Analysis of Supply and Demand Situation of Low Carbon Energy in China Based on Grey System Neural Network. Issue 1 (July 2020) - Xi, Jing
Abstract: At present, with the rapid development of the world economy, the demand for energy and resources is increasing day by day. Resource scarcity and environmental deterioration have become important issues facing the world. The energy development mode based on traditional fossil energy cannot support the rapid economic development of our country, which makes the energy transformation of our country imperative. In this paper, the grey GM (1, 1) model and artificial neural network are combined to modify the prediction results of GM (1, 1) model. In order to make GM(1, 1) model have higher prediction accuracy in medium and long-term prediction, partial data GM(1, 1) model groups are respectively established by using partial data sequences of original data, and the nonlinear mapping relationship between fitting values and original data is calculated by establishing this partial GM(1, 1) model groups by using BP neural network. The calculation results show that the prediction method is reliable and has high prediction accuracy.