REDf: a deep learning model for short-term load forecasting to facilitate renewable integration and attaining the SDGs 7, 9, and 13.
- DOI
- 10.7717/peerj-cs.2819
- Published
- 2025
- Container
- PeerJ. Computer science
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.7717/peerj-cs.2819,
title = {REDf: a deep learning model for short-term load forecasting to facilitate renewable integration and attaining the SDGs 7, 9, and 13.},
author = {Miah MSU and Sulaiman J and Islam MI and Masuduzzaman M and Lipu MSH and Nugraha R},
year = {2025},
journal = {PeerJ. Computer science},
doi = {10.7717/peerj-cs.2819},
url = {https://doi.org/10.7717/peerj-cs.2819}
}RIS
TY - JOUR TI - REDf: a deep learning model for short-term load forecasting to facilitate renewable integration and attaining the SDGs 7, 9, and 13. AU - Miah MSU AU - Sulaiman J AU - Islam MI AU - Masuduzzaman M AU - Lipu MSH AU - Nugraha R PY - 2025 JO - PeerJ. Computer science DO - 10.7717/peerj-cs.2819 UR - https://doi.org/10.7717/peerj-cs.2819 ER -
APA
MSU, M., J, S., MI, I., M, M., MSH, L., & R, N. (2025). REDf: a deep learning model for short-term load forecasting to facilitate renewable integration and attaining the SDGs 7, 9, and 13.. PeerJ. Computer science. https://doi.org/10.7717/peerj-cs.2819
Source records
- pubmed · retrieved 2026-09-25T03:18:54.622Z