*3.4. Performance Measures Used*

Each model's performance was measured using three key performance measures: symmetric mean absolute percentage error (sMAPE), mean absolute error (MAE), and root-mean-square error (RMSE). Motepe et al. state that the MAE, RMSE, MPE, MAPE, and sMAPE are common forecasting error measurements [30]. They further state the challenge that the MAPE faces when target values are too small, which leads to errors being too large. The three used performance measurements in this research are presented in (17)–(19).

$$sMAPE = \frac{2}{N} \sum\_{k=1}^{N} \frac{|F\_k - T\_k|}{|F\_k| + |T\_k|} \tag{17}$$

$$MAE = \frac{\sum\_{k=1}^{N} |F\_k - T\_k|}{N} \tag{18}$$

$$RMSE = \sqrt{\frac{\sum\_{k=1}^{N} (F\_k - T\_k)^2}{N}} \tag{19}$$

where *Fk* is the forecasted value, *Tk* is the target value, and *N* is the number of forecasted values.
