A Genetic programming for modeling Hadronnucleus Interactions at 200 GeV/c

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@Misc{oai:CiteSeerX.psu:10.1.1.302.1666,

• title = "A Genetic programming for modeling Hadronnucleus Interactions at 200 {GeV/c}",
• author = "Mahmoud Y. El-bakry and El-sayed A. El-dahshan and A. Radi and M. Tantawy",
• year = "2013",
• month = jul # "~23",
• keywords = "genetic algorithms, genetic programming",
• annote = "The Pennsylvania State University CiteSeerX Archives",
• bibsource = "OAI-PMH server at citeseerx.ist.psu.edu",
• language = "en",
• oai = "oai:CiteSeerX.psu:10.1.1.302.1666",
• rights = "Metadata may be used without restrictions as long as the oai identifier remains attached to it.",
• URL = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.302.1666",
• URL = "http://www.ijser.org/researchpaper/Genetic-programming-for-modeling-Hadron.pdf",
• abstract = "Genetic programming (GP) is a soft computing search technique, which was used to develop a tree-structured program with the purpose of minimising the fitness value of it. It is also a powerful and flexible evolutionary technique with some special features that are suitable for building a tree representation which is always the best solution for the problem we encounter. In this paper, GP has been used to describe a function that calculates charged and negative pions multiplicity distribution for Hadron-nucleus interactions at 200 GeV/c and also compared with the parton two fireball model (PTFM). GP calculations are in accordance with the available experimental data in comparison with the conventional ones (PTFM). Finally, the calculation results showed that the GP model is superior to the traditional techniques that we have ever seen so far. Index Terms --- Genetic programming (GP), machine learning (ML), pion production, multiplicity distribution.",

}

Genetic Programming entries for Mahmoud Y El-Bakry EL-Sayed A El-Dahshan Amr Mohamed Mahmoud Khairat Radi M Tantawy

Citations