• Title of article

    High Energy Physics event selection with Gene Expression Programming Original Research Article

  • Author/Authors

    Liliana Teodorescu، نويسنده , , Daniel Sherwood، نويسنده ,

  • Issue Information
    دوهفته نامه با شماره پیاپی سال 2008
  • Pages
    11
  • From page
    409
  • To page
    419
  • Abstract
    Gene Expression Programming is a new evolutionary algorithm that overcomes many limitations of the more established Genetic Algorithms and Genetic Programming. Its application to event selection in high energy physics data analysis is presented using as an example application the selection of image particles produced in image interactions at 10 GeV and reconstructed in the decay mode image. The algorithm was used for automatic identification of classification criteria for signal/background separation. For the problem studied and for data samples with signal to background ratios between 0.25 and 5, the classification accuracy obtained with the criteria developed by the GEP algorithm was in the range of 92–95%.
  • Keywords
    Evolutionary algorithms , Gene Expression Programming , classification , High energy physics , Event selection
  • Journal title
    Computer Physics Communications
  • Serial Year
    2008
  • Journal title
    Computer Physics Communications
  • Record number

    1137399