Approaches Of Predicting China's Energy Demand And Their Comparison

Many approaches are available to analyze and predict the energy demand. Based on the fuzzy neural network theory, Grey System Theory, artificial neural network and LS-SVM theory, the energy demand of China is analyzed and predicted in this paper. At first, eleven factors of energy demand are analyzed, among which two principal factors are obtained; Secondly, based on the two principal factors, a study is conducted to simulate and predict the energy demand of China. The findings show that the fuzzy neural network model is more accurate than the other five models. Based on the fuzzy neural network model, the total amount of China's energy consumption during the ten years from 2010 to 2020 is predicted, and the amount is consistent with that calculated by CErCmA prediction system, a software developed by Wei Yiming and his fellow workers.