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基于线性分段与HMM的时间序列分类算法

, PP. 574-581

Keywords: 时间序列分类,隐马尔可夫模型,线性分段,导数估值

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Abstract:

抽象出时间序列的多段线性特征,并提出一种时间序列分类算法。该算法包括3个模块:导数估值函数,线性分段方法,DDHMM模型(基于HMM)。首先,利用导数估值函数与线性分段方法检测多段线性特征,若满足多线段特征,则将时间序列转化为特定结构的观察值序列;然后,利用训练观察值序列训练DDHMM模型,通过比较各模型产生测试观察值序列的概率值进行分类。实验表明,针对满足多段线性特征的时间序列,该算法具有较高的分类精度,应用在UCI数据集和实际工程中,分类效果好。

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