靠性。
The SVMFN employs a new definition of fuzzy density which incorporates accuracy and uncertainty of the classifiers to improve recognition reliability.
阐述了不确定度理论的含义、分类，介绍了直接测量量和间接测量量的合成标准不确定度。
Goes into particular meanings and class of uncertainty, concretely introduced direct measurement and indirect measurement of Synthetic criterion uncertainty.
就不确定度的定义、分类、评定步骤和方法、报告与表示、有效位数等问题进行了讨论。
The definitions, classification, steps and method of evaluation, report and expression, significant places of number etc. for measurement uncertainty were also discussed in the paper.
本文对测量误差和测量不确定度的定义、来源及分类进行描述。
This article defined the two different concepts: error and uncertainty of measurement, explained how they preduce and listed their types.
实验结果表明，D - S证据理论决策树分类算法能有效地对不确定数据进行分类，有较好的分类准确度，并能有效避免组合爆炸。
This D-S decision tree is a new classification method applied to uncertain data and shows good performance and can efficiently avoid combinatorial explosion.
实验结果表明，D - S证据理论决策树分类算法能有效地对不确定数据进行分类，有较好的分类准确度，并能有效避免组合爆炸。
This D-S decision tree is a new classification method applied to uncertain data and shows good performance and can efficiently avoid combinatorial explosion.
应用推荐