本文研究表明：采用基于支持向量机的方法，可以有效地提高系统的抗干扰性和识别率。

The research in this article shows that using SVM classifiers can efficiently improve the robustness and recognition rate of the system comparing with other methods.

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介绍了一种基于支持向量机的混合气体红外光谱组分浓度和种类分析的新方法。

A new method of infrared spectrum analysis based on support vector machine for mixture gas was proposed.

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进而提出了基于支持向量机(SVM)的网络延时预测方法。

The prediction method of network delays based on support vector machine (SVM) was put forward.

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