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Estimating transportation energy demand in Turkey using the artificial bee colony algorithm

Mustafa Sonmez, Ali Payıdar Akgüngör and Salih Bektaş

Energy, 2017, vol. 122, issue C, 301-310

Abstract: In this study, three different mathematical models were proposed to estimate transportation energy demand of Turkey using the artificial bee colony algorithm. In the development of the models, gross domestic product, population and total annual vehicle-km were taken as parameters. For transportation energy demand estimations, linear, exponential and quadratic forms of mathematical expressions were used. A 44-year-old historical data from 1970 to 2013 were utilized for the training and testing stages of the models. The performances of the models were then evaluated by six different global error measurement approaches. The models that were developed were used in two possible scenarios to forecast transportation energy demand of Turkey for a 21-year period from 2014 to 2034. Artificial bee colony algorithm revealed the suitability of the optimization method for transportation energy planning and policy developments in Turkey. Furthermore, the results obtained from scenarios indicated that the energy demand of Turkey will be double that of 2013 by 2034.

Keywords: Transportation energy demand; Artificial bee colony algorithm; Transportation energy demand modeling; Turkey (search for similar items in EconPapers)
Date: 2017
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Handle: RePEc:eee:energy:v:122:y:2017:i:c:p:301-310