Autoencoder and Incremental Clustering-Enabled Anomaly Detection

Autoencoder and Incremental Clustering-Enabled Anomaly Detection

Many machine-learning-enabled approaches towards anomaly detection depend on the availability of vast training data. Our data are formed from power readings of cycles from domestic appliances, such as dishwashers or washing machines, and contain no known examples of anomalous behaviour. Moreover, we...

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Bibliographic Details
Main Authors: Andrew Charles Connelly, Syed Ali Raza Zaidi, Des McLernon
Format: Article
Language:English
Published: MDPI AG 2023-04-01
Series:Electronics
Subjects:
autoencoder
anomaly detection
clustering
time series
unsupervised
Online Access:https://www.mdpi.com/2079-9292/12/9/1970

Internet

https://www.mdpi.com/2079-9292/12/9/1970

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