Forecasting airport surface traffic congestion based on decision tree

Zhaoyue Zhang, An Zhang, Cong Sun, Shanmei Li

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

To improve the operational efficiency of airport surfaces, this paper studies the air traffic congestion prediction of airport surfaces, demonstrates the limitations of traffic congestion prediction, and proposes a prediction method for airport surface traffic congestion based on decision tree. Firstly, the definition and measurement methods of traffic congestion in airport surfaces are promoted. Then, the key factors affecting traffic congestion are extracted, and a prediction model of traffic congestion is established. Finally, we verify the validity of the model based on actual operation data from Atlanta. The results show that the accuracy of the prediction is 70%.

Original languageEnglish
Pages (from-to)738-746
Number of pages9
JournalInternational Journal of Performability Engineering
Volume16
Issue number5
DOIs
StatePublished - May 2020

Keywords

  • Air transportation
  • C4.5 algorithm
  • Decision tree
  • Traffic congestion

Fingerprint

Dive into the research topics of 'Forecasting airport surface traffic congestion based on decision tree'. Together they form a unique fingerprint.

Cite this