%0 Journal Article %1 journals/eswa/JalalifarDG24 %A Jalalifar, Rasoul %A Delavar, Mahmoud Reza %A Ghaderi, Seyed Farid %D 2024 %J Expert Syst. Appl. %K dblp %N Part B %P 121487 %T SAC-ConvLSTM: A novel spatio-temporal deep learning-based approach for a short term power load forecasting. %U http://dblp.uni-trier.de/db/journals/eswa/eswa237.html#JalalifarDG24 %V 237

@article{journals/eswa/JalalifarDG24, added-at = {2023-11-29T00:00:00.000+0100}, author = {Jalalifar, Rasoul and Delavar, Mahmoud Reza and Ghaderi, Seyed Farid}, biburl = {https://www.bibsonomy.org/bibtex/2632d66204046db619c958791a6331f2b/dblp}, ee = {https://doi.org/10.1016/j.eswa.2023.121487}, interhash = {e0c1e6f1633b89c10d99fe4905231288}, intrahash = {632d66204046db619c958791a6331f2b}, journal = {Expert Syst. Appl.}, keywords = {dblp}, month = {March}, number = {Part B}, pages = 121487, timestamp = {2024-04-08T10:10:06.000+0200}, title = {SAC-ConvLSTM: A novel spatio-temporal deep learning-based approach for a short term power load forecasting.}, url = {http://dblp.uni-trier.de/db/journals/eswa/eswa237.html#JalalifarDG24}, volume = 237, year = 2024 }