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Advantages of Artificial Neural Network in Neutron Spectra Unfolding |
| ZHU Qing-Jun**, TIAN Li-Chao, YANG Xiao-Hu, GAN Long-Fei, ZHAO Na, MA Yan-Yun |
College of Science, National University of Defense Technology, Changsha 410073
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| Cite this article: |
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ZHU Qing-Jun, TIAN Li-Chao, YANG Xiao-Hu et al 2014 Chin. Phys. Lett. 31 072901 |
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Abstract Advantages of using the artificial neural network method in neutron spectra unfolding are investigated in comparison with the maximum entropy unfolding method. By introducing the information entropy theory, we find that for the spectrum with the information entropy over 3.5, the four-layer feed-forward neural network (11-35-55-60) and the maximum entropy method generally demonstrate the same unfolding performance, while the spectrum with the information entropy lower than 3.5, the artificial neural network unfolding model is recommend due to the fact that the artificial neural network method has a stronger negative correlation between the entropy of the spectra and the mean squares error of the spectra than the maximum entropy method.
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Published: 30 June 2014
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