A symmetry-constrained analytical persistence operator for periodically correlated energy processes achieves accuracy gains over classical persistence while preserving periodic variance and covariance.
Using smart persistence and random forests to predict photovoltaic energy production
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Symmetry-Constrained Forecasting of Periodically Correlated Energy Processes
A symmetry-constrained analytical persistence operator for periodically correlated energy processes achieves accuracy gains over classical persistence while preserving periodic variance and covariance.