%0 Journal Article %A E.Assareh and M.A. Behrang and R. Assareh and N. Hedayat %D 2011 %J International Journal of Industrial and Manufacturing Engineering %B World Academy of Science, Engineering and Technology %I Open Science Index 55, 2011 %T Global Electricity Consumption Estimation Using Particle Swarm Optimization (PSO) %U https://publications.waset.org/pdf/1598 %V 55 %X An integrated Artificial Neural Network- Particle Swarm Optimization (PSO) is presented for analyzing global electricity consumption. To aim this purpose, following steps are done: STEP 1: in the first step, PSO is applied in order to determine world-s oil, natural gas, coal and primary energy demand equations based on socio-economic indicators. World-s population, Gross domestic product (GDP), oil trade movement and natural gas trade movement are used as socio-economic indicators in this study. For each socio-economic indicator, a feed-forward back propagation artificial neural network is trained and projected for future time domain. STEP 2: in the second step, global electricity consumption is projected based on the oil, natural gas, coal and primary energy consumption using PSO. global electricity consumption is forecasted up to year 2040. %P 1252 - 1256