Anomaly Detection over Time Series Data

Zhenyi Zhu

doi:10.20944/preprints202207.0407.v1

Preprint Brief Report Version 1 Preserved in Portico This version is not peer-reviewed

Version 1 : Received: 26 July 2022 / Approved: 26 July 2022 / Online: 26 July 2022 (10:50:27 CEST)

The anomaly detection task is very important in computer science. And there are a lot of anomaly detection methods. Different from some thresholding methods, some unsupervised methods could make us get more accurate and faster result, which is the object of the project. In this paper, I tried to use EWMA and some other methods in two datasets: Webank time consuming indicators dataset and AIOps Challenge dataset. The paper consists nine parts: background of the project, related work, description of algorithms, implementation details, experimental setup and data sets used, experimental results and discussion, future directions, reference and meeting notes.

Anomaly Detection ; Time Series; EWMA

Computer Science and Mathematics, Computer Science

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Anomaly Detection over Time Series Data

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