FLIGHT DELAY PREDICTION BASED WITH MACHINE LEARNING


Hatipoglu I., TOSUN Ö., Tosun N.

LOGFORUM, vol.18, no.1, pp.96-107, 2022 (ESCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 18 Issue: 1
  • Publication Date: 2022
  • Doi Number: 10.17270/j.log.2022.655
  • Journal Name: LOGFORUM
  • Journal Indexes: Emerging Sources Citation Index (ESCI), Scopus
  • Page Numbers: pp.96-107
  • Keywords: GBDT, XGBoost, LightGBM, Catboost, delay prediction
  • Akdeniz University Affiliated: Yes

Abstract

Background: The delay of a planned flight causes many undesirable situations such as cost, customer satisfaction, environmental pollution. There is only one way to prevent these problems before they occur, and that is to know which flights will be delayed. The aim of this study is to predict delayed flights. For this, the use of machine learning techniques, which have become widespread with the development of computer capacities and data storage systems, is preferred.