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Alternative TitleOutliers and change-points detection algorithm for time series
苏卫星; 朱云龙; 刘芳; 胡琨元
Source Publication计算机研究与发展
Indexed ByEI ; CSCD
EI Accession number20141717618862
Contribution Rank1
Funding Organization国家科技支撑计划基金项目(2012BAF10B11,2014BAF07B01);辽宁省自然科学基金项目(201202226)
Keyword异常点 突变点 小波变换 Lipschitz指数 时间序列
Other AbstractBecause the conventional change-points detection method exists the shortages on time delay and inapplicability for the time series mingled with outliers in the practical applications, an outlier and change-point detection algorithm for time series, which is based on the wavelet transform of the efficient score vector, is proposed in this paper. The algorithm introduces the efficient score vector to solve the problem of the conventional detection method that statistics often increass infinitely with the number of data added during the process of detection, and proposes a strategy of analyzing the statistics by using wavelet in order to avoid the serious time delay. In order to distinguish the outlier and change-point during the detection process, we propose a detecting framework based on the relationship between Lipschitz exponent and the wavelet coefficients, by which both outlier and change-point can be detected out meanwhile. The advantage of this method is that the detection effect is not subject to the influence of the outlier. It means that the method can deal with the time series containing both outliers and change-points under actual operating conditions and it is more suitable for the real application. Eventually, the effectiveness and practicality of the proposed detection method have been proved through simulation results.
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Document Type期刊论文
Recommended Citation
GB/T 7714
苏卫星,朱云龙,刘芳,等. 时间序列异常点及突变点的检测算法[J]. 计算机研究与发展,2014,51(4):781-788.
APA 苏卫星,朱云龙,刘芳,&胡琨元.(2014).时间序列异常点及突变点的检测算法.计算机研究与发展,51(4),781-788.
MLA 苏卫星,et al."时间序列异常点及突变点的检测算法".计算机研究与发展 51.4(2014):781-788.
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