Artificial neural network models for forecasting and decision making

Some authors advocate artificial neural networks as a replacement for statistical forecasting and decision models; other authors are concerned that artificial neural networks might be oversold or just a fad. In this paper the authors review the literature comparing artificial neural networks and statistical models, particularly in regression-based forecasting, time series forecasting, and decision making. The present intention is to give a balanced assessment of the potential of artificial neural networks for forecasting and decision making models. The authors survey the literature and summarize several studies they have performed. Overall, the empirical studies find artificial neural networks comparable with their statistical counterparts. The authors note the need to consider the many mathematical proofs underlying artificial neural networks to determine the best conditions for their use in forecasting and decision making.