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Number of results

Journal

2011 | 9 | 3 | 874-883

Article title

Application of genetic programming for proton-proton interactions

Content

Title variants

Languages of publication

EN

Abstracts

EN
The aim of the present work is to use one of the machine learning techniques named the genetic programming (GP) to model the p-p interactions through discovering functions. In our study, GP is used to simulate and predict the multiplicity distribution of charged pions (P(n
ch)), the average multiplicity (〈n
ch〉) and the total cross section (σ
tot) at different values of high energies. We have obtained the multiplicity distribution as a function of the center of mass energy ($$
\sqrt s
$$) and charged particles (n
ch). Also, both the average multiplicity and the total cross section are obtained as a function of $$
\sqrt s
$$. Our discovered functions produced by GP technique show a good match to the experimental data. The performance of the GP models was also tested at non-trained data and was found to be in good agreement with the experimental data.

Publisher

Journal

Year

Volume

9

Issue

3

Pages

874-883

Physical description

Dates

published
1 - 6 - 2011
online
26 - 2 - 2011

Contributors

  • Department of Physics, Faculty of Sciences, Ain Shams University, Abbassia, Cairo, 11566, Egypt

References

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Document Type

Publication order reference

Identifiers

YADDA identifier

bwmeta1.element.-psjd-doi-10_2478_s11534-010-0088-7
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