Open Access
Issue
E3S Web Conf.
Volume 680, 2025
The 4th International Conference on Energy and Green Computing (ICEGC’2025)
Article Number 00059
Number of page(s) 7
DOI https://doi.org/10.1051/e3sconf/202568000059
Published online 19 December 2025
  1. B. Abouelanouar, A. Elkihel, F. Khathyri, and H. Gziri, Monitoring energy consumption based on predictive maintenance techniques, in Lecture Notes in Electrical Engineering (2021). [Google Scholar]
  2. S. Kumar, K. K. Raj, M. Cirrincione, G. Cirrincione, V. Franzitta, and R. R. Kumar, A Comprehensive Review of Remaining Useful Life Estimation Approaches for Rotating Machinery, Energies, Page 5538, vol. 17, no. 22, p. 5538 (2024). [Google Scholar]
  3. H. J. Park, N. H. Kim, and J.-H. Choi, Integrating Advanced Prognostic Methods for Accurate Remaining Useful Life Prediction in Industrial Systems, Annual Conference of the PHM Society, vol. 15, no. 1 (2023). [Google Scholar]
  4. A. Quattrocchi et al., Remaining Useful-Life Prediction of the Milling Cutting Tool Using Time–Frequency-Based Features and Deep Learning Models, Sensors, Vol. 23,Page 5659, vol. 23, no. 12, p. 5659 (2023). [Google Scholar]
  5. K. Fricke, R. G. Nascimento, M. Corbetta, C. S. Kulkarni, and F. A. C. Viana, Prognosis of Li-ion batteries under large load variations using hybrid physics-informed neural networks, Proceedings of the ACPHM Society, vol. 15, no. 1 (2023). [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.