paper
2018
Post-processing & calibration
Applications & impacts New model or method
Classical ML (trees, GP, linear, kernels)6 h–3 days Journal
2018-11-12
022
Nov 2018
Pengwei Du
IEEE Transactions on Sustainable Energy
Ensemble of ANN, SVR and Gaussian process models blends NWP wind forecasts with weather-station data via Bayesian model averaging for wind power forecasting at ERCOT.
Ensemble Machine Learning-Based Wind Forecasting to Combine NWP Output With Data From Weather Station
In one sentence. Ensemble of ANN, SVR and Gaussian process models blends NWP wind forecasts with weather-station data via Bayesian model averaging for wind power forecasting at ERCOT.
Labels
- Topic
- Post-processing & calibration, Applications & impacts
- Type
- New model or method
- Method
- Classical ML (trees, GP, linear, kernels)
- Time scale
- 6 h–3 days
- Domain
- Local / station
- Data
- NWP analysis or forecasts (IFS, GFS, ...), Station / in-situ
- Status
- Research
- Identifiers
- DOI:10.1109/tste.2018.2880615 OpenAlex:W2901316757
- Added
- 2026-10-22
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