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• W3200899501 endingPage "165810" @default.
• W3200899501 startingPage "165810" @default.
• W3200899501 abstract "A tagged neutron system was established for detecting explosives in a package. An associated α particle neutron generator ING-27 developed by the All-Russian Institute of Automatics (VNIIA) is used as the neutron source, four Lutetium Yttrium OxyorthoSilicate (LYSO) detectors are used for the γ detector, and a silicon detector is used as the α detector. In the package, milk powder, washing powder, ammonium nitrate simulant, and TNT simulant were set as samples. The α–γ coincidence spectra of samples under different placement situations were measured. Time windows of α–γ coincidence spectra were fine selected to obtain the γ information of the suspicious sample. BP neural network was used to analyze these γ spectra. Compared with the full γ spectrum information, the peak area ratio of C, N, O inelastic scattering is more suitable as the input eigenvector of the neural network. Through training, we find that the identification of the test data composed of 80 γ spectra is completely correct when the number of hidden layer nodes is 4." @default.
• W3200899501 created "2021-09-27" @default.
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• W3200899501 date "2021-11-01" @default.
• W3200899501 modified "2023-10-17" @default.
• W3200899501 title "BP neural network analysis for identification of explosive in package by tagged neutron method" @default.
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• W3200899501 doi "https://doi.org/10.1016/j.nima.2021.165810" @default.
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