It is depicted that including the utilization of limited energy usage and environmental data as one of the model's input variables, the electricity forecasting precision is more accurate, precise and can be improved.
The Error Correction Model displays better fitting accuracy and forecast precision than the MLR model.
In this study, we present the advantage of DWT to improve time series forecasting precision.
However, the application ranges and forecasting precision of these methods vary considerably.
Compared with the traditional model, TFRWν-SVM method requires fewer samples and has better forecasting precision.
The final results indicate that IEWT can effectively reduce the noise interference and enhance the forecasting precision of complex signal.
The result indicates the trend is consistent with the project practice, the predicted value and the actual value's relative error ≤5.9%, satisfies the forecasting precision (≤10%) and the forecasting precision is high, this model has the application value.
The results of popular forecasting precision indexes show that our proposed model is an effective forecasting technique for seasonal time series with nonlinear trend.
Spurious regression may be observed while using an MLR model without testing the stationarity of the series, thus decreasing forecast precision.
