دوره 2، شماره 4 - ( 7-1391 )
جلد 2 شماره 4 صفحات 544-533 |
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Kaveh A, Shamsapour N, Sheikholeslami R, Mashhadian M. FORECASTING TRANSPORT ENERGY DEMAND IN IRAN USING META-HEURISTIC ALGORITHMS. IJOCE 2012; 2 (4) :533-544
URL: http://ijoce.iust.ac.ir/article-1-111-fa.html
URL: http://ijoce.iust.ac.ir/article-1-111-fa.html
FORECASTING TRANSPORT ENERGY DEMAND IN IRAN USING META-HEURISTIC ALGORITHMS. عنوان نشریه. 1391; 2 (4) :533-544
چکیده: (21284 مشاهده)
This paper presents application of an improved Harmony Search (HS) technique and Charged System Search algorithm (CSS) to estimate transport energy demand in Iran, based on socio-economic indicators. The models are developed in two forms (exponential and linear) and applied to forecast transport energy demand in Iran. These models are developed to estimate the future energy demands based on population, gross domestic product (GDP), and the data of numbers of vehicles (VEH). Transport energy consumption in Iran is considered from 1968 to 2009 as the case of this study. The available data is partly used for finding the optimal, or near optimal values of the weighting parameters (1968-2003) and partly for testing the models (2004-2009). Finally transport energy demand in Iran is forecasted up to the year 2020.
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