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Utilizing Regression Algorithms for ATS Route Forecasts

Author

Listed:
  • Dewansh Raheja

    (Air Trafβic Management Research Institute, Nanyang Technological University, Singapor)

  • Y. X. LEE

    (Air Trafβic Management Research Institute, Nanyang Technological University, Singapor)

  • Z. W. Zhong

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

Abstract

Assuming the static nature of routes, our study aimed to employ traffic feedback results from European airspace design evaluation tool combined with econometric modelling to forecast air traffic on selected ATS routes in the ASEAN region. A case study involving evolution scenarios of the economy from 2004 to 2019 was used to show the importance of regression modelling and form an ATS route forecast procedure to illustrate current capabilities. The study findings show that the accumulation of flights over the airspace is likely to affect airway capacity and workload in the coming years. Thus, ATS route forecasts become necessary in order to meet such heavy traffic conditions and plan new ATS routes. The results of the study provide valuable insights on the ASEAN ATS route network and the future direction for efforts to prevent structure imbalances by increasing capacity or reducing demand.

Suggested Citation

  • Dewansh Raheja & Y. X. LEE & Z. W. Zhong, 2017. "Utilizing Regression Algorithms for ATS Route Forecasts," Journal of ICT, Design, Engineering and Technological Science, Juhriyansyah Dalle, vol. 1(1), pages 10-12.
    • Handle: RePEc:avb:jitdet:2017:p:10-12
    DOI: 10.33150/JITDETS-1.1.3
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    References listed on IDEAS

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