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Wind speed forecasting method based on deep learning strategy using empirical wavelet transform; long short term memory neural network and Elman neural network.[J].Hui Liu;Xi-wei Mi;Yan-fei Li.Energy Conversion and Management.2018,
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Wind power day-ahead prediction with cluster analysis of NWP.[J].Lei Dong;Lijie Wang;Shahnawaz Farhan Khahro;Shuang Gao;Xiaozhong Liao.Renewable and Sustainable Energy Reviews.2016,
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A Numerical Verification of Self-Similar Multiplicative Theory for Small-Scale Atmospheric Turbulent Convection.[J].Song Zong-Peng;Hu Fei;Liu Yu-Jue;Cheng Xue-Ling;Liu Lie;Xu Jing-Jing.Atmospheric and Oceanic Science Letters.2014, 2
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Wind power prediction based on numerical and statistical models.[J].Christos Stathopoulos;Akrivi Kaperoni;George Galanis;George Kallos.Journal of Wind Engineering & Industrial Aerodynamics.2013,
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Probabilistic forecasts of wind speed: ensemble model output statistics by using heteroscedastic censored regression.[J].Thordis L.Thorarinsdottir;TilmannGneiting.Journal of the Royal Statistical Society: Series A (Statistics in Society).2010, 2
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Wind forecasts for wind power generation using the Eta model.[J]..Renewable Energy.2009, 6
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Modeling and predicting complex space–time structures and patterns of coastal wind fields.[J].Montserrat Fuentes;Li Chen;Jerry M. Davis;Gary M. Lackmann.Environmetrics.2005, 5

