Comparing Variational and Empirical Mode Decomposition in Forecasting Day-Ahead Energy Prices

@article{Lahmiri2017ComparingVA,
  title={Comparing Variational and Empirical Mode Decomposition in Forecasting Day-Ahead Energy Prices},
  author={Salim Lahmiri},
  journal={IEEE Systems Journal},
  year={2017},
  volume={11},
  pages={1907-1910}
}
  • S. Lahmiri
  • Published 1 September 2017
  • Computer Science
  • IEEE Systems Journal
Recently, variational mode decomposition (VMD) has been proposed as an advanced multiresolution technique for signal processing. This study presents a VMD-based generalized regression neural network ensemble learning model to predict California electricity and Brent crude oil prices. Its performance is compared to that of the empirical mode decomposition (EMD) based generalized regression neural network (GRNN) ensemble model. Particle swarm optimization is used to optimize each GRNN initial… 

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