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Flight delay prediction: data analysis and model development

  • University of Bedfordshire
Research Output: Chapter in Book/Report/Conference proceeding Conference contribution Peer-review

Abstract

Flight delays in air transportation are a major concern that has adverse effects on the economy, the passengers, and the aviation industry. This matter critically requires an accurate estimation for future flight delays that can be implemented to improve airport operations and customer satisfaction. Having said that, a massive volume of data and an extreme number of parameters have restricted the way to build an accurate model. Many existing flight delay prediction methods are based on small samples and/or are complex to interpret with little or no opportunity for machine learning deployment. This paper develops a prediction model by analysing the data of domestic flights within the United States of America (USA). The proposed model gains insight into factors causing flight delays, cancellations and the relationship between departure and arrival delay using exploratory data analysis. In addition, Random Forest (RF) algorithm is used to train and test the big dataset to help the model development. A web application has also been developed to implement the model and the testing results are presented with the limitation discussed.

Publication Information

Output type

Research Output: Chapter in Book/Report/Conference proceeding Conference contribution Peer-review

Host publication Subtitle

System Intelligence through Automation and Computing, ICAC 2021

Original language

English

Publication milestones

  • Published - 15/11/2021

Publication status

Published - 15/11/2021

Publisher

Institute of Electrical and Electronics Engineers Inc., United States

Publication series

  • Publication series name: 2021 26th International Conference on Automation and Computing: System Intelligence through Automation and Computing, ICAC 2021

ISBN (Print)

9781665443524

ISBN (Electronic)

9781860435577

External Publication IDs

  • handle.net: 10547/626167
  • Scopus: 85123188798

Host publication title

2021 26th International Conference on Automation and Computing (ICAC)

Host publication editors

  • Chenguang Yang

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