Abstract:
:This study proposes a new method of visualizing the ambient dose rate distribution using artificial neural networks (ANNs) from airborne radiation monitoring results. The method was applied to the results of the airborne radiation monitoring which was conducted around the Fukushima Daiichi Nuclear Power Plant by an unmanned aerial vehicle. Much of the survey data obtained in the past were used as the training data for building a network. The number of training cases was related to the error between the ground and converted values by the ANN. The quantitative evaluation index (the root-mean-square error) between the ANN-converted value and the ground-based survey result converged at 200 training cases. This number of training case was considered a rough criterion of the required number of training cases. The reliability of the ANN method was evaluated by comparison with the ground-based survey data. The dose rate map created by the ANNs method reproduced ground-based survey results better than traditional methods.
journal_name
Sci Repjournal_title
Scientific reportsauthors
Sasaki M,Sanada Y,Katengeza EW,Yamamoto Adoi
10.1038/s41598-021-81546-4subject
Has Abstractpub_date
2021-01-20 00:00:00pages
1857issue
1issn
2045-2322pii
10.1038/s41598-021-81546-4journal_volume
11pub_type
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