New method for visualizing the dose rate distribution around the Fukushima Daiichi Nuclear Power Plant using artificial neural networks

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...

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Autores principales:	Miyuki Sasaki, Yukihisa Sanada, Estiner W. Katengeza, Akio Yamamoto
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/c30641db1c514e169da874cb86efc8e9
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spelling	oai:doaj.org-article:c30641db1c514e169da874cb86efc8e92021-12-02T10:49:34ZNew method for visualizing the dose rate distribution around the Fukushima Daiichi Nuclear Power Plant using artificial neural networks10.1038/s41598-021-81546-42045-2322https://doaj.org/article/c30641db1c514e169da874cb86efc8e92021-01-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-81546-4https://doaj.org/toc/2045-2322Abstract 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.Miyuki SasakiYukihisa SanadaEstiner W. KatengezaAkio YamamotoNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Miyuki Sasaki Yukihisa Sanada Estiner W. Katengeza Akio Yamamoto New method for visualizing the dose rate distribution around the Fukushima Daiichi Nuclear Power Plant using artificial neural networks
description	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.
format	article
author	Miyuki Sasaki Yukihisa Sanada Estiner W. Katengeza Akio Yamamoto
author_facet	Miyuki Sasaki Yukihisa Sanada Estiner W. Katengeza Akio Yamamoto
author_sort	Miyuki Sasaki
title	New method for visualizing the dose rate distribution around the Fukushima Daiichi Nuclear Power Plant using artificial neural networks
title_short	New method for visualizing the dose rate distribution around the Fukushima Daiichi Nuclear Power Plant using artificial neural networks
title_full	New method for visualizing the dose rate distribution around the Fukushima Daiichi Nuclear Power Plant using artificial neural networks
title_fullStr	New method for visualizing the dose rate distribution around the Fukushima Daiichi Nuclear Power Plant using artificial neural networks
title_full_unstemmed	New method for visualizing the dose rate distribution around the Fukushima Daiichi Nuclear Power Plant using artificial neural networks
title_sort	new method for visualizing the dose rate distribution around the fukushima daiichi nuclear power plant using artificial neural networks
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/c30641db1c514e169da874cb86efc8e9
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New method for visualizing the dose rate distribution around the Fukushima Daiichi Nuclear Power Plant using artificial neural networks

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