An integrated model based on deep kernel extreme learning machine and variational mode decomposition for day-ahead electricity load forecasting
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-023-08702-x.pdf
Reference45 articles.
1. Nti IK, Teimeh M, Nyarko-Boateng O, Adekoya AF (2020) Electricity load forecasting: a systematic review. J Electr Syst Inf Technol. https://doi.org/10.1186/s43067-020-00021-8
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3. Kuster C, Rezgui Y, Mourshed M (2017) Electrical load forecasting models: a critical systematic review. Sustain Cities Soc 35(August):257–270. https://doi.org/10.1016/j.scs.2017.08.009
4. Huang GB, Zhu QY, Siew CK (2006) Extreme learning machine: theory and applications. Neurocomputing 70(1–3):489–501. https://doi.org/10.1016/j.neucom.2005.12.126
5. Huang G, Huang GB, Song S, You K (2015) Trends in extreme learning machines: a review. Neural Netw 61:32–48. https://doi.org/10.1016/j.neunet.2014.10.001
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