Article ID: | iaor19972361 |
Country: | Netherlands |
Volume: | 12 |
Issue: | 5 |
Start Page Number: | 495 |
End Page Number: | 512 |
Publication Date: | Dec 1996 |
Journal: | International Journal of Forecasting |
Authors: | Flores Benito E., Vokurka Robert J., Pearce Stephen L. |
Keywords: | forecasting: applications |
The authors examined automatic feature identification and graphical support in rule-based expert systems for forecasting. The rule-based expert forecasting system (RBEFS) includes predefined rules to automatically identify features of a time series and selects the extrapolation method to be used. The system can also integrate managerial judgment using a graphical interface that allows a user to view alternate extrapolation methods two at a time. The use of the RBEFS led to a significant improvement in accuracy compared to equal-weight combinations of forecasts. Further improvement were achieved with the user interface. For 6-year ahead ex ante forecasts, the rule-based expert forecasting system has a median absolute percentage error (MdAPE) 15% less than that of equally weighted combined forecasts and a 33% improvement over the random walk. The results of the system are also compared to those of an earlier rule-based expert system which required human judgments about some features of the time series data. The results of the comparison of the two rule-based expert systems showed no significant differences between them.