ملخص
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.
اللغة الأصلية | English |
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الصفحات (من إلى) | 1787-1795 |
عدد الصفحات | 9 |
دورية | International Journal of Modern Physics C |
مستوى الصوت | 19 |
رقم الإصدار | 12 |
المعرِّفات الرقمية للأشياء | |
حالة النشر | Published - ديسمبر 2008 |
منشور خارجيًا | نعم |
ASJC Scopus subject areas
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