Unlocking the Potential of Deep Learning in Peak-Hour Series Forecasting.
Zhenwei Zhang|Xin Wang|Jingyuan Xie|Heling Zhang|Yuantao Gu
| Anthology ID: | DBLP:conf/cikm/ZhangWXZG23 |
|---|---|
| Volume: | Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, CIKM 2023, Birmingham, United Kingdom, October 21-25, 2023 |
| Year: | 2023 |
| Venue: | International Conference on Information and Knowledge Management (CIKM) |
| Publisher: | ACM |
| Pages: | 4415-4419 |
| URL: | https://doi.org/10.1145/3583780.3615159 |
| DOI: | https://doi.org/10.1145/3583780.3615159 |
| DBLP: | conf/cikm/ZhangWXZG23 |
| BibTeX: |
@inproceedings{zhang-2023-unlocking,
author = {Zhenwei Zhang and
Xin Wang and
Jingyuan Xie and
Heling Zhang and
Yuantao Gu},
editor = {Ingo Frommholz and
Frank Hopfgartner and
Mark Lee and
Michael P. Oakes and
Mounia Lalmas-Roelleke and
Min Zhang and
Rodrygo L. T. Santos},
title = {{Unlocking the Potential of Deep Learning in Peak-Hour Series Forecasting}},
booktitle = {{Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, CIKM 2023, Birmingham, United Kingdom, October 21-25, 2023}},
pages = {4415--4419},
publisher = {ACM},
year = {2023},
url = {https://doi.org/10.1145/3583780.3615159},
doi = {https://doi.org/10.1145/3583780.3615159}
}