Predicting performance of ground delay programs

Alexander Estes, Michael O. Ball, David J. Lovell

Research output: Contribution to conferencePaper

3 Scopus citations

Abstract

Models are proposed to estimate the performance of Ground Delay Programs as air traffic management initiatives. We apply Random Forest and Gradient-Boosted Forest regression techniques within the context of Geographically Weighted Regression. We estimate both the mean and 90th percentile responses for two performance indicators: average arrival delay and the number of cancelled arrivals.

Original languageEnglish (US)
StatePublished - Jan 1 2017
Event12th USA/Europe Air Traffic Management Research and Development Seminar, ATM 2017 - Seattle, United States
Duration: Jun 26 2017Jun 30 2017

Other

Other12th USA/Europe Air Traffic Management Research and Development Seminar, ATM 2017
CountryUnited States
CitySeattle
Period6/26/176/30/17

Keywords

  • Air traffic management
  • Delay prediction
  • Ground delay program

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  • Cite this

    Estes, A., Ball, M. O., & Lovell, D. J. (2017). Predicting performance of ground delay programs. Paper presented at 12th USA/Europe Air Traffic Management Research and Development Seminar, ATM 2017, Seattle, United States.