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

被引：51
|
作者：
Sonmez, Mustafa [1 ]
Akgungor, Ali Payidar [2 ]
Bektas, Salih [1 ]
机构：
[1] Aksaray Univ, Fac Engn, Dept Civil Engn, TR-68100 Aksaray, Turkey
[2] Kirikkale Univ, Fac Engn, Dept Civil Engn, TR-71451 Kirikkale, Turkey
来源：
ENERGY | 2017年 / 122卷
关键词：
Transportation energy demand; Artificial bee colony algorithm; Transportation energy demand modeling; Turkey; OPTIMIZATION APPROACH; EXERGY PRODUCTION; NEURAL-NETWORKS; CONSUMPTION; PREDICTION; GENERATION; EMISSIONS; FORECAST; POLICIES; SECTOR;
D O I：
10.1016/j.energy.2017.01.074
中图分类号：
O414.1 [热力学];
学科分类号：
摘要：
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. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码：301 / 310
页数：10
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