Title
Risk scenario prediction for sudden water pollution accidents based on Bayesian networks.
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.
Year
DOI
Venue
2018
10.1007/s13198-018-0724-y
Int. J. Systems Assurance Engineering and Management
Keywords
Field
DocType
Risk scenario prediction, Bayesian Networks, Sudden water pollution accidents, The Longjiang River cadmium pollution
Mathematical optimization,Conditional probability,Operations research,Pollution,Directed acyclic graph,Bayesian network,Water pollution,Engineering
Journal
Volume
Issue
ISSN
9
5
0975-6809
Citations 
PageRank 
References 
0
0.34
3
Authors
3
Name
Order
Citations
PageRank
Tiejun Cheng130222.39
Panpan Wang2205.75
Qianyi Lu300.34