对于已知行为，采用加权支持向量机分类算法来识别其行为类别；

For the known activities, the weighted support vector machine (WSVM) is used to recognize their types.

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对结果均方差的分析显示，加权支持向量机的预测精度优于人工神经网络和标准支持向量机模型。

The analysis to the mean square deviation showed us the conclusion, that the prediction accuracy of WSVM was better than the ANN and traditional SVM models.

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其中根据各样本重要性的不同，引入了加权支持向量机方法，然后利用免疫规划算法对其进行参数优化。

The immune programming algorithm, inspired by the immune system of human and other mammals, was used to optimize the parameters of weighted support vector machines.

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