Abstract: This paper proposes a new linear fitting method for time series. The turning points are picked up in terms of the slope changes of the adjacent point connections, and the set of key points of the time series is obtained by merging these points with extreme points. The method can not only eliminate the noise points, but also more precisely locate the key points of the series. Test results show the method can much better reflect the original time series. Comparing this method with the existed ones, the smaller fitting errors are achieved.

Key words: time series, linear fitting, fitting error, slope, key point

摘要： 提出一种新的时间序列线性拟合方法。通过判断连接相邻点所成线段的斜率变化，选择时间序列中的转折点，将这些点与时间序列的极值点合并作为关键点，利用这些关键点组成的序列拟合原时间序列。该线性拟合方法在剔除噪声的同时，能更精确地定位时间序列中的关键点。实验结果表明，与已有方法相比，该方法能近似表示原时间序列，且拟合后的时间序列和原时间序列之间的拟合误差更小。

关键词: 时间序列, 线性拟合, 拟合误差, 斜率, 关键点

CLC Number: 

• N945