A symmetry-constrained analytical persistence operator for periodically correlated energy processes achieves accuracy gains over classical persistence while preserving periodic variance and covariance.
A comparative study of machine learning-based methods for global horizontal irradiance forecasting,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
physics.data-an 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
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.