现代防御技术 ›› 2018, Vol. 46 ›› Issue (5): 114-121.DOI: 10.3969/j.issn.1009-086x.2018.05.18

• 综合保障性技术 • 上一篇    下一篇

复杂系统工程作业贝叶斯网络风险方法研究

熊娜1, 张孝东1, 李飞1, 马超2   

  1. 1.南昌理工学院,江西 南昌 330044;
    2.空军勤务学院,江苏 徐州 221000
  • 收稿日期:2018-03-19 修回日期:2018-04-24 出版日期:2018-10-30 发布日期:2020-11-25
  • 作者简介:熊娜(1985-),女,江西樟树人。讲师,硕士,从事工程管理研究。通信地址:221000 江苏省徐州市鼓楼区西阁街85号航弹系 E-mail:2249949260@qq.com
  • 基金资助:
    军队预研基金资助项目

Risk Evaluation Method for Complex System Engineering Works Based on Bayesian Network

XIONG Na1, ZHANG Xiao-dong1, LI Fei1, MA Chao2   

  1. 1. Nanchang Institute of Technology,Jiangxi Nanchang 330044,China;
    2. Air Force Logistics College,Jiangsu Xuzhou 221000,China
  • Received:2018-03-19 Revised:2018-04-24 Online:2018-10-30 Published:2020-11-25

摘要: 针对复杂系统工程作业工种多、隐蔽性强、不确定因素多的情况,提出了基于贝叶斯网络的风险评估方法。从工程作业过程分析着手,建立了贝叶斯网络风险评估模型;针对多状态根节点缺乏数据的问题,应用三角模糊函数确定了概率输入;针对多状态节点条件概率值难以获取的问题,应用DS证据理论融合处理专家信息。以安排导弹战备值班为研究对象进行了实例分析。仿真表明,评估模型因果推理即可确定工程作业存在的风险概率;诊断推理即可确定风险发生情况下的关键影响因子,据此可以制定合理的预防性措施。

关键词: 贝叶斯网络, 风险评估, 多状态, 三角模糊函数, 条件概率值, DS证据理论

Abstract: Confronted with the reality of engineering work in complex system involving multi-disciplines, rigid concealment and uncertain factors, a risk evaluation method based on Bayesian network is put forward. By analyzing the process of engineering work, all possible factors are determined for the establishment of Bayesian network model. Aiming at the problem of lacking data for multi-state root nodes, the probabilities are obtained by applying triangular fuzzy function. Aiming at the difficulty in obtaining conditional probability values for multi-state nodes, DS evidence theory is applied to fuse experts' information. Arrangement for missiles in combat duty is taken as an example to perform risk evaluation. The result shows that the risk probability of engineering work can be determined easily through reasoning forward. Through reasoning backward key factors can be pointed out when the risk happens and preventive maintenance policies can be made accordingly.

Key words: Bayesian network, risk evaluation, multi-state, triangular fuzzy function, conditional probability value, DS evidence theory

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