Flight operations quality assurance (FOQA) can be applied to monitoring and analyzing the data recorded in a flight to improve line operations and safety. In view of the requirements of FOQA and the shortage of general data processing algorithms, clustering analysis and density-based spatial clustering of applications with noise (DBSCAN) algorithm are studied depending on data mining, and FOQA based on clustering analysis is presented. The process of flight data analysis is discussed with this algorithm. The practicability and universality of DBSCAN algorithm is validated by the clustering analysis instance of an abnormal data during takeoff.


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Flight Operations Quality Assurance Based on Clustering Analysis


    Contributors:
    Sun, Zhuo (author) / Ma, Cunbao (author) / Li, Wen (author) / Shen, Chunnan (author)


    Publication date :

    2014


    Size :

    10 Seiten





    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English





    Flight Operations Quality Assurance (FOQA-HOMP)

    Healing, R. / AHS International | British Library Conference Proceedings | 2009



    Mission Operations and Command Assurance: Flight Operations Quality Improvements

    Witkowski, Mona M. / Potts, Sherrill S. / Kazz, Sheri L. et al. | NTRS | 1993


    Mission Operations and Command Assurance: Flight Operations Quality Improvements

    United States; National Aeronautics and Space Administration / United States; Air Force | British Library Conference Proceedings | 1993