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FORECASTING TRANSPORT ENERGY DEMAND IN IRAN USING META-HEURISTIC ALGORITHMS

عنوان مقاله: FORECASTING TRANSPORT ENERGY DEMAND IN IRAN USING META-HEURISTIC ALGORITHMS
شناسه ملی مقاله: JR_IJOCE-2-4_006
منتشر شده در در سال 1391
مشخصات نویسندگان مقاله:

A. Kaveh
N. Shamsapour
R. Sheikholeslami
M. Mashhadian

خلاصه مقاله:
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 ۱۹۶۸ to ۲۰۰۹ as the case of this study. The available data is partly used for finding the optimal, or near optimal values of the weighting parameters (۱۹۶۸-۲۰۰۳) and partly for testing the models (۲۰۰۴-۲۰۰۹). Finally transport energy demand in Iran is forecasted up to the year ۲۰۲۰.

کلمات کلیدی:
transport energy; forecasting; optimization; charged system search; harmony search

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/1831519/