【摘 要】
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The application of Bayesian network (BN) theory in risk assessment is an emerging trend.But in cases where data are incomplete and variables are mutually relate
【机 构】
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Research Center of Ocean Environment Numerical Simulation, Institute of Meteorology and Oceanography
论文部分内容阅读
The application of Bayesian network (BN) theory in risk assessment is an emerging trend.But in cases where data are incomplete and variables are mutually related,its application is restricted.To overcome these problems,an improved BN assessment model with parameter retrieval and decorrelation ability is proposed.First,multivariate nonlinear planning is applied to the feedback error leaing of parameters.A genetic algorithmis used to lea the probability distribution of nodes that lack quantitative data.Then,based on an improved grey relational analysis that considers the correlation of variation rate,the optimal weight that characterizes the correlation is calculated and the weighted BN is improved for decorrelation.An improved risk assessment model based on the weighted BN then is built.An assessment of sea ice disaster shows that the model can be applied for risk assessment with incomplete data and variable correlation.
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