Forecasting on Energy Consumption in China Based on Logistic-Markov

Abstract

Logistic model has a simple and apparent reality in mathematics, it can well characterize the feedback mechanism of energy consumption and economic growth. Based on the Logistic model, this paper proposes a new method for solving Logistic. With China’s total energy consumption in 2000-2013 as raw data, it uses Logistic model to predict our country’s total energy consumption. And then, it improves the predicted results with Markov chain. The results show that: the average relative error is 4.71 percent if it uses Logistic model, while the average relative error is only 2.45 percent if it is improved. The prediction accuracy is improved of 2.26 percent. Therefore, this paper uses Logistic-Markov method to predict energy consumption of 2014-2020. Finally, it analyzes energy consumption trends by predicting, and proposes the corresponding energy conservation measures.