Solar Power Forecasting Using Dynamic Meta-Learning Ensemble of Neural Networks
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Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-030-01418-6_52
Reference10 articles.
1. Pedro, H.T.C., Coimbra, C.F.M.: Assessment of forecasting techniques for solar power production with no exogenous inputs. Sol. Energy 86, 2017–2028 (2012)
2. Rana, M., Koprinska, I., Agelidis, V.: Univariate and multivariate methods for very short-term solar photovoltaic power forecasting. Energy Convers. Manag. 121, 380–390 (2016)
3. Chu, Y., Urquhart, B., Gohari, S.M.I., Pedro, H.T.C., Kleissl, J., Coimbra, C.F.M.: Short-term reforecasting of power output from a 48 MWe solar PV plant. Sol. Energy 112, 68–77 (2015)
4. Chen, C., Duan, S., Cai, T., Liu, B.: Online 24-h solar power forecasting based on weather type classification using artificial neural networks. Sol. Energy 85, 2856–2870 (2011)
5. Rana, M., Koprinska, I., Agelidis, V.G.: 2D-interval forecasts for solar power production. Sol. Energy 122, 191–203 (2015)
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