Radiation anomaly detection and classification with Bayes Model Selection

被引：1
|
作者：
Pfund, D. M. [1 ]
机构：
[1] Pacific Northwest Natl Lab, POB 999, Richland, WA 99352 USA
来源：
NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT | 2018年 / 904卷
关键词：
Anomaly detection; Gamma-ray spectroscopy; Radiation monitoring; Threat identification; SPECTRAL COMPARISON RATIOS;
D O I：
10.1016/j.nima.2018.07.047
中图分类号：
TH7 [仪器、仪表];
学科分类号：
0804 ; 080401 ; 081102 ;
摘要：
We present a new method for radiation anomaly detection that is based on Bayes Model Selection (BMS), together with models for gamma-radiation measurements from benign and threat sources. The method estimates the relative odds of pairs of such models, with the aim of supporting related hypotheses about the nature of the underlying source material. We also discuss partial optimization of the parameters in the models. The method allows measurements to be broadly categorized and screened for sources of interest in real time, a property that should improve the efficiency of mobile search or unattended monitoring operations
引用
收藏
页码：188 / 194
页数：7
相关论文
共 50 条
  • [1] Model Selection for Anomaly Detection
    Burnaev, E.
    Erofeev, P.
    Smolyakov, D.
    [J]. EIGHTH INTERNATIONAL CONFERENCE ON MACHINE VISION (ICMV 2015), 2015, 9875
  • [2] Automatic Model Selection for Anomaly Detection
    Wang, Ziyu
    Yang, Jiahai
    Zhang, Shize
    Li, Chenxi
    Zhang, Hui
    [J]. 2016 IEEE TRUSTCOM/BIGDATASE/ISPA, 2016, : 276 - 283
  • [3] Combining negative selection and classification techniques for anomaly detection
    Gonzalez, F
    Dasgupta, D
    Kozma, R
    [J]. CEC'02: PROCEEDINGS OF THE 2002 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1 AND 2, 2002, : 705 - 710
  • [4] SHAPE CLASSIFICATION OF ALTIMETRIC SIGNALS USING ANOMALY DETECTION AND BAYES DECISION RULE
    Tourneret, J. -Y.
    Mailhes, C.
    Severini, J.
    Thibaut, P.
    [J]. 2010 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2010, : 1222 - 1225
  • [5] A model for anomaly classification in intrusion detection systems
    Ferreira, V. O.
    Galhardi, V. V.
    Goncalves, L. B. L.
    Silva, R. C.
    Cansian, A. M.
    [J]. 4TH INTERNATIONAL CONFERENCE ON MATHEMATICAL MODELING IN PHYSICAL SCIENCES (IC-MSQUARE2015), 2015, 633
  • [6] Variable selection for Naive Bayes classification
    Blanquero, Rafael
    Carrizosa, Emilio
    Ramirez-Cobo, Pepa
    Remedios Sillero-Denamiel, M.
    [J]. COMPUTERS & OPERATIONS RESEARCH, 2021, 135
  • [7] BAYES PROCEDURES OF TRAINING SELECTION CLASSIFICATION
    FLEISHER, SM
    [J]. RADIOTEKHNIKA I ELEKTRONIKA, 1972, 17 (03): : 526 - &
  • [8] Anomaly process detection using negative selection algorithm and classification techniques
    Hosseini, Soodeh
    Seilani, Hossein
    [J]. EVOLVING SYSTEMS, 2021, 12 (03) : 769 - 778
  • [9] Anomaly process detection using negative selection algorithm and classification techniques
    Soodeh Hosseini
    Hossein Seilani
    [J]. Evolving Systems, 2021, 12 : 769 - 778
  • [10] Characterization of the Autoencoder Radiation Anomaly Detection (ARAD) model
    Ghawaly, James M., Jr.
    Nicholson, Andrew D.
    Archer, Daniel E.
    Willis, Michael J.
    Garishvili, Irakli
    Longmire, Brandon
    Rowe, Andrew J.
    Stewart, Ian R.
    Cook, Matthew T.
    [J]. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2022, 111
12345