• DocumentCode
    2900125
  • Title

    Data mining for understanding and improving decision-making affecting ground delay programs

  • Author

    Kulkarni, Devdatta ; Yao Wang ; Sridhar, B.

  • Author_Institution
    NASA Ames Res. Center, Moffett Field, CA, USA
  • fYear
    2013
  • fDate
    5-10 Oct. 2013
  • Abstract
    Difficulty of deciding on control action depends on the weather and traffic conditions. Weather signature on different days can categorize days into days with little decision difficulty, days with moderate decision difficulty and days with high decision difficulty. This paper examines performance of different data mining methods in the three regions of decision difficulty. Not surprisingly, data mining methods have the best performance in the region of little decision difficulty and have the poorest performance in the region of most decision difficulty. In applications where data mining methods have differing performance in differing regions, it would be more useful to characterize the region specific performance instead of characterizing performance by a single parameter.
  • Keywords
    data mining; decision making; control action; data mining methods; decision difficulty; decision-making improvement; ground delay programs; traffic conditions; weather conditions; Airports; Data mining; Delays; Economic indicators; Support vector machines; Wind;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Digital Avionics Systems Conference (DASC), 2013 IEEE/AIAA 32nd
  • Conference_Location
    East Syracuse, NY
  • ISSN
    2155-7195
  • Print_ISBN
    978-1-4799-1536-1
  • Type

    conf

  • DOI
    10.1109/DASC.2013.6712598
  • Filename
    6712598