The application of non-parametric statistical techniques to an alara programme

被引:0
|
作者
Moon, JH [1 ]
Cho, YH [1 ]
Kang, CS [1 ]
机构
[1] Seoul Natl Univ, Dept Nucl Engn, Kwanak Gu, Seoul 151742, South Korea
关键词
D O I
10.1093/oxfordjournals.rpd.a006533
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
For the cost-effective reduction of occupational radiation dose (ORD) at nuclear power plants, it is necessary to identify what are the processes of repetitive high ORD during maintenance and repair operations. To identify the processes, the point values such as mean and median are generally used, but they sometimes lead to misjudgment since they cannot show other important characteristics such as dose distributions and frequencies of radiation jobs. As an alternative, the non-parametric analysis method is proposed, which effectively identifies the processes of repetitive high ORD. As a case study, the method is applied to ORD data of maintenance and repair processes at Kori Units 3 and 4 that are pressurised water reactors with 950 MWe capacity and have been operating since 1986 and 1987 respectively, in Korea and the method is demonstrated to be an efficient way of analysing the data.
引用
收藏
页码:137 / 142
页数:6
相关论文
共 50 条
  • [41] Statistical parametric and non-parametric control charts for monitoring residential water consumption
    Bogo, Allyson Belli
    Henning, Elisa
    Kalbusch, Andreza
    SCIENTIFIC REPORTS, 2023, 13 (01)
  • [42] Selection of orthogonal chromatographic systems based on parametric and non-parametric statistical tests
    Forlay-Frick, P
    Van Gyseghem, E
    Héberger, K
    Vander Heyden, Y
    ANALYTICA CHIMICA ACTA, 2005, 539 (1-2) : 1 - 10
  • [43] Statistical parametric and non-parametric control charts for monitoring residential water consumption
    Allyson Belli Bogo
    Elisa Henning
    Andreza Kalbusch
    Scientific Reports, 13
  • [44] Comparison of Parametric and Non-Parametric Statistical Features for Z-Wave Fingerprinting
    Patel, Hiren J.
    Ramsey, Benjamin W.
    2015 IEEE MILITARY COMMUNICATIONS CONFERENCE (MILCOM 2015), 2015, : 378 - 382
  • [45] Non-parametric Bayesian mixture of sparse regressions with application towards feature selection for statistical downscaling
    Das, D.
    Dy, J.
    Ross, J.
    Obradovic, Z.
    Ganguly, A. R.
    NONLINEAR PROCESSES IN GEOPHYSICS, 2014, 21 (06) : 1145 - 1157
  • [46] Detection of spatiotemporal patterns of rainfall trends, using non-parametric statistical techniques, in Karnataka state, India
    Harishnaika N
    Shilpa N
    S A Ahmed
    Environmental Monitoring and Assessment, 2023, 195
  • [47] Detection of spatiotemporal patterns of rainfall trends, using non-parametric statistical techniques, in Karnataka state, India
    Harishnaika, N.
    Shilpa, N.
    Ahmed, S. A.
    ENVIRONMENTAL MONITORING AND ASSESSMENT, 2023, 195 (07)
  • [48] STATISTICAL QUESTION Non-parametric statistical tests for independent groups: numerical data
    Sedgwick, Philip
    BRITISH MEDICAL JOURNAL, 2012, 344
  • [49] Non-parametric Statistical Learning for URLLC Transmission Rate Control
    Zhang, Wenheng
    Derakhshani, Mahsa
    Lambotharan, Sangarapillai
    IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC 2021), 2021,
  • [50] Non-parametric statistical thresholding for sparse magnetoencephalography source reconstructions
    Owen, Julia P.
    Sekihara, Kensuke
    Nagarajan, Srikantan S.
    FRONTIERS IN NEUROSCIENCE, 2012, 6