| 面向粒子群优化的贝叶斯网络结构学习算法 |
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| 引用本文： | 黄河笑,衡星辰,彭建涵. 面向粒子群优化的贝叶斯网络结构学习算法[J]. 计算机工程与应用, 2010, 46(20): 193-196. DOI: 10.3778/j.issn.1002-8331.2010.20.053 |
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| 作者姓名： | 黄河笑 衡星辰 彭建涵 |
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| 作者单位： | 1.上海电视大学 信息与工程系，上海 200433 2.国网信息通信有限公司，北京 100054 |
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| 基金项目： | 国家重点基础研究发展规划（973）No.2004CB719400 |
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| 摘 要： | 提出了一种基于离散粒子群优化的贝叶斯网络结构学习算法——PSBN（Particle Swarm for Bayesian Network）。贝叶斯网络的结构被映射为一种符号编码，通过在迭代过程中对粒子的符号编码进行调整，从而进化得到具有更高适应度值的贝叶斯网络结构。根据贝叶斯网络的结构特点，粒子位置和速度的编码方案和基本操作被设计，使得算法对贝叶斯网络的结构学习有较好的收敛性。实验结果表明，与基于遗传算法的贝叶斯网络结构学习算法相比，PSBN算法具有较好的学习效果。
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| 关 键 词： | 贝叶斯网络 粒子群优化 适应度函数 结构学习 符号编码 |
| 收稿时间： | 2010-04-15 |
| 修稿时间： | 2010-5-18 |
Structure learning algorithm of Bayesian networks on particle swarm optimization |
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| HUANG He-xiao,HENG Xing-chen,PENG Jian-han. Structure learning algorithm of Bayesian networks on particle swarm optimization[J]. Computer Engineering and Applications, 2010, 46(20): 193-196. DOI: 10.3778/j.issn.1002-8331.2010.20.053 |
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| Authors: | HUANG He-xiao HENG Xing-chen PENG Jian-han |
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| Affiliation: | 1.Department of Information and Engineering，Shanghai Television University，Shanghai 200433，China 2.State Grid Information & Telecommunication Co.，Ltd，Beijing 100054，China |
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| Abstract: | A discrete PSO（Particle Swarm Optimization） based Bayesian network structure learning algorithm—PSBN（Particle Swarm for Bayesian Network） is proposed.A fitness function is given to evaluate the possible BN structure.Based on the characteristics of BN structure,the definition and encoding of the position and velocity of particle in PSO are given,and the basic operations of PSO are designed,which provides guarantee of convergence.As BN structure is considered as a symbol encoding,the BN structure having higher fitness values can be gotten by changing the symbol encoding of particles.The experimental results show this algorithm has better performance than the BN structure learning algorithm based on genetic algorithm. |
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| Keywords: | Bayesian network particle swarm optimization fitness function structure learning symbol encoding |
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