基于时间序列波动性的分段线性表示方法  

Piecewise Linear Representation Based on Time Series Volatility

作　　者：李颖 于东[1,3] 胡毅 刘劲松[1,2] 张丽鹏 LI Ying;YU Dong;HU Yi;LIU Jin-Song;ZHANG Li-Peng(Shenyang Institute of Computing Technology,Chinese Academy of Sciences,Shenyang 110168,China;University of Chinese Academy of Sciences,Beijing 100049,China;Shenyang CASNC Technology Co.Ltd.,Shenyang 110168,China)

机构地区：[1]中国科学院沈阳计算技术研究所,沈阳110168 [2]中国科学院大学,北京100049 [3]沈阳中科数控技术股份有限公司,沈阳110168

出　　处：《计算机系统应用》2021年第6期300-305,共6页Computer Systems & Applications

基　　金：国家科技重大专项(2019ZX04004-001)。

摘　　要：为了解决现有时间序列的分段线性表示方法忽略时间序列的全局特征,局限于局部最优的问题,本文通过研究时间序列的趋势,发现了时间序列的波动特性,将时间序列的趋势变化分为上下两层,在上下两层分别剔除趋势保持点.实验结果表明,该分段方法时间复杂度低、且易于实现,在保持时间序列趋势特征的基础上,得到的拟合误差更小.Existing piecewise linear representation of time series ignores the global characteristics of time series and easily falls into local optima.To solve this,the paper studies the trend in time series and finds its fluctuation.The trends is divided into an upper layer and a lower one with their trend holding points removed.The experimental results show that the segmentation method has low time complexity and is easy to implement,and the fitting error is smaller on the premise of keeping the trend characteristics of time series.

关 键 词：时间序列 分段 波动 全局趋势 关键点 

分 类 号：O211.61[理学—概率论与数理统计]