• DocumentCode
    523916
  • Title

    Matrix Similarity Measurement Used in a GA-Based Feature Extraction

  • Author

    Zhefu, Yu ; Huibiao, Lu ; Chuanying, Jia

  • Author_Institution
    Dalian Maritime Univ., Dalian, China
  • Volume
    2
  • fYear
    2010
  • fDate
    11-12 May 2010
  • Firstpage
    633
  • Lastpage
    635
  • Abstract
    A GA-based feature extraction method was presented for solving non-linear regression questions. The order of regression function is determined by practical experience, so the application of this method is limited. In this paper, the angle measurement method of matrix similarity was used to determine the order of the polynomial space. By doing this, the GA-based feature extraction method became more practical. An explicit non-linear regress function can be very easy to find. The experiment shows that it achieved satisfactory results.
  • Keywords
    feature extraction; genetic algorithms; matrix algebra; nonlinear functions; regression analysis; support vector machines; GA based feature extraction method; genetic algorithm; matrix similarity measurement; nonlinear regression function; polynomial space; Automation; Extraterrestrial measurements; Feature extraction; Genetic algorithms; Goniometers; Kernel; Polynomials; Symmetric matrices; Angle Measurement; Feature Extraction; Genetic Algorithm; Matrix Similarity; Support Vector Regression;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on
  • Conference_Location
    Changsha
  • Print_ISBN
    978-1-4244-7279-6
  • Electronic_ISBN
    978-1-4244-7280-2
  • Type

    conf

  • DOI
    10.1109/ICICTA.2010.613
  • Filename
    5523388