Dec 12, 2017 · The results show that AS-GAR model has the best forecasting performance among the four GAR models, and it outperforms ARIMA model, BP neural ...

The results show that AS-GAR model has the best forecasting performance among the four GAR models, and it outperforms ARIMA model, BP neural network model, SVM ...

The results show that AS-GAR model has the best forecasting performance among the four GAR models, and it outperforms ARIMA model, BP neural network model, ...

It uses the GMDH-based autoregressive (GAR) model proposed in the authors' previous work [40] to predict the linear trend of the energy consumption time series, ...

Oct 27, 2016 · This paper combines the traditional auto-regressive model with group method of data handling (GMDH) suitable for small sample prediction, and ...

The results show that AS-GAR model has the best forecasting performance among the four GAR models, and it outperforms ARIMA model, BP neural network model, SVM ...

This study combines the traditional auto-regressive model with group method of data handling (GMDH) suitable for small sample prediction.

China's Energy Consumption Forecasting by GMDH Based Auto-Regressive Model. XIE Ling,XIAO Jin,HU Yi,ZHAO Hengjun,XIAO Yi. Journal of Systems Science and ...

The proposed model can be used to improve the accuracy of energy consumption forecasting. The model can also be applied to other time series forecasting ...

Comparison of China's primary energy consumption forecasting by using ARIMA (the autoregressive integrated moving average) model and GM(1,1) model.