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Application and improvement of continuous monitoring methods for artificial radionuclides based on Bayesian statistics

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成果类型:
期刊论文
作者:
Li, Xiang;Huang, Qianhong;Xie, Yuxi;Gong, Xueyu
通讯作者:
Gong, XY
作者机构:
[Gong, Xueyu; Huang, Qianhong; Li, Xiang] Univ South China, Sch Nucl Sci & Technol, Changsheng West Rd 28, Hengyang 421001, Peoples R China.
[Li, Xiang] HengYang Normal Univ, Sch Comp Sci & Technol, HengHua Rd 16, Hengyang 421001, Peoples R China.
[Xie, Yuxi] HengYang Normal Univ, Sch Phys & Elect Engn, HengHua Rd 16, Hengyang 421001, Peoples R China.
通讯机构:
[Gong, XY ] U
Univ South China, Sch Nucl Sci & Technol, Changsheng West Rd 28, Hengyang 421001, Peoples R China.
语种:
英文
关键词:
Bayesian statistics;Artificial radionuclides monitoring;Beta distribution;Poisson distribution;Gaussian distribution
期刊:
Journal of Radioanalytical and Nuclear Chemistry
ISSN:
0236-5731
年:
2024
基金类别:
Department of Science and Technology of Hunan Province [2024JJ6096]
机构署名:
本校为第一且通讯机构
院系归属:
核科学技术学院
摘要:
This paper delves into the Bayesian statistics applications of three preeminent models, Poisson distribution, Gaussian distribution, and Binomial distribution, in the continuous surveillance of artificial radionuclides. It introduces a slide-window method to accelerate the updating of the prior distribution of model parameters and compares the performances of three models before and after utilizing this method. Comparisons among the three models are made before and after using the slide-window. Experimental results demonst...

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