Title :
Gene Expression Programming Approach to Event Selection in High Energy Physics
Author :
Teodorescu, Liliana
Author_Institution :
Brunel Univ., Uxbridge
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. It allowed automatic identification of selection rules that can be interpreted as cuts applied on the input variables. The signal/background classification accuracy was over 90% in all cases
Keywords :
data analysis; genetic algorithms; high energy physics instrumentation computing; automatic identification; event selection; evolutionary algorithm; gene expression programming approach; genetic algorithms; high energy physics data analysis; input variables; selection rules; signal-background classification accuracy; Biological cells; Data analysis; Encoding; Evolutionary computation; Gene expression; Genetic algorithms; Genetic programming; Input variables; Neural networks; Tail; Event selection; evolutionary algorithms; gene expression programming;
Journal_Title :
Nuclear Science, IEEE Transactions on
DOI :
10.1109/TNS.2006.878571
