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Boosting short-term wind power prediction with Gaussian wake model enhanced machine learning inputs
A peer-reviewed journal article published by Elsevier on 2026-12-01 describes a method that combines a Gaussian wake model with machine-learning inputs to improve short-term wind power prediction. The supplied record contains only bibliographic metadata and no experimental results or impact details.
Categories: energy-and-resources, technology, science-and-space
Generated scores
Scores are based on the cited reporting and use a 1–10 scale. Read the methodology.
- Confidence
- 5/10
- Geographic reach
- 1/10
- Global importance
- 2/10
- Impact magnitude
- 2/10
- Positivity
- 6/10
- Urgency
- 1/10
Why it matters
The article reports research aimed at enhancing short-term wind power prediction.

