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上海电力大学学报:2010,26(5):505-508
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基于关键点的时间序列模式表示
(上海电力学院 计算机与信息工程学院, 上海 200090)
Time Series Pattern Representation Based on Skeleton Points
(School of Computer and Information Engineering, Shanghai University of Electric Power, Shanghai 200090, China)
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投稿时间:2010-07-12    
中文摘要: 时间序列包含的数据量大、维数高、数据更新快,很难直接在原始时间序列上进行数据挖掘.借鉴时间序列线性分段的基本思想,提出了一种基于关键点的分段线性表示法,用关键点组成的直线段近似描述时间序列.将关键点作为时间序列的分割点,反映时间序列的主要特征,降低时间序列的维数,使整体误差达到最小.
中文关键词: 时间序列  模式表示  关键点  线性分段
Abstract:Time series data have the characteristics of being large in size,high dimensionality and prompt update.It is hard to manipulate for data analysis and mining in its original structure.Using the basic idea of piecewise linear time series for reference,a time series segmentation algorithm is proposed based on skeleton point,which can approximately represent time series by linear composed of skeleton point.This method adopts skeleton point as segmentation point in time series reflecting mostly character of time series.The dimensionality of time series is reduced,and the error of the whole is minimized.
文章编号:20100523     中图分类号:    文献标志码:
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引用文本:
张安勤,叶文珺.基于关键点的时间序列模式表示[J].上海电力大学学报,2010,26(5):505-508.
ZHANG An-qin,YE Wen-jun.Time Series Pattern Representation Based on Skeleton Points[J].Journal of Shanghai University of Electric Power,2010,26(5):505-508.