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中文摘要：
产品销售时序通常具有正态高斯分布、幅值较大、奇异点等混合噪音，为此，设计了一种鲁棒损失函数，得到一种新的支持向量机，即鲁棒v-支持向量机。它可以有效地压制销售时序的多种噪音和奇异点，具有很强的鲁棒性，而且比标准v-支持向量机具有更简洁的对偶优化问题。最后进行了汽车销售预测的实例分析，结果表明，基于鲁棒ν-支持向量机的预测模型是有效可行的。
英文摘要：
To inhibit the normal Gaussian distributional noise, greater amplitude noise and singular points of product sales series, a robust loss function was designed, and a new support vector machine was obtained, named robust v - support vector machine （Rv-SVM）. Rv-SVM, which was with strong robustness and simpler dual optimization problem than standard v -SVM, various types of noises and singular points of product sales series could he inhibited effectively. Then, Rv -SVM was applied to predict ear sales, and the results showed that the prediction model based on Rv-SVM was effective and feasible.
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