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裘江南, 王延章, 董磊磊, 等. 基于贝叶斯网络的突发事件预测模型[J]. 系统管理学报, 2011, 20(1): 98-102. QIU Jiangnan, WANG Yanzhang, DONG Leilei, et al. A model for predicting emergency event based on Bayesian Networks. Journal of Systems & Management, 2011, 20(1): 98-102. (in Chinese)

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• 标题: 基于贝叶斯网络的钱塘江河口地区咸潮入侵研究Analysis on Saline Water Intrusion in Qiantang River Based on Bayesian Network

  作者: 高希超, 马冲, 张徐杰, 许月萍, 张永强

  关键字: 贝叶斯网络, 咸潮入侵, 钱塘江河口, 联合风险Bayesian Network; Saline Water Intrusion; Estuary of Qiantang River; Joint Risk

  期刊名称: 《Journal of Water Resources Research》, Vol.1 No.6, 2012-11-20

  摘要: 本文建立了钱塘江下游桐庐、闸口及瞰浦三站水(潮)位之间的贝叶斯网络模型，并对网络模型的参数进行了估计和分析。通过三站高、低水位的不同遭遇情况来确定是否有咸潮入侵的情况发生，给出了桐庐、闸口两站咸潮入侵的概率，且通过贝叶斯网络的推理功能对所研究地区的咸潮入侵情况进行仿真分析，给出在某些特定情况下各站发生咸潮入侵的概率。 Saline water intrusion in QiantangRiverexerts a severe impact on residential life, environment and economic development. In this article, a simple Bayesian Network model based on water levels of Tong- lu, Zhakou and Kanpu stations is established and the parameters are analyzed through the observation data. Whether the saline water intrusion will occur or not is determined by the relative water level of Tonglu, Zha- kou and Kanpu stations. Based on the model, the probability of saline water intrusion at Tonglu and Zhakou stations is determined. The reasoning ability of Bayesian Network is utilized to simulate the potential saline water intrusion in some certain situations.