A Framework for Data Mining in Wind Power Time Series

@inproceedings{Kramer2014AFF,
  title={A Framework for Data Mining in Wind Power Time Series},
  author={Oliver Kramer and Fabian Gieseke and Justin Heinermann and Jendrik Poloczek and Nils Andr{\'e} Treiber},
  booktitle={DARE},
  year={2014}
}
Wind energy is playing an increasingly important part for ecologically friendly power supply. The fast growing infrastructure of wind turbines can be seen as large sensor system that screens the wind energy at a high temporal and spatial resolution. The resulting databases consist of huge amounts of wind energy time series data that can be used for prediction, controlling, and planning purposes. In this work, we describe WindML, a Python-based framework for wind energy related machine learning… 

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