中国安全科学学报 ›› 2018, Vol. 28 ›› Issue (12): 1-6.doi: 10.16265/j.cnki.issn1003-3033.2018.12.001

• 安全科学技术基础学科 •    下一篇

山区公路暴雨-洪水灾害链贝叶斯网络建模推理

罗军华1, 林孝松1 教授, 牟凤云1 教授, 余情2 讲师, 鲁小平3   

  1. 1 重庆交通大学 建筑与城市规划学院,重庆 400074
    2 重庆交通大学 土木工程学院,重庆 400074
    3 重庆市气象局,重庆 401147
  • 收稿日期:2018-09-20 修回日期:2018-11-05 发布日期:2020-11-25
  • 作者简介:罗军华 (1995—),男,贵州铜仁人,硕士研究生,研究方向为自然灾害风险评估与模拟预测。E-mail:674914258@qq.com。
  • 基金资助:
    国家自然科学基金资助(41601564);国家自然科学基金校内培育项目资助(2018PY15);重庆市基础研究与前沿探索项目(cstc2018jcyjAX0156)。

Inference modeling of mountainous highway rainstorm-flood disaster chain based on Bayesian network

LUO Junhua1, LIN Xiaosong1, MU Fengyun1, YU Qing2, LU Xiaoping3   

  1. 1 College of Architecture and Urban Planning, Chongqing Jiaotong University, Chongqing 400074, China
    2 Civil Engineering College, Chongqing Jiaotong University, Chongqing 400074, China
    3 Chongqing Meteorological Bureau, Chongqing 401147, China
  • Received:2018-09-20 Revised:2018-11-05 Published:2020-11-25

摘要: 为提供山区公路暴雨-洪水灾害的防灾减灾工作依据,利用贝叶斯网络,研究不同情形下灾害链中公路构筑物的破损情况。山区公路暴雨-洪水灾害的演化过程具有链式规律,将其划分为暴雨灾害链和公路构筑物破坏链;以贝叶斯复杂网络理论为基础,结合重庆市、湖南省山区公路暴雨-洪水灾害历史灾情数据,分析公路各构筑物间相互影响方式,构建山区公路暴雨-洪水灾害链贝叶斯网络推理模型,并以湖南省绥宁县2015年6月18日省道S221武阳镇至李熙桥镇路段灾害为例进行模型验证。结果表明:利用贝叶斯网络工具箱,通过网络架构搭建、节点参数设定、联合树推理引擎调用等过程,可实现不同证据组合下贝叶斯网络推理预测;实例的模型预测结果与灾害实际情况吻合较好,证实了山区公路暴雨-洪水灾害链贝叶斯网络模型预测的可行性。

关键词: 山区公路, 暴雨-洪水, 灾害链, 贝叶斯网络, 推理

Abstract: In order to provide reference basis for the disaster prevention and mitigation work of rainstorm-flood disaster on mountainous highway, the Bayesian network was used to study the damage to highway structures in the disaster chain under different circumstances. The evolutional process of rainstorm-flood disasters on mountainous highway with chain-rules characteristic was divided into a rainstorm disaster chain and a highway-structure destruction chain. Based on the Bayesian complex network theory, interaction modes between highway structures were analyzed. A Bayesian network inference model was built for rainstorm-flood disaster chain on mountainous highway on the basis of historical data on disasters in Chongqing city and Hunan province. The effectiveness of the model was checked by a case study of a disaster occurred on the section of provincial highway 221 between Wuyang and Lixiqiao town in Suining county Hunan province on June 18, 2015. The result shows that Bayesian network inference under different combined evidence can be implemented by using Bayesian network toolbox with network framework construction, node parameter setting, joint tree inference engine calling and so on, and that prediction result obtained by using the conforms with the actual disaster condition.

Key words: mountainous highway, rainstorm-flood, disaster chain, Bayesian network, inference

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