Artificial neural network and genetic algorithm hybrid technique for nucleusnucleus collisions

E. El-Dahshan*, A. Radi, M. Y. El-Bakry

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)


Selecting the optimal topology of a neural network for a particular application is a difficult task. Genetic Algorithm (GA) has been used to find the optimal neural network (NN) solution (i.e., hybrid technique) to calculate the pseudo-rapidity distribution of the shower particles for C12, O16, Si28, and S32 on nuclear emulsion. An efficient NN has been designed by GA to predict the distributions that are not present in the training set and matched them effectively. The proposed method shows a better fitting with experimental data. The hybrid technique GAANN simulation results prove a strong presence modeling in heavy ion collisions.

Original languageEnglish
Pages (from-to)1787-1795
Number of pages9
JournalInternational Journal of Modern Physics C
Issue number12
Publication statusPublished - Dec 2008
Externally publishedYes


  • Genetic algorithm
  • Heavy ion collisions
  • Neural network

ASJC Scopus subject areas

  • Statistical and Nonlinear Physics
  • Mathematical Physics
  • General Physics and Astronomy
  • Computer Science Applications
  • Computational Theory and Mathematics


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