A New Grey Convolution Model And Its Application In Carbon Dioxide Emission Prediction

Carbon dioxide-based greenhouse gas emissions have led to the accumulation of greenhouse effects,and the global warming has caused frequent disasters.It is of great practical significance to accurately predict carbon dioxide emissions under the condition of incomplete carbon dioxide emission system data.Based on the analysis of carbon dioxide emission research,this thesis uses a new grey prediction model to model and analyze China’s provincial carbon dioxide emissions in view of the "little data" and uncertainty in the research of carbon dioxide emissions,so as to provide reliable data support for the formulation of policies to reduce carbon dioxide emissions.The grey prediction model is a modeling method for "minority data" systems and has been applied in many fields such as economy,transportation,energy and environment etc.Due to the complexity and uncertainty of the system,the prediction accuracy of the existing grey prediction model does not meet the requirements.In this thesis,two new grey multivariate prediction models are constructed according to the principle of "new information first" and carbon dioxide emissions in China province are predicted and studied.The main contents of this thesis include:(1)In view of the shortcomings of traditional first-order additive grey multivariate convolution model,a smooth additive generation operator with the principle of "difference information" is introduced to construct a smooth additive grey multivariate convolution model.Based on the parameter solution,it is proved that the smooth additive grey multivariate convolution model is superior to the traditional first order additive grey multivariate convolution model in terms of model properties.(2)Based on the principle of "new information first" the additive generator with damping parameters is introduced into the grey multivariate convolution model to construct the damping additive grey multivariate convolution model.At the same time,the method of solving the damping parameter is given,and the properties of the damping additive grey multivariable convolution model are analyzed from the angle of initial value utilization,stability of the solution and reduction error.Finally,the accuracy of the damping additive grey multivariate convolution model is proved by the example.(3)Research on China’s provincial carbon dioxide emissions based on grey model.Firstly,regional division of China’s provinces.Secondly,a new grey multivariate model is constructed based on energy consumption and population at the end of the year to predict the carbon dioxide emissions of Chinese provinces.Finally,the prediction results of provincial carbon dioxide emissions are analyzed,and suggestions are made to each province to reduce carbon dioxide emissions based on the prediction results.