Neural networks: Forecasting breakthrough or passing fad?
By C. Chatfield. 1993
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- J. De Gooijer
- Rob J Hyndman
- Sven F. Crone
- Konstantinos Nikolopoulos
- Fotios Petropoulos
- James W. Taylor
- Christoph Bergmeir
- Nikolaos Kourentzes
Citations in the corpus
- 25 years of time series forecasting (2006, background): “However, in two editorials in this Journal, Chatfield (1993, 1995) questioned whether ANNs had been oversold as a miracle forecasting technique.”
- Findings from Evidence-Based Forecasting: Methods for Reducing Forecast Error (2006, background): “Early reviews on the accuracy of neural nets were not favourable; Chatfield (1993) refers to some of these. However, Adya and Collopy (1998) found eleven studies that met the criteria for a comparative evaluation, and in 8 of these (73%), neural nets were more accurate.”
- Forecasting for Marketing (2005, unknown): “Chatfield (2000) summarizes research on prediction intervals. Unfortunately, prediction intervals are not widely used in practice. Rush and Page (1979) found a decreasing use of measures of uncertainty for metals forecasts from 22 percent of forecasts during the period 1910-1939 to only 8 percent du”
- Neural networks for short-term load forecasting: a review and evaluation (2001, background): “Judging from the number of papers, NN-based forecasting systems have not turned into a “passing fad,” as it was feared they might [ 12 ].”
- 25 Years of IIF Time Series Forecasting: A Selective Review (2005, background): “However, in two editorials in this Journal, Chatfield (1993, 1995) questioned whether ANNs had been oversold as a miracle forecasting technique.”
- Advances in forecasting with neural networks? Empirical evidence from the NN3 competition on time series prediction (2011, methodology): “With regard to accuracy, the top 10 algorithms indicate some progress in accuracy, but not quite enough to confirm a breakthrough for NNs in the view of Chatfield (1993). Unsurprisingly, the top contenders for the M3 monthly data are also ranked highly for this subset: Theta (B07), ForecastPro (B03)”