paper
2021
Post-processing & calibration
Applications & impacts New model or method
Transformer / ViTRNN / LSTM / ConvLSTM6 h–3 daysInria Journal
2021-09-15
018
Sep 2021
Emmanouil Christoforou, Ioannis Z. Emiris, Apostolos Florakis et al.
Energy Systems
Inria
Spatio-temporal deep learning corrects day-ahead wind speed forecasts built on WRF predictions for energy use; abstract missing, judged from title.
Spatio-temporal deep learning for day-ahead wind speed forecasting relying on WRF predictions
In one sentence. Spatio-temporal deep learning corrects day-ahead wind speed forecasts built on WRF predictions for energy use; abstract missing, judged from title.
Labels
- Topic
- Post-processing & calibration, Applications & impacts
- Type
- New model or method
- Method
- Transformer / ViT, RNN / LSTM / ConvLSTM
- Time scale
- 6 h–3 days
- Domain
- Regional
- Data
- NWP analysis or forecasts (IFS, GFS, ...)
- Status
- Research
- Identifiers
- DOI:10.1007/s12667-021-00480-6 OpenAlex:W3201527902
- Added
- 2026-10-22
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