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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Vydané v:	Engineering applications of artificial intelligence Ročník 162; s. 112735
Hlavní autori:	Li, Chuanrui, Ma, Liyong
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 26.12.2025
Predmet:	Autoencoder Early weak anomaly detection Multi-task learning Uncertainty Early weak anomaly detection Uncertainty Autoencoder Multi-task learning
ISSN:	0952-1976
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