Integrated forecasting model with adaptive parameters optimization using a harmony search algorithm for carbon dioxide emissions

With the significant increase of greenhouse gases and environmental deterioration, it is essential to understand trends of CO2 emissions form fossil fuel so as to establish effective energy policies and environmental strategy decision. In this study, a novel integrated forecasting model with adaptive parameters optimization by using Harmony Search (HS) algorithm for carbon dioxide emissions is established. In this proposed model, the integrated weights and nonlinear exponential parameters for single models are determined by HS. This novel integrated model is applied to CO2 emissions from 2000 to 2010 for China and United States in order to test the applicabilit y and forecasting accuracy. Through the comparison with other integrated methods (EW, VACO, R, DMFSE), our model showed better forecasting performance with the smaller MAPE.