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[1]Qinghua Hu, Shenghua Xiong. Correlation aware multi-step ahead wind speed forecasting with heteroscedastic multi-kernel learning Energy Conversion and Management, 2018, 163: 384-406
[2]Dipti Srinivasan, Zheng Wang. Wind power curve modeling and wind power forecasting with inconsistent data IEEE Transactions on Sustainable Energy, 2018, 10(1): 16-25
[3]Deyu Meng, Pengfei Zhu. Deterministic and probabilistic wind power forecasting using a variational Bayesian-based adaptive r Applied Energy, 2017, 208: 1097-1112
[4]Jianzhou Wang. Short-term wind speed forecasting using a hybrid model [J]. Energy, 2017, 119: 561-577
[5]Qinghua Hu. Self-adaptive robust nonlinear regression for unknown noise via mixture of Gaussians Neurocomputing, 2017, 235: 274-286
[6] A novel wind speed forecasting model for wind farms of Northwest China International Journal of Green Energy, 2017, 14(5): 463-478
[7]Zongxia Xie, Pengfei Zhu, Daren Yu. On estimating uncertainty of wind energy with mixture of distributions Energy, 2016, 112: 935-962
[8]Xiang Wei. A hybrid wind speed forecasting model based on phase space reconstruction theory and Markov model: A case study of wind farms in northwest China [J]. Energy, 2015, 91: 556-572
[9]Ping Jiang. The study and application of a novel hybrid forecasting model–A case study of wind speed forecasting in China [J]. Applied Energy, 2015, 143: 472-488
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