论文信息 - An Online Anomalous Time Series Detection Algorithm for Univariate Data Streams

An Online Anomalous Time Series Detection Algorithm for Univariate Data Streams

We address the online anomalous time series detection problem among a set of series, combining three simple distance measures. This approach, akin to control charts, makes it easy to determine when a series begins to differ from other series. Empirical evidence shows that this novel online anomalous time series detection algorithm performs very well, while being efficient in terms of time complexity, when compared to approaches previously discussed in the literature.

Kishan G. Mehrotra | Chilukuri K. Mohan | Huaming Huang

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