• DocumentCode
    2136249
  • Title

    Research on Event Analysis Approach for the Identification of Aircraft Large Vertical Load

  • Author

    Zhao Yu ; Chen Rui ; Huang Si-ming ; Xu Bao-guang

  • Author_Institution
    Inst. of Policy & Manage., Chinese Acad. of Sci., Beijing, China
  • fYear
    2010
  • fDate
    24-26 Aug. 2010
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Aircraft large vertical load means the aircraft is weighted above the normal, which may harm the air safety. So it is crucial to do the research on how to choose suitable models and methods to identify whether the aircraft got a large vertical load before landing and adjust immediately. The MWW nonparametric test is used to extract the distinct features. Then, compare the most commonly used models and choose the k-nearest neighbors and support vector machines with dynamic weight consideration to classify, both of them ensure the accuracy and make sense according to the feature of the dynamic data and comparison of some classify methods. The results indicate that the two methods make no difference on this problem but the model v-SVC in support vector machine seems more adaptable when the problem expands.
  • Keywords
    aerospace computing; air safety; aircraft; data mining; feature extraction; pattern classification; support vector machines; MWW nonparametric test; air safety; aircraft large vertical load identification; data mining; event analysis approach; feature extraction; k-nearest neighbors; support vector machines; v-SVC model; Accuracy; Aircraft; Atmospheric modeling; Kernel; Support vector machine classification; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Management and Service Science (MASS), 2010 International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-5325-2
  • Electronic_ISBN
    978-1-4244-5326-9
  • Type

    conf

  • DOI
    10.1109/ICMSS.2010.5575672
  • Filename
    5575672