Forecasting carbon emissions using MGM(1,m|λ,γ) model with the similar meteorological condition

Carbon emission is a common concern of the international community and effectively predicting its future trend is necessary for emission reduction planning. Considering that the change trend of carbon emissions is unstable, more attention should be paid to the correction effect of new information on the development trend. Therefore, based on the traditional MGM(1,m) model, this paper introduces the new information priority operator X and nonlinear parameter gamma to strengthen the role of new information, further constructs three comparison models of MGM(1,m vertical bar lambda), MGM(1,m vertical bar gamma) and MGM(1,m vertical bar lambda,gamma).Then we apply the new model to the carbon emission prediction of different regions (cities, countries and continents) and different trends (fluctuating, rising and declining). The results illustrate that the new model has higher prediction accuracy, and adding dynamic parameters is a scientific and practical method to improve the forecasting ability of the grey forecasting model. Finally, we analyze the current situation and future development trend of carbon emissions, and put forward reasonable suggestions.

Automated summary

This paper introduces a new carbon emission prediction model by incorporating new information priority operator and nonlinear parameter. The new model is applied to predict carbon emissions in different regions and trends, and demonstrates higher accuracy and forecasting ability.