paper
2022
Post-processing & calibration
Downscaling & super-resolution New model or method
Classical ML (trees, GP, linear, kernels)6 h–3 days Journal
2022-04-19
008
Apr 2022
Sujan Ghimire, Ravinesh Chand Deo, David Casillas-Pérez et al.
Applied Energy
Hybrid deep and machine learning models use global climate model and observational predictors to boost solar radiation predictions; abstract not available, so scope is inferred from the title.
Boosting solar radiation predictions with global climate models, observational predictors and hybrid deep-machine learning algorithms
In one sentence. Hybrid deep and machine learning models use global climate model and observational predictors to boost solar radiation predictions; abstract not available, so scope is inferred from the title.
Labels
- Topic
- Post-processing & calibration, Downscaling & super-resolution
- Type
- New model or method
- Method
- Classical ML (trees, GP, linear, kernels)
- Time scale
- 6 h–3 days
- Domain
- Regional
- Data
- CMIP / climate model output, Station / in-situ
- Status
- Research
- Identifiers
- DOI:10.1016/j.apenergy.2022.119063 OpenAlex:W4224262388
- Added
- 2026-10-22
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