@inproceedings{f3b14815394a4028941e4ff1aaacd030,
title = "DBN structure learning based on MI-BPSO algorithm",
abstract = "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.",
keywords = "binary particle swarm optimization, dynamic Bayesian network, mutual information, structure learning",
author = "Guoliang Li and Xiaoguang Gao and Ruohai Di",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 13th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2014 - Proceedings ; Conference date: 04-06-2014 Through 06-06-2014",
year = "2014",
month = sep,
day = "26",
doi = "10.1109/ICIS.2014.6912142",
language = "英语",
series = "2014 IEEE/ACIS 13th International Conference on Computer and Information Science, ICIS 2014 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "245--250",
editor = "Yan Han and Wenai Song and Simon Xu and Lichao Chen and Roger Lee",
booktitle = "2014 IEEE/ACIS 13th International Conference on Computer and Information Science, ICIS 2014 - Proceedings",
}