Determination of energy projection and environmental effect using artificial models and it?s relationship economical indicataors

Recently, global warming and its effects have become one of the most important themes in the world. Under the Kyoto Protocol, the EU has agreed to an 8% reduction in its greenhouse gas emissions by 2008-2012. The greenhouse gas emissions (GHGs: total GHG, CO2, CO, SO2, NO2, E (emissions of non-methane volatile organic compounds)) covered by the Protocol are weighted by their global warming potentials (GWPs) and aggregated to give total emissions in CO2 equivalents. The main subject in this study is to obtain equations by artificial neural network (ANN) approach to predict the GHGs of Turkey using sectoral energy consumption. The equations obtained are used to determine the future level of the GHG and take measures to control the share of sectors in total emission.