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Table 3 shows the out-of-sample forecast results using linear and nonlinear time series methods.
It was observed from the results presented in Tables 14, 16 and 18 that in terms of the ( varpi_{m} ) which combines the accuracies of the models MAE, MSE and MAPE into a single evaluation score (Eq. 135); S-GFMAPR produced the best out-of-sample forecast results in all but one of the data set analysed.
From September 2017 to December 2022 outside of the sample, the forecast results of VAR show that annually average Brent crude oil prices for 2017 2022 are $53.0, $61.3, $74.4, $90.0, $105.5, and $120.7 per barrel, respectively.
The forecasting results are accurate.
The forecasting results are good.
Only the best forecasting results are reported.
However, the forecasting results are not desirable.
The forecasting results are more stable.
Finally, the system load forecasting results are obtained by summing up all the ARIMA forecasting results.
The final forecasting results are obtained by adding the forecasting results of these two models.
Section Comparison of forecasting results compares the performance of the models for the forecasting benchmark dataset.
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