Genetic algorithm approach to estimate transport energy demand in Turkey |
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| Affiliation: | 1. Department of Materials Science and Technology, Sharif University of Technology, Tehran, Iran;2. Metallic Materials Research Center (MMRC-MA), Tehran, Iran;3. Department of Materials Science and Engineering, Hamedan University of Technology, Hamedan, Iran;1. School of Forensic and Applied Sciences, University of Central Lancashire, Preston, PR1 2HE, UK;2. North-West University, Potchefstroom, 2520, South Africa;3. Dept Ecología y Biología Animal, Facultad de Biología, Universidad de Vigo, 36310, Vigo, Spain;4. CEH Lancaster, Library Avenue, Bailrigg, Lancaster, LA11 4AP, UK;1. College of Management Science and Engineering, Nanjing Audit University, Nanjing, 211815, China;2. College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, 211100, China;1. State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Chengdu, Sichuan 610500, PR China;2. Petroleum Systems Engineering, Faculty of Engineering and Applied Science, University of Regina, Regina, Saskatchewan S4S 0A2, Canada;3. Heavy Oil Company, Xinjiang Oil Field, CNPC, Karamay, Xinjiang 834000, PR China |
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| Abstract: | Transport energy modeling is a subject of current interest among transport engineers and scientists concerned with problems of sustainable transport. Transport energy planning is not possible without a reasonable knowledge of past and present energy consumption and likely future demands. In this study, three forms of the energy demand equations are developed in order to improve transport energy demand estimation efficiency for future projections based on genetic algorithm (GA) notion. The Genetic Algorithm Transport Energy Demand Estimation (GATEDE) model is developed using population, gross domestic product and vehicle-km. All equations proposed here are linear and non-linear, of which one is linear, second is exponential and third is quadratic. The quadratic form of the GATEDE model provided better-fit solution to the observed data and can be used with a high correlation coefficient for Turkey's future transport energy projections. It is expected that this study will be helpful in developing highly applicable and productive planning for transport energy policies. The GATEDE gives transport energy demand in comparison with the other transport energy demand projections. The GATEDE model plans the sectoral energy demand of Turkey until 2020. |
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