E3S Web Conf.
Volume 252, 20212021 International Conference on Power Grid System and Green Energy (PGSGE 2021)
|Number of page(s)||7|
|Section||Energy Technology Research and Development and Green Energy-Saving Applications|
|Published online||23 April 2021|
- Hart, G.W. (1992) Nonintrusive appliance load monitoring. Proceedings of the IEEE, 80(12): 1870–1891. [Google Scholar]
- Faustine, A., Mvungi, N.H., Kaijage, S., Michael, K. (2017) A survey on non-intrusive load monitoring methodies and techniques for energy disaggregation problem. arXiv 2017, arXiv: 1703.00785. [Google Scholar]
- Rahimpour, A., Qi, H., Fugate, D., Kuruganti, T. Non-Intrusive Energy Disaggregation Using Non-Negative Matrix Factorization With Sum-to-k Constraint. (2017) IEEE T rans. Power Syst, 32: 4430–4441. [Google Scholar]
- Kong, W.C., Dong, Z.Y., Ma, J., Hill, D.J., Zhao, J.H., Luo, F.J. (2018) An Extensible Approach for Non-Intrusive Load Disaggregation With Smart Meter Data. IEEE TRANSACTIONS ON SMART GRID, 9(4): 3362–3372. [Google Scholar]
- Kelly, J., Knottenbelt, W. (2015) Neural NILM: Deep neural networks applied to energy disaggregation. In: Proceedings of the 2nd ACM International Conference on Embedded Systems for Energy-Efficient Built Environments. Seoul. pp. 55–64. [Google Scholar]
- Zhang, C., Zhong, M., Wang, Z., Goddard, N., Sutton, C. (2018) Sequence-to-point learning with neural networks for nonintrusive load monitoring. In: The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18). New Orleans. pp. 2604–2611. [Google Scholar]
- D’Incecco, M., Squartini, S., Zhong, M. J. (2020) Transfer Learning for Non-Intrusive Load Monitoring. IEEE TRANSACTIONS ON SMART GRID, 11(2): 1419–1429. [Google Scholar]
- Shin, C., Joo, S., Yim, J., Lee, H., Moon, T., Rhee, W. (2019) Subtask gated networks for non-intrusive load monitoring. In: The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19). Honolulu. pp. 1150–1157 [Google Scholar]
- He, K.M., Zhang, X.Y., Ren, S.Q., Sun, J. (2016) Deep Residual Learning for Image Recognition. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition. Seattle. pp: 770–778 [Google Scholar]
- Murray, D., Stankovic, L., Stankovic, V. (2017) An electrical load measurements dataset of united kingdom households from a two-year longitudinal study. Scientific data, vol. 4, p. 160122. [PubMed] [Google Scholar]
- Rafiq, H., Shi, X., Zhang, H., et al. (2020) A Deep Recurrent Neural Network for Non-Intrusive Load Monitoring Based on Multi-Feature Input Space and Post-Processing. Energies, 13(9): 2195. [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.