Forecasting and analyzing influenza activity in Hebei Province, China, using a CNN-LSTM hybrid model
The hybrid CNN-LSTM model had better prediction performances than the SARIMA model, CNN model, LSTM model, and XGBoost model. This hybrid model could provide more accurate influenza activity projections in the Hebei Province.
Authors
- Caixiao Jiang
- Guangyue Han
- Yan Li (ORCID: https://orcid.org/0000-0002-4694-4926)
- Zhihuai Xing
- Qi Li (ORCID: https://orcid.org/0000-0002-2825-3531)
- Xu Han (ORCID: https://orcid.org/0000-0003-3491-8576)
- Wentao Wu (ORCID: https://orcid.org/0000-0003-4417-9033)
- Minghao Geng (ORCID: https://orcid.org/0009-0008-7330-0588)
- Shangze Liu
- Nana Guo
- Guofan Li
Institutions
- Hebei Medical University (CN)
- Hebei Provincial Center for Disease Control and Prevention (CN)
Publication Details
- Journal
- BMC Public Health
- Published
- 2024-08-12
- DOI
- https://doi.org/10.1186/s12889-024-19590-8
- Citations
- 17
- Primary Topic
- Air Quality Monitoring and Forecasting
- Type
- article
- Field-Weighted Citation Impact
- 3.50