Title :
High energy physics data analysis with gene expression programming
Author :
Teodorescu, Liliana
Author_Institution :
Brunel Univ., London, UK
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;
Conference_Titel :
Nuclear Science Symposium Conference Record, 2005 IEEE
Print_ISBN :
0-7803-9221-3
DOI :
10.1109/NSSMIC.2005.1596225
