%0 Journal Article %1 journals/eaai/DuZLLWSZAY23 %A Du, Jian %A Zheng, Jianqin %A Liang, Yongtu %A Liao, Qi %A Wang, Bohong %A Sun, Xu %A Zhang, Haoran %A Azaza, Maher %A Yan, Jinyue %D 2023 %J Eng. Appl. Artif. Intell. %K dblp %P 105647 %T A theory-guided deep-learning method for predicting power generation of multi-region photovoltaic plants. %U http://dblp.uni-trier.de/db/journals/eaai/eaai118.html#DuZLLWSZAY23 %V 118

@article{journals/eaai/DuZLLWSZAY23, added-at = {2023-09-30T00:00:00.000+0200}, author = {Du, Jian and Zheng, Jianqin and Liang, Yongtu and Liao, Qi and Wang, Bohong and Sun, Xu and Zhang, Haoran and Azaza, Maher and Yan, Jinyue}, biburl = {https://www.bibsonomy.org/bibtex/2b603c19feedf5ced6215a8eff1477028/dblp}, ee = {https://doi.org/10.1016/j.engappai.2022.105647}, interhash = {6ec7b28c532ffca7564ccf81f3df834c}, intrahash = {b603c19feedf5ced6215a8eff1477028}, journal = {Eng. Appl. Artif. Intell.}, keywords = {dblp}, pages = 105647, timestamp = {2024-04-09T02:56:38.000+0200}, title = {A theory-guided deep-learning method for predicting power generation of multi-region photovoltaic plants.}, url = {http://dblp.uni-trier.de/db/journals/eaai/eaai118.html#DuZLLWSZAY23}, volume = 118, year = 2023 }