High Energy Physics event selection with Gene Expression Programming

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@Article{Teodorescu2008409,

• author = "Liliana Teodorescu and Daniel Sherwood",
• title = "High Energy Physics event selection with Gene Expression Programming",
• journal = "Computer Physics Communications",
• volume = "178",
• number = "6",
• pages = "409--419",
• year = "2008",
• ISSN = "0010-4655",
• DOI = "doi:10.1016/j.cpc.2007.10.003",
• URL = "http://www.sciencedirect.com/science/article/B6TJ5-4R29FNK-1/2/4e3abbd674450ca48d43711fdb1b4f95",
• keywords = "genetic algorithms, genetic programming, Gene Expression Programming, Evolutionary algorithms, Event selection, Classification, High Energy Physics",
• 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 KS particles produced in e+e- interactions at 10 GeV and reconstructed in the decay mode KS-->[pi]+[pi]-. 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%.",

}

Genetic Programming entries for Liliana Teodorescu Daniel Sherwood

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