Generative AI for Energy: Multi-Horizon Power Consumption Forecasting using Large Language Models.
Kevin Roitero|Gianluca D'Abrosca|Andrea Zancola|Vincenzo Della Mea|Stefano Mizzaro
| Anthology ID: | DBLP:conf/cikm/RoiteroDZMM24 |
|---|---|
| Volume: | Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, CIKM 2024, Boise, ID, USA, October 21-25, 2024 |
| Year: | 2024 |
| Venue: | International Conference on Information and Knowledge Management (CIKM) |
| Publisher: | ACM |
| Pages: | 4015-4019 |
| URL: | https://doi.org/10.1145/3627673.3679933 |
| DOI: | https://doi.org/10.1145/3627673.3679933 |
| DBLP: | conf/cikm/RoiteroDZMM24 |
| BibTeX: |
@inproceedings{roitero-2024-generative,
author = {Kevin Roitero and
Gianluca D'Abrosca and
Andrea Zancola and
Vincenzo Della Mea and
Stefano Mizzaro},
editor = {Edoardo Serra and
Francesca Spezzano},
title = {{Generative AI for Energy: Multi-Horizon Power Consumption Forecasting using Large Language Models}},
booktitle = {{Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, CIKM 2024, Boise, ID, USA, October 21-25, 2024}},
pages = {4015--4019},
publisher = {ACM},
year = {2024},
url = {https://doi.org/10.1145/3627673.3679933},
doi = {https://doi.org/10.1145/3627673.3679933}
}