• DocumentCode
    2126715
  • Title

    A New Method to Alarm Large Scale of Flights Delay Based on Machine Learning

  • Author

    Zonglei, Lu ; Jiandong, Wang ; Guansheng, Zheng

  • Author_Institution
    Coll. of Inf. Sci. & Technol., Nanjing Univ. of Aeronaut. & Astronaut., Nanjing
  • fYear
    2008
  • fDate
    21-22 Dec. 2008
  • Firstpage
    589
  • Lastpage
    592
  • Abstract
    A new method to alarm large scale of flight delays based on machine learning is presented in this paper. This new method first does unsupervised learning on the data of the flights collected from the airport. The standard of each class of delay can be gotten after the learning process. With these classes of delay, the supervised learning method can be used on the data so that the alarm model could be built. Comparing with the recent manual alarm standard, this model synthesizes more factors to do alarm. Since the recent delay standard is only related to the number of flights, which is helpful only in serious delay case, the new model performs will be more practical value than recent ones.
  • Keywords
    aerospace computing; unsupervised learning; flight delays; flights data; machine learning; supervised learning method; unsupervised learning; Airports; Delay effects; Educational institutions; Information science; Knowledge acquisition; Large-scale systems; Learning systems; Machine learning; Space technology; Unsupervised learning; Classification; Clustering; Flights Delay; Machine Learning; Unsupervised Learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Knowledge Acquisition and Modeling, 2008. KAM '08. International Symposium on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-0-7695-3488-6
  • Type

    conf

  • DOI
    10.1109/KAM.2008.18
  • Filename
    4732894