基于趋势的时间序列分段线性化算法

通过分析时间序列的几何形态特征,研究时间序列向上、向下趋势的几何形态。根据时间序列的变化特征,提出了高、低滤波点和高、低滤波线概念,利用高低滤波线判断时间序列的向上趋势、向下趋势,提出了一种基于时间序列变化趋势的分段线性化方法。实验结果表明,这样分段线性化便于实现,运行速度快,保持了时间序列的形态特征,有较好的逼近性及线段个数也很少等优点。

A method of time series piecewise linearization based on tendency

The geometric form of upward and downward trends in time series was studied by analyzing the geometric characteristics of time series. Concepts of high or low filtering points and high or low filtering lines were proposed according to the variation characteristics of time series. These concepts were used to judge the upward trends and the downward trends of the time series. Furthermore, a piecewise linear representation of time series based on upward or downward property was proposed. The results of experiments show that this method is easy to be programmed. It has desirable approximation, runs fast, and keeps the shape of time series. Furthermore, the number of lines is small.