Applications of artificial neural networks to the nonlinear combination of forecasts

This paper proposes artificial neural networks (ANN) as a tool for nonlinear combination of forecasts. In this study, three forecasting models are used for individual forecasts, and then two linear combining methods are used to compare with the ANN combining method. The comparative experiment using real‐world data shows that the prediction by the ANN method outperforms those by linear combining methods. The paper suggests that the ANN method can be used as an alternative to conventional linear combining methods to achieve greater forecasting accuracy.