A hybrid BiLSTM-XGBoost model for short-term forecasting of key parameters in nuclear power systems
- DOI
- 10.1038/s41598-026-44745-5
- Published
- 2026-05-05
- Container
- Scientific Reports
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-026-44745-5,
title = {A hybrid BiLSTM-XGBoost model for short-term forecasting of key parameters in nuclear power systems},
author = {Jichong Lei and Zhiqiang Peng and Zining Ni and Changan Ren and Hong Hu and Xu Gao and Kun Xu and Yuhan Cao},
year = {2026},
journal = {Scientific Reports},
doi = {10.1038/s41598-026-44745-5},
url = {https://doi.org/10.1038/s41598-026-44745-5}
}RIS
TY - JOUR TI - A hybrid BiLSTM-XGBoost model for short-term forecasting of key parameters in nuclear power systems AU - Jichong Lei AU - Zhiqiang Peng AU - Zining Ni AU - Changan Ren AU - Hong Hu AU - Xu Gao AU - Kun Xu AU - Yuhan Cao PY - 2026 JO - Scientific Reports DO - 10.1038/s41598-026-44745-5 UR - https://doi.org/10.1038/s41598-026-44745-5 ER -
APA
Lei, J., Peng, Z., Ni, Z., Ren, C., Hu, H., Gao, X., Xu, K., & Cao, Y. (2026). A hybrid BiLSTM-XGBoost model for short-term forecasting of key parameters in nuclear power systems. Scientific Reports. https://doi.org/10.1038/s41598-026-44745-5
Source records
- crossref · retrieved 2026-11-09T04:59:00.320Z