DBN structure learning based on MI-BPSO algorithm

Guoliang Li, Xiaoguang Gao, Ruohai Di

科研成果: 书/报告/会议事项章节会议稿件同行评审

6 引用 (Scopus)

摘要

To improve the accuracy of structure learning for Dynamic Bayesian Network (DBN), this paper proposes Mutual Information-Binary Particle Swarm Optimization (MI-BPSO) algorithm. The MI-BPSO algorithm firstly uses MI and conditional independence test to prune the search space and speed up the convergence of the searching phase, then calls BPSO algorithm to search the constrained space and get the intra-network and inter-network of DBN. Experimental results show that this algorithm performs as well as K2 while it doesn't need a given variable ordering, and performs better than MWST-GES, MWST-HC and I-BN-PSO.

源语言英语
主期刊名2014 IEEE/ACIS 13th International Conference on Computer and Information Science, ICIS 2014 - Proceedings
编辑Yan Han, Wenai Song, Simon Xu, Lichao Chen, Roger Lee
出版商Institute of Electrical and Electronics Engineers Inc.
245-250
页数6
ISBN(电子版)9781479948604
DOI
出版状态已出版 - 26 9月 2014
活动2014 13th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2014 - Proceedings - Taiyuan, 中国
期限: 4 6月 20146 6月 2014

出版系列

姓名2014 IEEE/ACIS 13th International Conference on Computer and Information Science, ICIS 2014 - Proceedings

会议

会议2014 13th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2014 - Proceedings
国家/地区中国
Taiyuan
时期4/06/146/06/14

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