Prediction of Ambient Dose Rate Based on Linearization and Cross-validation Method

Abstract

環境中のγ線線量値を長期にわたり予測するため，放射性核種の物性と担体の拡散を考慮した空間線量値の時間変化を直線化する方法を提示した．現象の変化が直線化できると予測は線形補外となる．交差検証法で過去のデータの一部を用いて予測を行い実測との対応から予測精度を見積る．将来の予測計算も，過去の処理と同一である．方法自体の精度のオーダは同じである．本処理の可能性を示す指標も示した．

福島県伊達市下小国集会所のモニタリング・ポストのデータでテストすると，線量予測式と実測値の決定係数は0.9以上，1年先の予測値では0.7であった．観測点の気象的擾乱，周辺環境の変化は決定係数の低下として現れる．

我々は，福島原子力発電所事故により他の市町村に避難し，帰宅時期を考慮している人を想定した．

Figures

Figure 1.

 Vector representation of β(t) function.

Vertical axis is the value of β(t) function in unit [1/d].

Horizontal axis is the elapsed day from March 15, 2011. Dots correspond to β(t) function per 15 [d], and straight line is the regression one.

Figure 2.

 Prediction and observation curves from 2012 to 2019.

The vertical axis is the ambient dose rate [μSv/h] and the horizontal is elapsed days from March 15, 2011. The blue zigzag are observation dose rates, and the red is fitting (until 2016) and prediction (after 2017).

Figure 3.

 Fitting and observations of low R² period in Table 1.

Blue dots are observations. Red curve is calculated by Eq. (11).

Table

Table 1. Prediction and the precision based on determination coefficients

	Observation Period	Effective**/total days	Fitting R2	Prediction R2
1	B*~2012.12.10	255/255	0.872	0.759
2	B~2013.12.10	583/620	0.956	0.784
3	B~2014.12.10	875/985	0.982	0.413
4	B~2015.12.10	1217/1350	0.986	0.636
5	B~2016.12.9	1559/1715	0.909	Figure 1

*) B is the start day that is 2012.3.31.

**) Effective days is that no-measurement and snow days are subtracted from total days.

R² is calculated for the effective days in Linear{dose (t)} set.

Prediction R² is calculated among predicted dose rates and observations. The observation period is from 2012.3.30 to 2016.12.9.

文献

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