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Bayesian network learning algorithm based on unconstrained optimization and ant colony optimization 被引量：3

Bayesian network learning algorithm based on unconstrained optimization and ant colony optimization
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摘要 Structure learning of Bayesian networks is a wellresearched but computationally hard task.For learning Bayesian networks,this paper proposes an improved algorithm based on unconstrained optimization and ant colony optimization（U-ACO-B） to solve the drawbacks of the ant colony optimization（ACO-B）.In this algorithm,firstly,an unconstrained optimization problem is solved to obtain an undirected skeleton,and then the ACO algorithm is used to orientate the edges,thus returning the final structure.In the experimental part of the paper,we compare the performance of the proposed algorithm with ACO-B algorithm.The experimental results show that our method is effective and greatly enhance convergence speed than ACO-B algorithm. Structure learning of Bayesian networks is a wellresearched but computationally hard task.For learning Bayesian networks,this paper proposes an improved algorithm based on unconstrained optimization and ant colony optimization（U-ACO-B） to solve the drawbacks of the ant colony optimization（ACO-B）.In this algorithm,firstly,an unconstrained optimization problem is solved to obtain an undirected skeleton,and then the ACO algorithm is used to orientate the edges,thus returning the final structure.In the experimental part of the paper,we compare the performance of the proposed algorithm with ACO-B algorithm.The experimental results show that our method is effective and greatly enhance convergence speed than ACO-B algorithm.
作者 Chunfeng Wang Sanyang Liu Mingmin Zhu
机构地区 Department of Mathematical Sciences Department of Mathematics
出处 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2012年第5期784-790,共7页 系统工程与电子技术（英文版）
基金 supported by the National Natural Science Foundation of China (60974082,11171094) the Fundamental Research Funds for the Central Universities (K50510700004) the Foundation and Advanced Technology Research Program of Henan Province (102300410264) the Basic Research Program of the Education Department of Henan Province (2010A110010)
关键词 Bayesian network structure learning ant colony optimization unconstrained optimization Bayesian network structure learning ant colony optimization unconstrained optimization
分类号 TP183 [自动化与计算机技术—控制理论与控制工程] O224 [理学—运筹学与控制论]
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参考文献22

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同被引文献19

  • 1Chen Fei Wang Xiufeng Rao Yimei.Learning Bayesian networks using genetic algorithm[J].Journal of Systems Engineering and Electronics,2007,18(1):142-147. 被引量：3
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  • 8Iannis T, Laura E B, Constantin F A. The max-min hill-climbing Bayesian network structure learning algorithm[J]. Machine Learning, 2006,65(10) : 31-78.
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二级引证文献12

Journal of Systems Engineering and Electronics
2012年 第5期

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