# Wind speed forecast using random forest learning method

arXiv: https://arxiv.org/abs/2203.14909 · HTML: https://mlsanity.com/paper/2203.14909/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
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- First posted on arXiv 23 Mar 2022.

## Abstract (arXiv)

Wind speed forecasting models and their application to wind farm operations are attaining remarkable attention in the literature because of its benefits as a clean energy source. In this paper, we suggested the time series machine learning approach called random forest regression for predicting wind speed variations. The computed values of mutual information and auto-correlation shows that wind speed values depend on the past data up to 12 hours. The random forest model was trained using ensemble from two weeks data with previous 12 hours values as input for every value. The computed root mean square error shows that model trained with two weeks data can be employed to make reliable short-term predictions up to three years ahead.