paper
2022
Post-processing & calibration
Applications & impacts New model or method
6 h–3 days Journal
2022-02-24
022
Feb 2022
Yan Han, Lihua Mi, Lian Shen et al.
Applied Energy
Hybrid deep learning corrects numerical weather forecasts of short-term wind speed; the abstract is unavailable, so the gain is unquantified.
A short-term wind speed prediction method utilizing novel hybrid deep learning algorithms to correct numerical weather forecasting
In one sentence. Hybrid deep learning corrects numerical weather forecasts of short-term wind speed; the abstract is unavailable, so the gain is unquantified.
Labels
- Topic
- Post-processing & calibration, Applications & impacts
- Type
- New model or method
- Time scale
- 6 h–3 days
- Domain
- Local / station
- Data
- NWP analysis or forecasts (IFS, GFS, ...)
- Status
- Research
- Identifiers
- DOI:10.1016/j.apenergy.2022.118777 OpenAlex:W4213450433
- Added
- 2026-10-22
Labels and summary are generated by Claude and reviewed weekly. Wrong? Edit this entry.