Cite
Day-AheadWind Power Forecasting Using a Two-Stage Hybrid Modeling Approach Based on SCADA and Meteorological Information, and Evaluating the Impact of Input-Data Dependency on Forecasting Accuracy.
MLA
Dehua Zheng, et al. “Day-AheadWind Power Forecasting Using a Two-Stage Hybrid Modeling Approach Based on SCADA and Meteorological Information, and Evaluating the Impact of Input-Data Dependency on Forecasting Accuracy.” Energies (19961073), vol. 10, no. 12, Dec. 2017, p. 1988. EBSCOhost, https://doi.org/10.3390/en10121988.
APA
Dehua Zheng, Min Shi, Yifeng Wang, Eseye, A. T., & Jianhua Zhang. (2017). Day-AheadWind Power Forecasting Using a Two-Stage Hybrid Modeling Approach Based on SCADA and Meteorological Information, and Evaluating the Impact of Input-Data Dependency on Forecasting Accuracy. Energies (19961073), 10(12), 1988. https://doi.org/10.3390/en10121988
Chicago
Dehua Zheng, Min Shi, Yifeng Wang, Abinet Tesfaye Eseye, and Jianhua Zhang. 2017. “Day-AheadWind Power Forecasting Using a Two-Stage Hybrid Modeling Approach Based on SCADA and Meteorological Information, and Evaluating the Impact of Input-Data Dependency on Forecasting Accuracy.” Energies (19961073) 10 (12): 1988. doi:10.3390/en10121988.