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A combined LSTM and LightGBM framework for improving deterministic and probabilistic wind energy forecasting

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WPP2014

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The aim of the probabilistic wind power forcasting track of GEFCom2014 was to predictc the wind power generation 24h ahead in 10 zones, correpsonding to 10 wind farms in Australia. Howerver the location is unknow.

The forcasts were to be expressed in the form of a set of 99 quantiles, with various norminal propportions between 0 and 1.

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A combined LSTM and LightGBM framework for improving deterministic and probabilistic wind energy forecasting

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