 Projection of future transport energy demand of Jordan using adaptive neuro-fuzzy techniqueAhmed Al-Ghandoor, Murad Samhouri, Ismael Al-Hinti, Jamal Jaber and Mohammad Al-Rawashdeh Energy, 2012, vol. 38, issue 1, 128-135 Abstract: This paper illustrates a new approach to model and forecast the transport energy demand of Jordan based on Adaptive Neuro-Fuzzy Inference System (ANFIS) and the double exponential smoothing techniques. The ANFIS model has been developed using socio-economic and transport related indicators based on annual number of vehicles, vehicle ownership level, income level, and fuel prices in Jordan. The double exponential smoothing technique has been used to forecast the different transport indicators to feed the developed ANFIS model in order to forecast the transport energy demand for the next two decades. The model has been validated using testing data and has showed very accurate results of 97%. The results show that the transport energy demand is expected to increase at % 4.9 yr−1 from years 2010–2030. In addition, a number of policy gaps are identified as contributors to the low efficiency composition of the fleet in terms of engine size and vehicle age. It is expected that the results of this study will be helpful in developing highly applicable and productive planning for future transport energy policies. Keywords: Energy; Transportation; ANFIS; Jordan (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:38:y:2012:i:1:p:128-135 DOI: 10.1016/j.energy.2011.12.023 Access Statistics for this article Energy is currently edited by Henrik Lund and Mark J. Kaiser More articles in Energy from Elsevier |
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