A Novel Multivariate Time-Series Anomaly Detection Approach Using an Unsupervised Deep Neural Network

A Novel Multivariate Time-Series Anomaly Detection Approach Using an Unsupervised Deep Neural Network

With the development of hardware technology, we can collect increasingly reliable time series data, in which time series anomaly detection is an important task to find problems in time and avoid risks. It is not easy to establish a multivariate time series anomaly detection system, because the colle...

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Bibliographic Details
Main Authors: Peihai Zhao, Xiaoyan Chang, Mimi Wang
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Anomaly detection
multivariate time-series
deep neural network
unsupervised learning
Online Access:https://ieeexplore.ieee.org/document/9503373/

Internet

https://ieeexplore.ieee.org/document/9503373/

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