Journal
RADIATION PHYSICS AND CHEMISTRY
Volume 199, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.radphyschem.2022.110264
Keywords
Landmine; Angular distribution of neutrons; MCNP6.1; Artificial neural networks; MATLAB
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The study focused on the feasibility of a landmine identification system (LIS) using the angular distribution of thermal neutrons, utilizing artificial neural networks and least-squares methods with input data prepared by the MCNP6.1 Monte Carlo code. Achieving promising results with a relative error of less than 15%, the study confirmed the system's sensitivity to landmine depth and soil moisture, suggesting its potential for landmine identification.
The feasibility study of the landmine identification system (LIS) based on the angular distribution of thermal neutrons for buried landmines was undertaken in this work. The operation of the system was based on both artificial neural networks (ANN) and least-squares methods in which the input data were prepared by the MCNP6.1 Monte Carlo code before feeding into MATLAB and dedicated programs, respectively. Having achieved the promising ANN and least-squares results (with a relative error of less than 15%), the study confirmed that the proposed system is sensitive to the depth of the landmine as well as to the soil moisture, therefore it could be used for landmine identification.
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