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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.

Sources

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