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Forecasting the Air Passenger Volume in Singapore: An Evaluation of TimeSeries Models

Author

Listed:
  • GUO RUI

    (School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore)

  • ZHONG ZHAOWEI

    (School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore)

Abstract

Nowadays due to the increasing development of the air transport technology, air passenger movements have been growing dynamically. Therefore it is necessary to have a good forecasting model suitable for Singapores situation. This paper explores various methods to predict the air passenger movements, and analyzes and compares the relative results obtained using corresponding models. 8 time-series models were simulated for 18 years prediction from 1998 to 2015 in the study, and were compared based on their forecasting error measurements. Finally, appropriate models for Singapores situation are recommended. Afterwards, forecasting for the next 18 years is conducted to have an idea about the future development.

Suggested Citation

  • Guo Rui & Zhong Zhaowei, 2017. "Forecasting the Air Passenger Volume in Singapore: An Evaluation of TimeSeries Models," International Journal of Technology and Engineering Studies, PROF.IR.DR.Mohid Jailani Mohd Nor, vol. 3(3), pages 117-123.
  • Handle: RePEc:apa:ijtess:2017:p:117-123
    DOI: 10.20469/ijtes.3.40004-3
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    References listed on IDEAS

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    1. Scarpel, Rodrigo Arnaldo, 2013. "Forecasting air passengers at São Paulo International Airport using a mixture of local experts model," Journal of Air Transport Management, Elsevier, vol. 26(C), pages 35-39.
    2. Profillidis, V.Α., 2012. "An ex-post assessment of a passenger demand forecast of an airport," Journal of Air Transport Management, Elsevier, vol. 25(C), pages 47-49.
    3. Profillidis, V.A, 2000. "Econometric and fuzzy models for the forecast of demand in the airport of Rhodes," Journal of Air Transport Management, Elsevier, vol. 6(2), pages 95-100.
    4. Torabi, Mahmoud & Rao, J.N.K., 2013. "Estimation of mean squared error of model-based estimators of small area means under a nested error linear regression model," Journal of Multivariate Analysis, Elsevier, vol. 117(C), pages 76-87.
    5. Grubb, Howard & Mason, Alexina, 2001. "Long lead-time forecasting of UK air passengers by Holt-Winters methods with damped trend," International Journal of Forecasting, Elsevier, vol. 17(1), pages 71-82.
    6. Profillidis, V. & Botzoris, G., 2015. "Air passenger transport and economic activity," Journal of Air Transport Management, Elsevier, vol. 49(C), pages 23-27.
    7. J. D. Bermudez & J. V. Segura & E. Vercher, 2007. "Holt-Winters Forecasting: An Alternative Formulation Applied to UK Air Passenger Data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 34(9), pages 1075-1090.
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    Cited by:

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    2. Mahmoud Mohamed Attalla & Mohamed Abdelfadiel Mohamed & Sabry Mohamed Iraqi, 2017. "The effects of inlet airflow angle on the quality of mixing air distribution in an aircraft cabin mock-up," Journal of Advances in Technology and Engineering Research, A/Professor Akbar A. Khatibi, vol. 3(4), pages 133-143.

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