Application of a New Information Priority Accumulated Grey Model with Simpson to Forecast Carbon Dioxide Emission

Abstract

Climate warming is a hot topic of common concern all over the world and it has had a significant impact on climate, oceans and human life. The increase in the concentration of carbon dioxide in the atmosphere has become a significant factor in climate warming. In recent years, the concentration of carbon dioxide in the atmosphere has been mostly anthropogenic emissions. Accurate forecasting of carbon dioxide emissions will effectively propose solutions to the problem of global warming and then improve the environment in which we live. In our work, first of all, we use the new information priority accumulation method to optimize the weight of the new information in the prediction. Then we use the numerical integration method to optimize the background value of the grey model to achieve more accurate forecast. Application case results show that our proposed model is superior to other grey models in predicting carbon dioxide emission in India and Bangladesh.

Proactive visual prediction auditing the green eco-safety through backcasting approach booster by grey recruitment priority conceptual framework

“…The country's natural gas is increasing reserves and giving the government. The priority is to generate electricity using fossil fuels to face the problem of power outages between 2011 and 2018 and as discussed by Xiang et al [14] . Eventually, Egypt went from being short on electricity to have a surplus, but this new reality created a market that relied heavily on oil and gas.…”