Research on the Prediction of Carbon Emission Based on the Chaos Theory and Neural Network

Abstract

In this paper, carbon emissions and the related problems are studied based on carbon emission time series data and the chaos theory, in order to make clear the relationship among the data, and we reconstruct the time series by phase space reconstruction. Finally, the predicting model of the carbon emission is established with BP neural network. The simulation results show that the hybrid of chaos theory and BP neural network can be used to fit and predict the carbon emissions time series without considering other factors, which is easier and more accurate than other predicting method.

Keywords

• Carbon emissions
• Chaos theory
• BP neural network
• Phase space reconstruction