Open Science Research Excellence
%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 International Science Index 55, 2011
%T Global Electricity Consumption Estimation Using Particle Swarm Optimization (PSO)
%U http://waset.org/publications/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