articleTop 1% cited
Deep learning based ensemble approach for probabilistic wind power forecasting
Applied Energy · 2016 · Vol. 188 · pp. 56–70
Huaizhi Wang(Shenzhen University)Gangqiang Li(Shenzhen University)Guibin Wang✉(Shanghai Tunnel Engineering Rail Transit Design & Research Institute)Jianchun Peng(Shenzhen University)Hui Jiang(Shenzhen University)Yitao Liu(Shenzhen University)
Energy Load and Power ForecastingElectric Power System OptimizationComputational Physics and Python ApplicationsWind powerProbabilistic logicWind power forecastingProbabilistic forecastingComputer scienceWavelet transformElectric power systemArtificial neural networkWind speedEnsemble learning
Funding
- National Natural Science Foundation of China
- Natural Science Foundation of Guangdong Province
- National Key Research and Development Program of China
Citations
730
FWCI
32.81
field-weighted impact
References
46
Percentile
100%
vs. same field & year
Citations per year
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References
Traffic Flow Prediction With Big Data: A Deep Learning Approach
IEEE Transactions on Intelligent Transportation Systems · 2014 · 2,943 citations
On comparing three artificial neural networks for wind speed forecasting
Applied Energy · 2010 · 698 citations
Probabilistic Forecasting of Wind Power Generation Using Extreme Learning Machine
IEEE Transactions on Power Systems · 2013 · 739 citations
Probabilistic Forecasts, Calibration and Sharpness
Journal of the Royal Statistical Society Series B (Statistical Methodology) · 2007 · 1,691 citations
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