计算机应用 ›› 2012, Vol. 32 ›› Issue (07): 1943-1946.DOI: 10.3724/SP.J.1087.2012.01943

• 先进计算 • 上一篇    下一篇

离散动态贝叶斯网络推理的编程计算算法

史建国1,高晓光2   

  1. 1. 海军航空工程学院 战略导弹工程系,山东 烟台264001
    2. 西北工业大学 电子信息学院,西安710072
  • 收稿日期:2011-12-28 修回日期:2012-02-16 发布日期:2012-07-05 出版日期:2012-07-01
  • 通讯作者: 史建国
  • 作者简介:史建国(1965-),男,辽宁凌源人,教授,博士,主要研究方向:智能火力控制系统;高晓光(1958-),女,辽宁鞍山人,教授,博士,主要研究方向:先进火力控制、大系统。
  • 基金资助:

    国家自然科学基金前期项目(60774064);博士后研究基金资助项目(20080431386)

Programming algorithm for reference of discrete dynamic Bayesian network

SHI Jian-guo1,GAO Xiao-guang2   

  1. 1. Department of Strategy Missile Engineering, Navy Aeronautical and Astronautical University, Yantai Shandong 264001, China
    2. School of Electronics and Information, Northwestern Polytechnical University, Xi'an Shaanxi 710072, China
  • Received:2011-12-28 Revised:2012-02-16 Online:2012-07-05 Published:2012-07-01
  • Contact: SHI Jian-guo

摘要: 离散动态贝叶斯网络是对时间序列进行建模和推理的重要工具,具有广泛的建模应用价值,但是其推理算法还有待进一步完善。针对构离散动态贝叶斯网络的推理算法难以理解、编程计算难、推理速度慢的问题,给出了实现离散动态贝叶斯推理算法的数据结构,推导了进行计算机编程计算的推理算法和编程步骤,并通过实例进行了算理验证。

关键词: 贝叶斯网络, 数据结构, 推理

Abstract: The discrete dynamic Bayesian network is a useful tool for modeling and inferring the time series progress, and it has wide modeling application value. But its inference algorithm needs improving. Concerning the shortcomings of the discrete dynamic Bayesian network, such as its inference algorithm is hard to understand, hard to program and running slowly, this paper proposed the most suitable storage data structure of the discrete dynamic Bayesian network, deduced the fast inference algorithm for the discrete dynamic Bayesian network, and verified the inference algorithm for the discrete dynamic Bayesian networks through a sample.

Key words: Bayesian network, data structure, inference

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