Data Science and Big Data in Energy Forecasting
Abstract
:- (1)
- Energy-related time series analysis;
- (2)
- Energy-related time series model;
- (3)
- Energy-related time series forecasting;
- (4)
- Non-parametric time series approaches.
- (1)
- Spain (5);
- (2)
- China (2);
- (3)
- Taiwan (2);
- (4)
- Canada (1);
- (5)
- Poland (1);
- (6)
- Chile (1);
- (7)
- France (1).
Funding
Acknowledgments
Conflicts of Interest
References
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Share and Cite
Martínez-Álvarez, F.; Troncoso, A.; Riquelme, J.C. Data Science and Big Data in Energy Forecasting. Energies 2018, 11, 3224. https://doi.org/10.3390/en11113224
Martínez-Álvarez F, Troncoso A, Riquelme JC. Data Science and Big Data in Energy Forecasting. Energies. 2018; 11(11):3224. https://doi.org/10.3390/en11113224
Chicago/Turabian StyleMartínez-Álvarez, Francisco, Alicia Troncoso, and José C. Riquelme. 2018. "Data Science and Big Data in Energy Forecasting" Energies 11, no. 11: 3224. https://doi.org/10.3390/en11113224