Forecasting greenhouse gas emissions with the new information priority generalized accumulative grey model

Abstract

Air pollution and other environmental problems caused by excessive emissions of greenhouse gases have become a comprehensive problem requiring joint global treatment. To consider the characteristics of different regions and different countries in terms of greenhouse gas emissions for accurate prediction, a new information priority generalized accumulative grey model (NIPGAGM(1,1,k)) is proposed. The new model maintains the structure of the traditional grey model and the basic result characteristics of its features. This research further deduces the calculation formulas of the model's time response sequence and parameter estimation. Furthermore, an optimization model is established to search the parameters using a detailed optimization algorithm. The optimization value of the new model is determined by the intelligent optimization algorithm. Then, the new model is applied to the greenhouse gas emission prediction of the Shanghai Cooperation Organization (SCO) member states. The numerical results are compared with those of existing models. Finally, according to the forecast results of greenhouse gas emissions in these regions, reasonable suggestions for clean energy production are proposed.