Learning Bayesian network structure with immune algorithm

被引：1

作者：

Cai, Zhiqiang ^{[1
]}

Si, Shubin ^{[1
]}

Sun, Shudong ^{[1
]}

Dui, Hongyan ^{[1
]}

机构：

[1] Northwestern Polytech Univ, Sch Mechatron, Key Lab Contemporary Design & Integrated Mfg Tech, Minist Educ, Xian 710072, Peoples R China

来源：

JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS | 2015年 / 26卷 / 02期

基金：

中国国家自然科学基金;

关键词：

structure learning; Bayesian network; immune algorithm; local optimal structure; vaccination;

D O I：

10.1109/JSEE.2015.00034

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Finding out reasonable structures from bulky data is one of the difficulties in modeling of Bayesian network (BN), which is also necessary in promoting the application of BN. This paper proposes an immune algorithm based method (BN-IA) for the learning of the BN structure with the idea of vaccination. Furthermore, the methods on how to extract the effective vaccines from local optimal structure and root nodes are also described in details. Finally, the simulation studies are implemented with the helicopter convertor BN model and the car start BN model. The comparison results show that the proposed vaccines and the BN-IA can learn the BN structure effectively and efficiently.

引用

页码：282 / 291

页数：10

共 27 条

[1] Learning Bayesian networks in the space of structures by estimation of distribution algorithms [J].