ARTIFICIAL NEURAL NETWORK AND GENETIC ALGORITHM HYBRID TECHNIQUE FOR NUCLEUS–NUCLEUS COLLISIONS

DOI10.1142/S0129183108013382zbMath1178.82055MaRDI QIDQ3631044

El-Sayed A. El-Dahshan, Mahmoud Y. Elbakry, Amr Radi

Publication date: 5 June 2009

Published in: International Journal of Modern Physics C (Search for Journal in Brave)

zbMATH Keywords

neural networkgenetic algorithmheavy ion collisions

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Interacting particle systems in time-dependent statistical mechanics (82C22) Neural networks for/in biological studies, artificial life and related topics (92B20) Neural nets applied to problems in time-dependent statistical mechanics (82C32)

Related Items (3)

Radial basis function neural network model for mean velocity and vorticity of capillary flow ⋮ Modeling of Transverse Momentum Spectra for Charged Particles in Proton–Proton Collisions Based on Soft Computing Approaches ⋮ GENETIC PROGRAMING MODELING FOR NUCLEUS–NUCLEUS COLLISIONS

Cites Work

• Unnamed Item
• Feed forward neural networks modeling for K--P interactions
• GENETIC PROGRAMMING FOR HADRONIC INTERACTIONS AT HIGH ENERGIES

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