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。

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

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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。

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

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采用支持向量回归在线辨识算法作为建模方法建立被控对象的逆模型。

Online identification algorithm of support vector regression is used to build the inverse model for the plant.

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