计算机科学 ›› 2011, Vol. 38 ›› Issue (11): 153-155.

• 数据库与数据挖掘 • 上一篇    下一篇

基于函数的时间序列分段线性表示方法

谢福鼎,王赫楠,张永,孙岩   

  1. (辽宁师范大学城市与环境学院 大连116029) (辽宁师范大学计算机系 大连116081)
  • 出版日期:2018-12-01 发布日期:2018-12-01

Method of Time Series Piecewise Linear Representation Based on the Function

  • Online:2018-12-01 Published:2018-12-01

摘要: 考虑到时间序列的时间特性对不同区段的影响以及时间序列数据动态增长的实际情况,在RPAA ( Reversed Piecewise Aggregate Approximation)和PAA(Piecewise Aggregate Approximation)方法的基础上,提出了一种新的时间序列分段线性表示方法FPAA(Founction Piecewise Aggregate Approximation)。FPAA方法通过定义函数影响因子,克服了RPAA和PAA方法的不足。该方法具有线性时间复杂度,满足下界定理,并且支持时间序列的在线划分。实验表明,与PAA方法和RPAA方法相比,所提出的方法可以较有效地进行时间序列的在线查询。

关键词: 时间序列,分段线性表示,时间特性,影响因子,在线划分

Abstract: Considering the actual situation of the different influence on the different segments in terms of time property of time series and the dynamic growth data of time series, a new method FPAA(Function Piecewise叔gregate Approximation)of piecewise linear representation was proposed based on the method of RPAA(Reversc Piccewise Aggregate Approximate) and PA八(Piecewise Aggregate Approximate). The proposed method overcomes the disadvantages of RPAA and PAA by defining the influence factor of function. FPAA has the linear complexity, satisfies lower bounding lemma and supports online segmentation of time series. Compared with the methods of PAA and RPAA, the FPAA method can effectively query time series online.

Key words: Dime series, Piecewise linear representation, Time property, Influence factor, Online segmentation

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