| 基于EMD方法的时间序列分层相似性匹配算法 |
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| 引用本文： | 郭艳琴,贾素玲.基于EMD方法的时间序列分层相似性匹配算法[J].计算机工程与应用,2008,44(34):129-131. |
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| 作者姓名： | 郭艳琴 贾素玲 |
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| 作者单位： | 北京航空航天大学经济管理学院,北京,100083 |
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| 摘 要： | 时间序列数据挖掘是时态数据挖掘的一个重要方面,针对金融时间序列非稳定、非线性的特点,使用EMD方法进行序列趋势的提取,得到了原始时间序列的长期趋势。在此基础上提出了子序列分层匹配算法,首先进行时间序列趋势的粗匹配,在结果集中进一步进行细节匹配,与传统方法相比,提高了相似性匹配的效率,减少了结果集的冗余。
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| 关 键 词： | 经验模式分解 趋势提取 时间序列相似性匹配 |
| 收稿时间： | 2008-5-20 |
| 修稿时间： | 2008-6-23
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Hierarchical algorithm for time series similar pattern matching based on EMD |
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| GUO Yan-qin,JIA Su-ling.Hierarchical algorithm for time series similar pattern matching based on EMD[J].Computer Engineering and Applications,2008,44(34):129-131. |
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| Authors: | GUO Yan-qin JIA Su-ling |
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| Affiliation: | Department of Economics and Management，Beihang University，Beijing 100083，China |
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| Abstract: | Data mining of time series is an important part of DM(Data Mining).This article first extracts the trend information from financial series using EMD method which is applicable for non-stationary and non-linear time series.Then the hierarchical algorithm for time series similar pattern matching is proposed based on the result of trend extraction which improves the effec-tiveness of similar pattern matching and decreases the redundancy. |
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| Keywords: | Empirical Mode Decomposition(EMD) trend extraction similar pattern matching time series |
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