In the stage I, called as data preprocessing, the support vector machines for regression (SVMR) approach is used to filter out the outliers in the training data set.

第一阶段称为所谓的资料预先处理，即使用支援向量回归来找出训练资料集中的离异点并删除之。

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Consequently, the learning mechanism of the proposed approach is much easier than the robust support vector regression networks (RSVRNs) approach and the weighted LS-SVMR approach.

我们所提出的方法在整个学习架构上要比强健式支援向量机网路与权重式最小平方支援向量机回归法更简易。

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