MST-VAE: Multi-Scale Temporal Variational Autoencoder for Anomaly Detection in Multivariate Time Series

In IT monitoring systems, anomaly detection plays a vital role in detecting and alerting unexpected behaviors timely to system operators. With the growth of signal data in both volumes and dimensions during operation, unsupervised learning turns out to be a great solution to trigger anomalies thanks...

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Bibliografische Detailangaben

Hauptverfasser:	Tuan-Anh Pham, Jong-Hoon Lee, Choong-Shik Park
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	MDPI AG 2022-10-01
Schriftenreihe:	Applied Sciences
Schlagworte:	multi-scale convolutional kernels variational autoencoder multivariate time series anomaly detection convolutional neural network
Online-Zugang:	https://www.mdpi.com/2076-3417/12/19/10078
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