SRI Home | About |  Instructions for Authors |  Editors |  Archive | Authors Information Charge FAQ | Submit |  Peer Review
Publication Ethics

Reviewers’ Guidelines

Memberships and Standards

Manuscript Handling fees

Conferences

More on membership

News

Journal categories

Join Our Editorial Team

Citing Reference

Google Scholar h5-index


SNIP indicator

 

  Sci. Res. Impact.  

  5(5): 260-284, September 2019

 

 View: PDF (307KB) 

 

 Search Authors Articles in:

 

 

 

 

 

Scientific Research and Impact, Vol. 5(6), pp  260-284 September 2019

doi:1014412/SRI2019.284

(ISSN 2315-5396) 2019 Science Park Journals

Full Length Research Paper

 

EVALUATING FORECASTING ACCURACY OF NIGERIAN AIR TRAVEL DEMAND.

Adeniran Adetayo Olaniyi

 

Department of Transport Management Technology, Federal University of Technology Akure

 

 Abstract

This paper discussed few of forecasting models and their application for travel forecasting of international air passenger demand in Murtala Muhammed International Airport. Secondary data of international air passenger demand from the period of 1995 to 2017 was used for analysis. The forecasting method analyzed included: single moving average (n = 2, n = 3, n =4, n =5, n = 6, n = 7, n = 8, n = 9, n = 10) and simple exponential smoothing method (α =0.1, α =0.2, α =0.3, α =0.4, α=0.5, α=0.6, α=0.7, α=0.8, α=0.9). The accuracy of the forecasting method was measured using Mean Absolute Deviation (MAD), Mean Square Error (MSE), and Root Mean Square Error (RMSE). The accuracy of the forecasting method was measured using Mean Absolute Deviation (MAD), Mean Square Error (MSE), and Root Mean Square Error (RMSE). The result showed that the simple exponential smoothing with a smoothing constant of 0.9 obtained the best accuracy; however, it was selected as the most appropriate forecasting method. The 2018 forecast of international air passenger travel demand in Murtala Muhammed International Airport will be 2,844,230. It was revealed that the higher the value of smoothing constant nearer to 1, the more sensitive the forecast become the current conditions; the lower the value of n for the single moving average, the more realistic or reliable the forecast; simple exponential smoothing is more reliable than single moving average.

           

Keywords: forecasting, accuracy, quantitative techniques, air transport.

 

 

                                                                                                       

 

 

            

This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Science Park Journals

Copyright Science Park Journals 2012 - 2019                  Terms and Condition  |  Privacy Policy  |  FAQ  |  Customer Services