Transportation energy consumption;
Neural network;
Log-linear model;
EMISSIONS;
POLICIES;
SECTOR;
D O I:
10.1016/j.enpol.2011.02.045
中图分类号:
F [经济];
学科分类号:
02 ;
摘要:
The objective of this study is to project transport energy consumption in Thailand for the next 20 years. The study develops log-linear regression models and feed-forward neural network models, using the as independent variables national gross domestic product, population and the numbers of registered vehicles. The models are based on 20-year historical data between years 1989 and 2008, and are used to project the trends in future transport energy consumption for years 2010-2030. The final log-linear models include only gross domestic product, since all independent variables are highly correlated. It was found that the projection results of this study were in the range of 54.84-59.05 million tonnes of oil equivalent, 2.5 times the 2008 consumption. The projected demand is only 61-65% of that predicted in a previous study, which used the LEAP model. This major discrepancy in transport energy demand projections suggests that projects related to this key indicator should take into account alternative projections, because these numbers greatly affect plans, policies and budget allocation for national energy management. (C) 2011 Elsevier Ltd. All rights reserved.
机构:
Department of Energy, Power Engineering and Environment, Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb, Lučićeva 5, Zagreb,10000, CroatiaDepartment of Sustainability and Planning, Aalborg University, Rendsburggade 14, Aalborg,9000, Denmark
机构:
Seoul Natl Univ, Dept Mech & Aerosp Engn, Gwanak Ro 1, Seoul 151744, South Korea
Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen 518055, Peoples R ChinaSeoul Natl Univ, Dept Mech & Aerosp Engn, Gwanak Ro 1, Seoul 151744, South Korea
Zhang, Yanhui
Cha, Sukwon
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机构:
Seoul Natl Univ, Dept Mech & Aerosp Engn, Gwanak Ro 1, Seoul 151744, South KoreaSeoul Natl Univ, Dept Mech & Aerosp Engn, Gwanak Ro 1, Seoul 151744, South Korea
Cha, Sukwon
Feng, Wei
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h-index: 0
机构:
Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen 518055, Peoples R ChinaSeoul Natl Univ, Dept Mech & Aerosp Engn, Gwanak Ro 1, Seoul 151744, South Korea
Feng, Wei
Xu, Guoqing
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机构:
Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen 518055, Peoples R China
Shanghai Univ, Sch Mechatron Engn & Automat, Shanghai 200444, Peoples R ChinaSeoul Natl Univ, Dept Mech & Aerosp Engn, Gwanak Ro 1, Seoul 151744, South Korea