11:15 AM - 11:30 AM
[2I06] Estimation of radiation source distribution from γ ray spectral data using machine learning
Keywords:Machine learning, Estimation of radiation source distribution
In order to estimate the radiation source distribution, the accuracy of the estimation has been verified by machine learning using γ-ray energy spectra obtained from simulation calculations. This verification has made it possible to estimate the radiation source distribution in a two-dimensional plane to some extent, even if there are obstructions between the source distribution and the measurement points.
However, machine learning using spectral data obtained from actual measurements has not yet been performed. Therefore, we have created a prototype of a device that uses multiple NaI spectrometers to stably measure radiation distributed on a flat surface. In this study, machine learning was performed using data obtained from measurements with this device to confirm the estimation accuracy.
However, machine learning using spectral data obtained from actual measurements has not yet been performed. Therefore, we have created a prototype of a device that uses multiple NaI spectrometers to stably measure radiation distributed on a flat surface. In this study, machine learning was performed using data obtained from measurements with this device to confirm the estimation accuracy.