Risk scenario prediction for sudden water pollution accidents based on Bayesian networks

Tiejun Cheng (), Panpan Wang and Qianyi Lu
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Tiejun Cheng: Nanjing University of Posts and Telecommunications
Panpan Wang: Nanjing University of Posts and Telecommunications
Qianyi Lu: Nanjing University of Posts and Telecommunications

International Journal of System Assurance Engineering and Management, 2018, vol. 9, issue 5, No 16, 1165-1177

Abstract: Abstract Predicting and analyzing the future possible scenario of the sudden water pollution accident can help emergency managers to get know the possible future of the accident and make response. In this paper, the Bayesian Network (BN) is extended to support emergency decision for sudden water pollution accidents. Three types of node variables for BN are built according to the characteristics of sudden water pollution accident. Then, the directed acyclic graph (DAG) is constructed to connect the variables. Through Estimating of the conditional probability of BN, the possible scenario of sudden water pollution accident can be formed based DAG and BN. Finally, the Longjiang River cadmium pollution in Guangxi Province is given to illustrate the feasibility and validity of the proposed method. The results show that the BN can give the possible scenario of the sudden pollution accident and can help emergency managers to make detailed alternatives further to minimize the losses.

Keywords: Risk scenario prediction; Bayesian Networks; Sudden water pollution accidents; The Longjiang River cadmium pollution (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1007/s13198-018-0724-y

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