Anomaly Detection on Gas Turbine Time-series’ Data Using Deep LSTM-Autoencoder
Anomaly detection with the aim of identifying outliers plays a very important role in various applications (e.g., online spam, manufacturing, finance etc.). An automatic and reliable anomaly detection tool with accurate prediction is essential in many domains. This thesis proposes an anomaly detecti...
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| Format: | Others |
| Language: | English |
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Umeå universitet, Institutionen för datavetenskap
2021
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| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-179863 |