Analysis of Hurricane Matthew 2016 Data to Estimate Airline Passengers Disruption

Harshitha Meda, Lauren B. Davis, Chrysafis Vogiatzis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Disruptions in airline operations are not uncommon and can interrupt smooth and efficient passenger transportation, especially during extreme weather conditions and hurricanes. Airline operations can be severely affected and/or halted for the duration of these phenomena. In order to develop tools to implement proper recovery actions for different stakeholders during a disruption present in an air transportation system, prior hurricane data analysis is crucial. This work focuses on analyzing a large set of airline data during Hurricane Matthew in 2016 to obtain meaningful insights regarding the affected airports and airlines. Our analysis also predicts the number of affected airline passengers during the hurricane. The results of our study show that Orlando International Airport (MCO) and Southwest Airlines were the most affected airport and airline, respectively. Our findings further reveal that certain airline passengers were affected before and after the day of the hurricane.

Original languageEnglish (US)
Title of host publicationProceedings - 2019 IEEE International Conference on Big Data, Big Data 2019
EditorsChaitanya Baru, Jun Huan, Latifur Khan, Xiaohua Tony Hu, Ronay Ak, Yuanyuan Tian, Roger Barga, Carlo Zaniolo, Kisung Lee, Yanfang Fanny Ye
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3909-3915
Number of pages7
ISBN (Electronic)9781728108582
DOIs
StatePublished - Dec 2019
Event2019 IEEE International Conference on Big Data, Big Data 2019 - Los Angeles, United States
Duration: Dec 9 2019Dec 12 2019

Publication series

NameProceedings - 2019 IEEE International Conference on Big Data, Big Data 2019

Conference

Conference2019 IEEE International Conference on Big Data, Big Data 2019
CountryUnited States
CityLos Angeles
Period12/9/1912/12/19

Keywords

  • air transportation
  • airlines
  • airports
  • disruption
  • Hurricane Matthew

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Information Systems
  • Information Systems and Management

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  • Cite this

    Meda, H., Davis, L. B., & Vogiatzis, C. (2019). Analysis of Hurricane Matthew 2016 Data to Estimate Airline Passengers Disruption. In C. Baru, J. Huan, L. Khan, X. T. Hu, R. Ak, Y. Tian, R. Barga, C. Zaniolo, K. Lee, & Y. F. Ye (Eds.), Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019 (pp. 3909-3915). [9006133] (Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigData47090.2019.9006133