时间序列分段线性表示及相似性算法研究

随着计算机软、硬件的进步,人们利用信息技术产生和搜集数据的能力大幅度提高.作为数据挖掘的重要研究课题之一,时间序列的挖掘与预测近几年发展迅速.本文时时间序列的分段线性化表示进行了研究,采用新的分段线性化表示方法建立了序列相似性度量准则,弥补了以往度量准则对时间轴上伸缩的变化敏感的问题.新的表示方法和相似性度量准则使时间序列数据更容易应用传统的数据挖掘方法.

Research on the Comparability Algorithm and Piecewise Linear Representation of Time Series

With the development of computer software and hardware, the ability of generating and collecting data by information technology has improved greatly. As the important area of data-mining research, time series data-mining and forecasting have developed greatly. This paper analyze piecewise linear representation of time series and give a new type representation which are used to build a new measurement rule of similar time series, This new measurement avoids the problem of omitting the similar time series with different length of during time. This paper also discusses the mining algorithms