Distinguishing Primary Cosmic-Ray Composition with Artificial Neural Networks

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Liang Hualou, Xie Wei, Ren Jingru, Wang Taijie and Dai Guiliang. Distinguishing Primary Cosmic-Ray Composition with Artificial Neural Networks[J]. Chinese Physics C, 1997, 21(3): 205-210.
Liang Hualou, Xie Wei, Ren Jingru, Wang Taijie and Dai Guiliang. Distinguishing Primary Cosmic-Ray Composition with Artificial Neural Networks[J]. Chinese Physics C, 1997, 21(3): 205-210. shu
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Received: 1900-01-01
Revised: 1900-01-01
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Distinguishing Primary Cosmic-Ray Composition with Artificial Neural Networks

    Corresponding author: Liang Hualou,
  • Institute of High Energy Physics,The Chinese Academy of Science,Beijing 100039

Abstract: We used artificial neural networks(ANN) to distinguish superhigh energy cosmic-ray proton(p) and nucleus(N) with Monte Carlo family data in mountain emulsion chamber experiment.The result shows that when visible energy of a family is larger than 500TeV,about 80% of p and N can be correctly selected,and more than 70% can be selected in the region between 100 and 500TeV.

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