| Article ID: | iaor2016618 |
| Volume: | 33 |
| Issue: | 1 |
| Start Page Number: | 60 |
| End Page Number: | 69 |
| Publication Date: | Feb 2016 |
| Journal: | Expert Systems |
| Authors: | Lu Shin-Li, Tsai Chen-Fang |
| Keywords: | petroleum, demand |
In this paper, we adopt the exponentially weighted moving average (EWMA) method to develop the residual modification EWMA grey forecasting model REGM(1,1) and combines it with fuzzy theory to derive the fuzzy REGM or the FREGM(1,1) model. The proposed model is used to forecast annual petroleum demand in Taiwan. The experimental results show that the mean absolute percentage errors, median absolute percentage error, and symmetric mean absolute percentage error of FREGM(1,1) model are higher by 23.71, 12.26, and 23.06% respectively, compared with those obtained using the traditional GM(1,1) model.