Early weak anomaly detection and uncertainty quantification of equipment based on multi-task and multi-domain temporal memory autoencoder

To avoid severe malfunctions of industrial equipment, it is necessary to perform accurate detection in the early stages of abnormal occurrences. However, early anomalies are usually weak, difficult to model anomalous features, and affected by data uncertainty and training uncertainty. To address the...

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Vydáno v:	Engineering applications of artificial intelligence Ročník 162; s. 112735
Hlavní autoři:	Li, Chuanrui, Ma, Liyong
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier Ltd 26.12.2025
Témata:	Autoencoder Early weak anomaly detection Multi-task learning Uncertainty Early weak anomaly detection Uncertainty Autoencoder Multi-task learning
ISSN:	0952-1976
On-line přístup:	Získat plný text
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