A survey on anomaly detection for technical systems using LSTM networks

•Focusing on practical application of neural network-based detection algorithms.•LSTM-based approaches allow dynamic and time-variant anomaly detection.•Graph-based approaches enable unified representation of heterogeneous data.•Transfer learning addresses frequent lack of sufficiently large and div...

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Bibliographic Details

Published in:	Computers in industry Vol. 131; p. 103498
Main Authors:	Lindemann, Benjamin, Maschler, Benjamin, Sahlab, Nada, Weyrich, Michael
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.10.2021
Subjects:	Anomaly detection Artificial intelligence Autoencoder Context modeling Long short-term memory Transfer learning Long short-term memory Autoencoder Transfer learning Artificial intelligence Anomaly detection Context modeling
ISSN:	0166-3615, 1872-6194
Online Access:	Get full text
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