Using linear programming technique and scaling kernel function, the support vector regression model was obtained.

通过线性规划技术和采用尺度函数作为核函数来实现支持向量回归模型。

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Whereas SVM is not suitable for the smoothing regression, a modified support vector regression model is proposed.

鉴于后者有着对于光顺性的特殊要求，已有的支持向量机并不适用。

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The generalization of the support vector regression model, the optimization of the generalization capacity, and the training speed are discussed.

同时对广泛的支持向量回归模型、优化支持向量模型的泛化能力和运算速度等方面进行讨论。

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