Accurate Anomaly Interval Recognition and Fault Classification by Pattern Mining and Clustering
Author:
Affiliation:
1. School of Electronic and Information Engineering, Beijing Jiaotong University,Beijing,China
2. Beijing Baolande Software Corporation,Beijing,China
Funder
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10225747/10225748/10226079.pdf?arnumber=10226079
Reference21 articles.
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4. Unsupervised anomaly detection via variational autoencoder for seasonal kpis in web applications;xu;Proceedings of the 2018 World Wide Web Conference,0
5. Exathlon: a benchmark for explainable anomaly detection over time series;jacob;ArXiv Preprint,2020
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1. Joint Subsequence Anomaly Detection and Fault Classification for Multivariate Time Series;2024 9th International Conference on Computer and Communication Systems (ICCCS);2024-04-19
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