Neural network models for forecast: a review

Neural networks are advocated as a replacement for statistical forecasting methods. The authors review the literature comparing neural networks and classical forecasting methods, particularly in causal forecasting, time series forecasting, and judgmental forecasting. They provide not only an overview and evaluation of the literature but also summarize several studies performed which address the typical criticisms of work in this area. Overall, the empirical studies find neural networks at least as good as their classical counterparts.<
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