Table 1.
Commonly used ETS models.
Fig 1.
The STL decomposition of the logarithm of Bursa’s corrected NG consumption data (January 2014 to December 2022).
Fig 2.
The STL decomposition of the logarithm of Kayseri’s corrected NG consumption data (January 2014 to December 2022).
Fig 3.
(A) NGD values in Bursa for May and October over 2014-2022.
The original and corrected NGD values in Bursa for (B) July, (C) August, and (D) September 2014-2022. The original and corrected (“smoothed” gray lines during the summer periods in the figures) monthly NGD values in the training sets of (E) Bursa and (F) Kayseri.
Table 2.
Details on the time series models applied to the logarithms of the corrected NG data.
Table 3.
Accuracy metrics for the benchmark time series model on the training and test sets.
Fig 4.
The real NGD values, one-step ahead training set predictions, and multi-step ahead test set predictions using the TBATS model for Bursa.
Fig 5.
The real NGD values, one-step ahead training set predictions, and multi-step ahead test set predictions using the AI-AFTER algorithm for Kayseri.
Fig 6.
QQ Plot for the multi-step ahead test set prediction residuals for Bursa.
Fig 7.
QQ Plot for the multi-step ahead test set prediction residuals for Kayseri.
Table 4.
An example of how a local training set is selected in JITL-GPR model.
Table 5.
values that yield the minimum RMSE values of one-step ahead predictions.
Table 6.
Accuracy metrics for the JITL-GPR and TBATS models on the training and test sets.
Fig 8.
NGDP for (A) January, and (B) November 2023.
The filled circles represent the training sets in both subfigures, and also NGDPs for August-October 2023 (in the left subfigure); while the large diamonds denote the true value of the query point.
Fig 9.
Comparison of RMSE and MAPE values of different methods for the test set.
Fig 10.
Comparison of real, one-step ahead training set and multi-step ahead test set predictions of NGD values.
Fig 11.
One-step ahead training set and multi-step ahead test set prediction residuals.
Table 7.
Accuracy metrics for the JITL-GPR and SARIMA models on the additional dataset.
Fig 12.
One-step ahead training set and multi-step ahead test set predictions for NGD values for Turkey.