A New Hybrid Wavelet-Neural Network Approach for Forecasting Electricity

Heni BOUBAKER, SOUHIR BEN AMOR, Hichem Rezgui
2020 Energy Studies Review  
This study investigates the performance of a novel neural network technique in the problem of price forecasting. To improve the prediction accuracy using each model's unique features, this research proposes a hybrid approach that combines the -factor GARMA process, empirical wavelet transform and the local linear wavelet neural network (LLWNN) methods, to form the GARMA-WLLWNN process. In order to verify the validity of the model and the algorithm, the performance of the proposed model is
more » ... ted using data from Polish electricity markets, and it is compared with the dual generalized long memory -factor GARMA-G-GARCH model and the individual WLLWNN. The empirical results demonstrated the proposed hybrid model can achieve a better predicting performance and prove that is the most suitable electricity market forecasting technique.
doi:10.15173/esr.v24i1.4135 fatcat:qjppz6be3zdibnvd47newdftiy