Open Access
| Issue |
E3S Web Conf.
Volume 391, 2023
4th International Conference on Design and Manufacturing Aspects for Sustainable Energy (ICMED-ICMPC 2023)
|
|
|---|---|---|
| Article Number | 01069 | |
| Number of page(s) | 8 | |
| DOI | https://doi.org/10.1051/e3sconf/202339101069 | |
| Published online | 05 June 2023 | |
- Y. Zhao, Q. Liu, D. Li, D. Kang, Q. Lv and L. Shang, “Hierarchical Anomaly Detection and Multimodal Classification in Large-Scale Photovoltaic Systems,” in IEEE Transactions on Sustainable Energy, vol. 10, no. 3, pp. 1351–1361, (July 2019) [CrossRef] [Google Scholar]
- Xiang Gao, Eric Munson, Glen P. Abousleman, and Jennie Si “Automatic solar panel recognition and defect detection using infrared imaging”, Proc. SPIE 9476, Automatic Target Recognition XXV, 947600 (22 May 2015) [Google Scholar]
- Y. Zhao, R. Ball, J. Mosesian, J.-F. de Palma and B. Lehman, “Graph-Based Semi- supervised Learning for Fault Detection and Classification in Solar Photovoltaic Arrays,” in IEEE Transactions on Power Electronics, vol. 30, no. 5, pp. 2848–2858, (May 2015) [CrossRef] [Google Scholar]
- Arena, E., Corsini, A., Ferulano, R., Iuvara, D.A., Miele, E.S., Ricciardi Celsi, L., Sulieman, N.A., & Villari, M. Anomaly Detection in Photovoltaic Production Factories via Monte Carlo Pre-Processed Principal Component Analysis. Energies, 14(13), 3951.(2021) [CrossRef] [Google Scholar]
- Mallor, Fermin, et al. “A method for detecting malfunctions in PV solar panels based on electricity production monitoring.” Solar Energy 153: 51–63 (2017). [CrossRef] [Google Scholar]
- L.O. Chua, “CNN: A Vision of Complexity,” in ternational Journal of Bifurcation and ' Chaos, pp. 2219–2425, (1997). [CrossRef] [Google Scholar]
- A.F. Agarap, “Deep learning using rectified linear units (relu).,” arXiv preprint, (2018). [Google Scholar]
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