FORECASTING INTERNATIONAL AIRLINE PASSENGER TRAFFIC USING NEURAL NETWORKS

This paper examines the potential of using neural networks (NNs) in lieu of traditional statistical techniques in forecasting international airline passenger traffic. Neural networks appear to enhance forecasting accuracy and go beyond the capabilities of conventional statistical analysis. Therefore, airline decision makers should benefit from using neural networks in forecasting airline passenger loads.

  • Corporate Authors:

    University of British Columbia, Vancouver

    Faculty of Commerce and Business Administration
    Vancouver, British Columbia  Canada  V6T 1Z2
  • Authors:
    • Nam, K
    • Schaefer, T
  • Publication Date: 1995-9

Language

  • English

Media Info

Subject/Index Terms

Filing Info

  • Accession Number: 00713888
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Nov 7 1995 12:00AM