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Self-Diagnosis of Multiphase Flow Meters through Machine Learning-Based Anomaly Detection
2020
Energies
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In this work, we propose an Anomaly Detection approach, based on unsupervised Machine Learning algorithms, that enables the metrology system to detect outliers and to provide a statistical level of confidence ...
The approach is validated both on real and synthetic data. ...
In Proceedings of the 2019 18th IEEE International Conference On Machine Learning And Applications
(ICMLA), Boca Raton, FL, USA, 16–19 December 2019; pp. 1756–1763.
44. ...
doi:10.3390/en13123136
fatcat:tvyweqdua5fqjafgs6sqacvxxa