论文标题
使用贝叶斯统计决策理论测量低活动性铀污染
Measurement of Low-Activity Uranium Contamination using Bayesian Statistical Decision Theory
论文作者
论文摘要
在辐射检测领域的各种技术挑战中，需要在自然辐射背景下存在较大波动的情况下进行准确的低级放射性测量，同时降低错误警报率。已经提出了一些使用统计推断的研究来克服这一挑战。这项工作提出了一种在核退役领域决策的先进统计方法。结果表明，所提出的方法允许调整背景信号平稳性的置信度。它还确保了真实检测率（TDR），错误警报率（FAR）和响应时间之间的可接受权衡，并且与用户要求一致。
Amongst the various technical challenges in the field of radiation detection is the need to carry out accurate low-level radioactivity measurements in the presence of large fluctuations in the natural radiation background, while lowering the false alarm rates. Several studies, using statistical inference, have been proposed to overcome this challenge. This work presents an advanced statistical approach for decision-making in the field of nuclear decommissioning. The results indicate that the proposed method allows to adjust the confidence degree in the stationarity of the background signal. It also ensures an acceptable tradeoff between the True Detection Rate (TDR), the False Alarm Rate (FAR) and the response time, and is consistent with the users requirements.
