...版） 关键字: 高速列车轴承；极小样本；可靠性评估；Bayes方法[gap=1033]Key words: high-speed train bearing; minimum sample; reliability evaluation; Bayes method...
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在软测量建模过程中，基于支持向量机的算法能较好地解决小样本、非线性、高维数、局部极小点等问题。
In model establishment of soft-sensing, the problems of small sample, non-linearity, high dimensions and local minimal value can be well solved by support vector machine algorithm.
作为一种新的机器学习方法，SV M能较好地解决小样本、非线性、高维数和局部极小点等实际问题。
As a new machine learning method, SVM can solve the small sample, nonlinear, high dimension and local minima, the actual problem.
支持向量机方法较好地解决了许多学习方法面临的小样本、非线性和局部极小点等问题，具有很好的应用前景。
SVM solves practical problems such as small samples, nonlinearity, local minima, which exist in most of learning methods, and has a bright future.
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