Using Bees Algorithm and Artificial Neural Network to Forecast World Carbon Dioxide Emission

Abstract In this study, an integrated multi-layer perceptron neural network and Bees Algorithm is presented for analyzing world CO2 emissions. For this purpose, the following steps are done: STEP 1: In the first step, the Bees Algorithm is applied in order to determine the world's fossil fuels and primary energy demand equations based on socio-economic indicators. The world's population, gross domestic product, oil trade movement, and natural gas trade movement are used as socio-economic indicators in this study. The following scenarios are designed for forecasting each socio-economic indicator in a future time domain: Scenario I: For each socio-economic indicator, several polynomial trend lines are fitted to the observed data and the best fitted polynomial (highest correlation coefficient (R2) value) for each socio-economic indicator is used for future forecasting. Scenario II: For each socio-economic indicator, several neural networks are trained and the best trained network for each socio-economic indi...