[1]陈运文,吴飞,吴庐山,等. 基于异常检测的时间序列研究[J].计算机技术与发展,2015,25(04):166-170.
　CHEN Yun-wen,WU Fei,WU Lu-shan,et al. Research on Time Series Based on Anomaly Detection[J].,2015,25(04):166-170.
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 基于异常检测的时间序列研究()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
25
期数:
2015年04期
页码:
166-170
栏目:
应用开发研究
出版日期:
2015-04-10

文章信息/Info

Title:
 Research on Time Series Based on Anomaly Detection
文章编号:
1673-629X（2015)04-0166-05
作者:
 陈运文; 吴飞; 吴庐山; 刘博
 上海工程技术大学 电子电气工程学院
Author(s):
 CHEN Yun-wen ; WU Fei ; WU Lu-shan; LIU Bo
关键词:
 ; 时间序列; 异常检测; 数据挖掘; 多元时间序列
Keywords:
 ; time series; anomaly detection; data mining; multivariate time series
分类号:
TP311
文献标志码:
A
摘要:
 时间序列是一种重要类型的时态数据，广泛应用于科研、经济和军事等各个领域，而针对时间序列的异常检测研究是近年来大数据挖掘的热点与难点。文中以国内外最近的研究成果和时间序列检测的研究价值为基础，探讨了时间序列异常检测的定义并对相关异常检测方法进行归类研究与总结，同时指出每种异常检测方法的优缺点，并进一步分析部分具有代表性的时间序列异常检测的相关研究成果，尤其是讨论了多元时间序列异常检测研究所面临的难题，并给出解决此难题的思路和方法。最后总结归纳时间序列异常检测的几点建议与未来研究方向，以期对相关研究提供有益的参考。
Abstract:
 Time series is a temporal data of important class which are widely used in scientific research,economics,and military and other fields,but the study aiming at anomaly detection of time series in recent years is the hot and difficult of data mining. In this paper,based on the recent research achievements at home and abroad and the research value of time sequential detection,discuss the definition of a-nomaly detection of time series and the research on related anomaly detection methods are classified and summarized,at the same time point out the advantages and disadvantages of each type of anomaly detection methods,and further analyze relevant research achievements of some typical time series of the anomaly detection,especially discussing the multivariate time series,the challenges faced by the institute of anomaly detection,and giving ideas and methods to solve this problem. Finally,some suggestions about anomaly detection and future research trends are also summarized,which is hopefully beneficial to the researchers of time series and other relative domains.

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更新日期/Last Update: 2015-06-05