Electricity prices neural networks forecast using the Hilbert-Huang transform

The problem of forecasting of electicity prices is addressed in terms of joint approach employing the general regression artificial neural network and empirical mode decomposition approaches (EMD) which is part of Hilbert-Huang transform. The application of developed approach to day-ahead hourly time series has demonstrated the whole accuracy increase as well as peaks prediction.