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基于重标级差分析的时间序列分割方法 被引量：1

Segmentation for time series data based on R/S analysis
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摘要 针对重标级差分析法(Rescaled Range Analysis,R/S)在时间序列挖掘中的应用,提出了一种基于R/S分析的时间序列分割模型和算法,该算法能够根据序列波动的聚集性和自相似的特征,将序列分割为多个子序列。实验结论表明该方法可以发现时间序列的波动变化规律,方法有效、正确。 In this paper a segmentation model and algorithm based on R/S analysis is proposed for the application of rescaled range analysis in time series data mining.The series can be divided into some subsequences with proposed algorithm according to the character of clustering of volatility and self-similarity.Experimental results show that the volatility change tendency of time series can be obtained by the method.
作者 王阅 高学东
机构地区 北京科技大学经济管理学院
出处 《计算机工程与应用》 CSCD 北大核心 2008年第29期223-225,共3页 Computer Engineering and Applications
基金 国家教育部新世纪人才支持计划No.NCET-05-0097~~
关键词 时间序列 重标级差分析 波动聚集 自相似 time series Rescaled Range（R/S） analysis clustering of volatility self-similarity
分类号 TP311.13 [自动化与计算机技术—计算机软件与理论]
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参考文献9

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共引文献2

同被引文献12

  • 1范英,魏一鸣.基于R/S分析的中国股票市场分形特征研究[J].系统工程,2004,22(11):46-51. 被引量：52
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计算机工程与应用
2008年 第29期

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