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EALSTM-QR: Interval wind-power prediction model based on numerical weather prediction and deep learning

Xiaosheng Peng, Hongyu Wang, Jianxun Lang, Wenze Li, Qiyou Xu, Zuowei Zhang, Tao Cai, Shanxu Duan, Fangjie Liu, Chaoshun Li

2020Energy133 citationsDOI

Topics & Concepts

Numerical weather predictionWind power forecastingArtificial neural networkWind powerPrediction intervalPredictive modellingWind speedComputer scienceInterval (graph theory)MeteorologyPower (physics)Deep learningArtificial intelligenceElectric power systemMachine learningEngineeringMathematicsGeographyElectrical engineeringQuantum mechanicsPhysicsCombinatoricsEnergy Load and Power ForecastingWind Energy Research and DevelopmentSolar Radiation and Photovoltaics
EALSTM-QR: Interval wind-power prediction model based on numerical weather prediction and deep learning | Litcius