In this paper, SARIMA, ETS, TBATS, PROPHET and NN approaches are provided to forecast quarterly electricity connections processes by using R-Studio. After splitting data into training and test sets, several data preprocessing techniques, such as anomaly detection and stationarity checking, are conducted.
MAPE and MASE are used for comparing forecast accuracy on both train and test sets to find the best fit model.