时间序列的自适应误差约束分段线性表示  

Adaptive piecewise linear representation of time series based on error restricted

作　　者：贾澎涛[1] 林卫[2] 何华灿[1] 

机构地区：[1]西北工业大学计算机学院 [2]河南师范大学计算机与信息技术学院,河南新乡453003

出　　处：《计算机工程与应用》2008年第5期10-13,共4页Computer Engineering and Applications

基　　金：国家自然科学基金(the National Natural Science Foundation of China under Grant No.50474041);西北工业大学基础研究基金(theRe-search Foundation of Northwestern Polytechnical University under Grant No.W018101)

摘　　要：实际过程中采集到的时间序列数据通常是海量数据,在原时间序列数据上直接进行数据挖掘的效率通常是低下的,有时甚至不可行,因此就须将时间序列在更高的层次上进行表示。借鉴时间序列线性分段的基本思想,提出了一种自适应误差约束的分段线性表示方法,该方法在查找出时间序列特殊点的基础上,通过给定误差e进行调节,可以自动地产生拟合线段的数目。不仅可以压缩数据,去除噪声,还能得到时间序列的模式变化特征。与一般的分段线性表示相比,文中方法的拟合误差更小,适应能力更强。Time series is an important high dimension data type composed of a series of data observed according to time sequence.Usually time series data is massive.Sometimes,it is inefficient or impractical to mine the original time-series data directly. So time series should be represented on a higher level.Reference to the idea of pieeewise linear of time series,we put forward a method of adaptive pieeewise linear representation of time series based on error restricted.This method can give the number of fitting lines automatically according to a given error e on the special points of time series,This method not only compresses data and wipes of noise,but also finds the various pattern features of time series.According to experiments our algorithm leads to less fitting error and better performance than other algorithms.

关 键 词：数据挖掘 时间序列 自适应 分段线性表示 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]