• DocumentCode
    3598983
  • Title

    High energy physics data analysis with gene expression programming

  • Author

    Teodorescu, Liliana

  • Author_Institution
    Brunel Univ., London, UK
  • Volume
    1
  • fYear
    2005
  • Firstpage
    143
  • Lastpage
    147
  • Abstract
    Gene expression programming is a new evolutionary algorithm that overcomes many limitations of the more established genetic algorithms and genetic programming. Its first application to high energy physics data analysis is presented. The algorithm was successfully used for event selection on samples with both low and high background level. The signal/background classification accuracy was over 90% in all cases.
  • Keywords
    data analysis; high energy physics instrumentation computing; evolutionary algorithm; gene expression programming; genetic algorithms; genetic programming; high energy physics data analysis; Biological cells; Data analysis; Evolutionary computation; Gene expression; Genetic algorithms; Genetic programming; Neural networks; Support vector machine classification; Support vector machines; Tail;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Nuclear Science Symposium Conference Record, 2005 IEEE
  • ISSN
    1095-7863
  • Print_ISBN
    0-7803-9221-3
  • Type

    conf

  • DOI
    10.1109/NSSMIC.2005.1596225
  • Filename
    1596225
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3598983