Photovoltaic power forecasting with ensemble of learners: large test case from PV plants in Italy, Zambia and Australia

AUTHORS
Lorenzo Gigoni, Alessandro Betti, Fabrizio Ruffini, Ciro Lanzetta, Antonio Piazzi, Mauro Tucci e Michela Moschella.

ABSTRACT
An innovative ensamble-based forecasting method based on a number of machine learning techniques independently trained and combined in a cooperative ensemble fashion.

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