基于重要点的时间序列固定分段数分段算法

基于重要点探测技术的时间序列线性分段算法能较好地保留序列的全局特征和拟合高精确度。传统的基于重要点时间序列分段算法,只能通过误差阈值来控制分段,该方法不能预计分段数量,不能适应后期要求分段数量一定的应用。提出一种基于序列重要点的时间序列固定分段数的分段算法—PLR_FPIP,该方法借用二叉树层次遍历的思路,重新调整原方法的分段次序,使用重要点组成的直线段近似描述时间序列,该方法能够在分段数量一定的情况下对时间序列分段。实验证明,该分段算法能在固定分段数的情况下反映时间序列的主体特征,算法简单快速,整体拟合误差小。

Time Series Segmentation Based on Fixed Number of PIPs Detection

The algorithm of time series segmentation based on the series important points can better retain global characteristics of series and fitting high accuracy.The traditional segmentation algorithm chooses segment point only through error threshold but fixed number of subsection.It can not meet the application which requires fix segment number.It proposes an algorithm based on fixed number of PIPs detection（PLR_FPIP）,which uses the ideas of binary tree level traversal,re-adjust the order of the original method and use PIPs composed of straight time series.Experimental results show that this algorithm can reflect the main characteristics of time series in cases of fixed number of PIPs,and the algorithm is simple,fast,low total error.