APA (7th ed.) Citation

Qu, Z., Li, J., Hou, X., & Gui, J. (2023). A D-stacking dual-fusion, spatio-temporal graph deep neural network based on a multi-integrated overlay for short-term wind-farm cluster power multi-step prediction. Energy (Oxford), 281, 128289. https://doi.org/10.1016/j.energy.2023.128289

Chicago Style (17th ed.) Citation

Qu, Zhijian, Jian Li, Xinxing Hou, and Jianglin Gui. "A D-stacking Dual-fusion, Spatio-temporal Graph Deep Neural Network Based on a Multi-integrated Overlay for Short-term Wind-farm Cluster Power Multi-step Prediction." Energy (Oxford) 281 (2023): 128289. https://doi.org/10.1016/j.energy.2023.128289.

MLA (9th ed.) Citation

Qu, Zhijian, et al. "A D-stacking Dual-fusion, Spatio-temporal Graph Deep Neural Network Based on a Multi-integrated Overlay for Short-term Wind-farm Cluster Power Multi-step Prediction." Energy (Oxford), vol. 281, 2023, p. 128289, https://doi.org/10.1016/j.energy.2023.128289.