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
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
Journal title :
Computer Physics Communications