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Energies
Volume 13
Issue 2
10.3390/en13020399
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Addendum to Energies 2019, 12(24), 4802.
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Addendum

Addendum: Termite, M.R. et al. A Never-Ending Learning Method for Fault Diagnostics in Energy Systems Operating in Evolving Environments. Energies 2019, 12, 4802

by
Maria Rosaria Termite
1,
Piero Baraldi
1,*,
Sameer Al-Dahidi
2,
Luca Bellani
3,
Michele Compare
3 and
Enrico Zio
1,3,4,5
1
Energy Department, Politecnico di Milano, Via La Masa 34, 20156 Milan, Italy
2
Department of Mechanical and Maintenance Engineering, School of Applied Technical Sciences, German Jordanian University, Amman 11180, Jordan
3
Aramis Srl, Via pergolesi 5, 20121 Milano, Italy
4
MINES ParisTech, PSL Research University, CRC, 06560 Sophia Antipolis, France
5
Department of Nuclear Engineering, College of Engineering, Kyung Hee University, Seoul 130-701, Korea
*
Author to whom correspondence should be addressed.
Energies 2020, 13(2), 399; https://doi.org/10.3390/en13020399
Submission received: 27 December 2019 / Accepted: 8 January 2020 / Published: 13 January 2020
Versions Notes
The authors would like to add the following note to Figure 3 of their paper published in Energies [1]:
The image used to represent the clustering module in Figure 3 was taken from Figure 6 of [2], reverted and without the text labels of the original figure.
The manuscript will be updated, and the original one will remain available on the article webpage, with reference to this Addendum. The authors apologize for any inconvenience this change may cause. The changes do not affect the scientific results.

References

  1. Termite, M.R.; Baraldi, P.; Al-Dahidi, S.; Bellani, L.; Compare, M.; Zio, E. A Never-Ending Learning Method for Fault Diagnostics in Energy Systems Operating in Evolving Environments. Energies 2019, 12, 4802. [Google Scholar] [CrossRef] [Green Version]
  2. Hao, Y.; Chen, Y.; Zakaria, J.; Hu, B.; Rakthanmanon, T.; Keogh, E. Towards Never-Ending Learning from Time Series Streams. In Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Chicago, IL, USA, 11–14 August 2013; ACM: New York, NY, USA, 2013; pp. 874–882. [Google Scholar]

Share and Cite

MDPI and ACS Style

Termite, M.R.; Baraldi, P.; Al-Dahidi, S.; Bellani, L.; Compare, M.; Zio, E. Addendum: Termite, M.R. et al. A Never-Ending Learning Method for Fault Diagnostics in Energy Systems Operating in Evolving Environments. Energies 2019, 12, 4802. Energies 2020, 13, 399. https://doi.org/10.3390/en13020399

AMA Style

Termite MR, Baraldi P, Al-Dahidi S, Bellani L, Compare M, Zio E. Addendum: Termite, M.R. et al. A Never-Ending Learning Method for Fault Diagnostics in Energy Systems Operating in Evolving Environments. Energies 2019, 12, 4802. Energies. 2020; 13(2):399. https://doi.org/10.3390/en13020399

Chicago/Turabian Style

Termite, Maria Rosaria, Piero Baraldi, Sameer Al-Dahidi, Luca Bellani, Michele Compare, and Enrico Zio. 2020. "Addendum: Termite, M.R. et al. A Never-Ending Learning Method for Fault Diagnostics in Energy Systems Operating in Evolving Environments. Energies 2019, 12, 4802" Energies 13, no. 2: 399. https://doi.org/10.3390/en13020399

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