Weather station selection for electric load forecasting
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DOI: 10.1016/j.ijforecast.2014.07.001
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- Ben Taieb, Souhaib & Hyndman, Rob J., 2014. "A gradient boosting approach to the Kaggle load forecasting competition," International Journal of Forecasting, Elsevier, vol. 30(2), pages 382-394.
- Hong, Tao & Pinson, Pierre & Fan, Shu, 2014.
"Global Energy Forecasting Competition 2012,"
International Journal of Forecasting, Elsevier, vol. 30(2), pages 357-363.
- Tao Hong & Pierre Pinson & Shu Fan, 2013. "Global Energy Forecasting Competition 2012," HSC Research Reports HSC/13/16, Hugo Steinhaus Center, Wroclaw University of Technology.
- Lloyd, James Robert, 2014. "GEFCom2012 hierarchical load forecasting: Gradient boosting machines and Gaussian processes," International Journal of Forecasting, Elsevier, vol. 30(2), pages 369-374.
- Tao Hong, 2014.
"Energy Forecasting: Past, Present, and Future,"
Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 32, pages 43-48, Winter.
- Tao Hong, 2013. "Energy forecasting: Past, present and future," HSC Research Reports HSC/13/15, Hugo Steinhaus Center, Wroclaw University of Technology.
- Nedellec, Raphael & Cugliari, Jairo & Goude, Yannig, 2014. "GEFCom2012: Electric load forecasting and backcasting with semi-parametric models," International Journal of Forecasting, Elsevier, vol. 30(2), pages 375-381.
- Charlton, Nathaniel & Singleton, Colin, 2014. "A refined parametric model for short term load forecasting," International Journal of Forecasting, Elsevier, vol. 30(2), pages 364-368.
- Tao Hong & Jason Wilson & Jingrui Xie, 2013. "Long term probabilistic load forecasting and normalization with hourly information," HSC Research Reports HSC/13/13, Hugo Steinhaus Center, Wroclaw University of Technology.
- Rafal Weron, 2006. "Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach," HSC Books, Hugo Steinhaus Center, Wroclaw University of Technology, number hsbook0601, December.
- Tao Hong & Pu Wang, 2013. "Fuzzy interaction regression for short term load forecasting," HSC Research Reports HSC/13/14, Hugo Steinhaus Center, Wroclaw University of Technology.
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Keywords
Hierarchical load forecasting; Global energy forecasting competition; Short term load forecasting; Long term load forecasting; Weather station combination; Cross validation; Out-of-sample test; Greedy algorithm;All these keywords.
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