Study on dependency analysis method for learning dynamic Bayesian network structure

doi:10.3778/j.issn.1002-8331.2011.03.015

Computer Engineering and Applications ›› 2011, Vol. 47 ›› Issue (3): 51-53.DOI: 10.3778/j.issn.1002-8331.2011.03.015

• 研究、探讨 • Previous Articles Next Articles

Study on dependency analysis method for learning dynamic Bayesian network structure

LENG Cuiping¹，WANG Shuangcheng^1，2，WANG Hui³

1.School of Mathematics & Information，Shanghai Lixin University of Commerce，Shanghai 201620，China
2.Opening Economy & Trade Research Center，Shanghai Lixin University of Commerce，Shanghai 201620，China
3.School of Information Engineering，The Central University for Nationalities，Beijing 100081，China

Received:2009-05-25 Revised:2009-07-26 Online:2011-01-21 Published:2011-01-21
Contact: LENG Cuiping

动态贝叶斯网络结构学习的依赖分析方法研究

冷翠平¹，王双成^1，2，王辉³

1.上海立信会计学院数学与信息学院，上海 201620
2.上海立信会计学院开放经济与贸易研究中心，上海 201620
3.中央民族大学信息工程学院，北京 100081

通讯作者: 冷翠平

Abstract

Abstract: At present，the methods of learning Dynamic Bayesian Network（DBN） structure have low efficiency and reliability.Learning dynamic Bayesian network structure is done based on the basic dependency relationship between variables and dependency analysis method.A sketch of dependency relationship between variables is built.Then the redundant edges can be got rid of by the conditional independent test.And the edges are oriented through the collision identify and the relative conditional prediction capability.Therefore，the dynamic Bayesian network structure can be established.This method has high efficiency and reliability.

Key words: Dynamic Bayesian Network（DBN）, dependency analysis, prior network, transition network, structure learning

摘要： 针对现有动态贝叶斯网络结构学习方法具有低效率和低可靠性等问题，基于变量之间的基本依赖关系和依赖分析方法进行动态贝叶斯网络结构学习。建立变量之间依赖关系草图，通过条件独立行检验去除多余的边，使用碰撞识别和条件相对预测能力确定边的方向，便可得到构成动态贝叶斯网络结构的先验网和转换网。该方法在效率和可靠性方面均具有优势。

关键词: 动态贝叶斯网络, 依赖分析, 先验网, 转换网, 结构学习

CLC Number:

TP391

LENG Cuiping¹，WANG Shuangcheng^1，2，WANG Hui³. Study on dependency analysis method for learning dynamic Bayesian network structure[J]. Computer Engineering and Applications, 2011, 47(3): 51-53.

冷翠平¹，王双成^1，2，王辉³. 动态贝叶斯网络结构学习的依赖分析方法研究[J]. 计算机工程与应用, 2011, 47(3): 51-53.

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Study on dependency analysis method for learning dynamic Bayesian network structure

动态贝叶斯网络结构学习的依赖分析方法研究

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