Predictive modelling: Flight delays and associated factors, Hartsfield-Jackson Atlanta international airport

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Citations (Scopus)
75 Downloads (Pure)

Abstract

Nowadays, a downside to traveling is the delays that are constantly being advertised to passengers resulting in a decrease in customer satisfaction and causing costs. Consequently, there is a need to anticipate and mitigate the existence of delays helping airlines and airports improving their performance or even take consumer-oriented measures that can undo or attenuate the effect that these delays have on their passengers. This study has as main objective to predict the occurrence of delays in arrivals at the international airport of Hartsfield-Jackson. A Knowledge Discovery Database (KDD) methodology was followed, and several Data Mining techniques were applied. Historical data of the flight and weather, information of the airplane and propagation of the delay were gathered to train the model. To overcome the problem of unbalanced datasets, we applied different sampling techniques. To predict delays in individual flights we used Decision Trees, Random Forest and Multilayer Perceptron. Finally, each model's performance was evaluated and compared. The best model proved to be the Multilayer Perceptron with 85% of accuracy.

Original languageEnglish
Title of host publicationCENTERIS 2018 - International Conference on ENTERprise Information Systems / ProjMAN 2018 - International Conference on Project MANagement / HCist 2018 - International Conference on Health and Social Care Information Systems and Technologies, CENTERIS/ProjMAN/HCist 2018
EditorsJoão Eduardo Quintela Varajão, Maria Manuela Cruz-Cunha, Ricardo Martinho, Rui Rijo, Dulce Domingos, Emanuel Peres
Pages638-645
Number of pages8
Volume138
DOIs
Publication statusPublished - 1 Jan 2018
EventInternational Conference on ENTERprise Information Systems / International Conference on Project MANagement / International Conference on Health and Social Care Information Systems and Technologies, CENTERIS/ProjMAN/HCist 2018 - Lisbon, Portugal
Duration: 21 Nov 201823 Nov 2018

Publication series

NameProcedia Computer Science
PublisherElsevier
Volume138
ISSN (Print)1877-0509

Conference

ConferenceInternational Conference on ENTERprise Information Systems / International Conference on Project MANagement / International Conference on Health and Social Care Information Systems and Technologies, CENTERIS/ProjMAN/HCist 2018
CountryPortugal
CityLisbon
Period21/11/1823/11/18

Keywords

  • Atlanta International Airport
  • Data Mining
  • Flight Delays
  • Hartsfield-Jackson International Airport
  • Predictive Analysis

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