A GA-based approach for parameter learning of discrete dynamic bayesian networks

Huange Wang, Xiaoguang Gao, C. P. Thompson

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Learning dynamic Bayesian networks (DBNs) is one of the current research focuses. In this article a GA-based approach is proposed for DBNs parameters learning from fully and partially observed data. The validity of the novel approach has been demonstrated by a detailedly described example, and the experimental results show that the proposed GA-based approach performs more accurately than the traditional EM algorithm.

源语言英语
主期刊名ICCMS 2010 - 2010 International Conference on Computer Modeling and Simulation
390-393
页数4
DOI
出版状态已出版 - 2010
活动2010 International Conference on Computer Modeling and Simulation, ICCMS 2010 - Sanya, 中国
期限: 22 1月 201024 1月 2010

出版系列

姓名ICCMS 2010 - 2010 International Conference on Computer Modeling and Simulation
1

会议

会议2010 International Conference on Computer Modeling and Simulation, ICCMS 2010
国家/地区中国
Sanya
时期22/01/1024/01/10

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