Editorial: Research prospective on neural network forecasting

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Neural Networks In Business Time Series Forecasting: Benefits And Problems (2011, background): “Over the last two decades we have seen a rapid rise in the application of NNs to a range of business problems including managerial forecasting applications (Gorr, 1994; Sharda, 1994; Hill et al., 1996; Swanson & White, 1996; Zhang, 2001).”
25 years of time series forecasting (2006, background): “Gorr (1994) and Hill et al. (1994) suggested that future research should investigate and better define the borderline between where ANNs and “traditional” techniques outperform one other.”
A comparative study of linear and nonlinear models for aggregate retail sales forecasting (2003, background): “Gorr (1994) and many others believed that neural networks should be able to capture the seasonality in the data because of their universal approximation ability.”
25 Years of IIF Time Series Forecasting: A Selective Review (2005, background): “Gorr (1994) and Hill et al. (1994) suggested that future research should investigate and better define the borderline between where ANNs and “traditional” techniques out-perform one other.”