Please wait a minute...
J4  2014, Vol. 48 Issue (1): 130-135    DOI: 10.3785/j.issn.1008-973X.2014.01.020
    
Bayesian network structure learning based on hybrid genetic
and fish swarm algorithm
GUO Tong,LIN Feng
School of Electrical Engineering, Zhejiang University, Hangzhou 310027, China 
Download:   PDF(746KB) HTML
Export: BibTeX | EndNote (RIS)       Supporting Info

Abstract  

The method of learning Bayesian network structure was proposed based on hybrid genetic and fish swarm algorithm. The method used the maximum weight spanning tree to generate the candidate networks. Then the artificial fish swarm algorithm referring to the ideas of crossover and mutation methods of genetic algorithm was used to optimize the initial populations. Because of the randomness of the stage of the searching food in the artificial fish swarm algorithm, the cloud-based adaptive theory was brought into this stage to improve it. Simulation experiments on ASIA and ALARM demonstrate that the approach has quite good optimization ability in Bayesian network structure learning.



Published: 01 January 2014
CLC:  TP 393  
Cite this article:

GUO Tong,LIN Feng. Bayesian network structure learning based on hybrid genetic
and fish swarm algorithm. J4, 2014, 48(1): 130-135.

URL:

http://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2014.01.020     OR     http://www.zjujournals.com/eng/Y2014/V48/I1/130


基于混合遗传鱼群算法的贝叶斯网络结构学习

提出基于云自适应的遗传鱼群算法的结构学习方法.该方法利用最大生成树准则得到初始种群,将遗传算法中的交叉、变异思想分别应用于人工鱼群算法的聚群、追尾、觅食阶段,从而改进鱼群算法进行初始种群的优化.由于鱼群算法的觅食阶段的较强随机性,将云自适应理论应用于觅食阶段生成变异率.在ASIA和ALARM上的仿真实验证明,混合遗传鱼群算法在贝叶斯网络结构学习中具有很强的寻优能力.

[1] HECKMAN D,WELLMAN M. Bayesian networks [J]. CACM,1995,38(3):27-30.
[2] FRIDEMAN N,LINIAL M,NACHMAN I. Using Bayesian networks to analyze data [J]. Journal of Computational Biology,2007(3):601-620.
[3] CHICKERING D M,HECKERMAN D,MEEK C. Large-sample learning of Bayesian networks is NP-hard [J]. Journal of Machine Learning Research,2004(5):1287-1330.
[4] CHENG J, BELL D A, LIU W. An algorithm for Bayesian belief network construction from data [C]∥Proceedings of the 6th International Workshop on Artificial Intelligence and Statistics. Lauderdale,Florida:[s. n.],1997:83-90 .
[5] CHOW C,LIU C. Approximation discrete probability distributions with dependence trees [J]. IEEE Transactions on Information Theory,1968,14(3):462-467.
[6] LARRANAGA P,POZA M,YURRAMENDI Y,et al. Structure learning of Bayesian networks by genetic algorithms:a performance analysis of control parameters [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence,1996,18(9):912-926.
[7] 李晓磊,邵之江,钱积新. 一种基于动物自治体的寻优模式:鱼群算法[J] . 系统工程理论与实践, 2002(11):32-38.
LI Xiao-lei,SHAO Zhi-jiang,QIAN Ji-xin.An optimizing method based on autonomous animats:fish swarm algorithm [J]. Systems Engineering: Theory and Practice,2002(11):32-38.
[8] 李德毅,孟海军,史雪梅. 隶属云和隶属云发生器[J]. 计算机研究与发展,1995,32(6):15-20 .
LI De-yi,MENG Hai-jun,SHI Xue-mei. Membership clouds and membership cloud generators [J]. Journal of Computer Research and Development,1995,32(6):15-20.
[9] 许丽佳,黄建国,王厚军,等. 混合优化的贝叶斯网络结构学习[J]. 计算机辅助设计与图形学学报, 2009,21(5):633-639.
XU Li-jia,HUANG Jian-guo,WANG Hou-jun, et al. Hybrid optimized algorithm for learning Bayesian network structure [J]. Journal of Computer-aided design and Computer Graphics,2009, 21(5):633-639.
[10] 沈佳杰,林峰.基于混合自适应Memetic算法的贝叶斯网络结构学习[J].系统工程与电子技术,2012, 34(6): 1293-1298.
SHEN Jia-jie,LIN Feng. Structure learning of Bayesian network using adaptive hybrid memetic algorithm [J]. Systems Engineering and Electronics,2012,34(6):1293-1298.
[11] 戴朝华,朱云芳,陈维荣.云自适应遗传算法[J] .控制理论与应用, 2007,24(4):646-650.
DAI Chao-hua,ZHU Yun-fang,CHEN Wei-rong. Adaptive genetic algorithm based on cloud theory [J]. Control Theory and Applications,2007,24(4):646650.
[12] 王翔,郑建国,张超群,等.采用约束蚁群优化的贝叶斯网结构学习算法[J].西安交通大学学报,2011,45(8):54-61.
WANG Xiang,ZHENG Jian-guo,ZHANG Chao-qun, et al. A constrained ant colony optimization algorithm for learning Bayesian networks [J]. Journal of Xi’an Jiaotong University,2011,45(8):54-61.
[13] 邸若海,高晓光.基于限制型粒子群优化的贝叶斯网络结构学习[J].系统工程与电子技术,2011,33(11):2423-2427.
DI Ruo-hai, GAO Xiao-guang. Bayesian network structure learning based on restricted particle swarm optimization [J]. Systems Engineering and Electronics,2011,33(11):2423-2427.
[14] CHICKERING D M. Optimal structure identification with greedy search [J]. Journal of Machine Learning Research,2002,3:507-554.

[1] I De-jun,WANG Gang,YANG Can-jun,JIN Bo,CHEN Yan-hu. NTP/IEEE1588-based time synchronization system in seafloor observatory network[J]. J4, 2014, 48(1): 1-7.
[2] DU Rui-zhong, TIAN Jun-feng, ZHANG Huan-guo. Cloud service selection model based on trust and personality preferences[J]. J4, 2013, 47(1): 53-61.
[3] ZHANG Shuai, SUN Jian-ling, XU Bin, HUANG Chao, KAVS Aleksander J.. RBAC based access control model for services compositions
cross multiple enterprises
[J]. J4, 2012, 46(11): 2035-2043.
[4] Chen Sui-sheng,Lu Jian-gang,Lou Xiao-chun. Localization algorithm for wireless sensor networks
based on MDS-MAP and nonlinear filtering
[J]. J4, 2012, 46(5): 866-872.
[5] YANG Zhao-hui, LI Shan-ping, LIN Xin. Quality optimizing real-time scheduling for incremental context services[J]. J4, 2012, 46(1): 90-97.
[6] PAN Ju-long, LI Shan-ping, ZHANG Dao-yuan. Detecting suspicious node within one cluster in wireless sensor network
using game theoretic approach
[J]. J4, 2012, 46(1): 72-78.
[7] GAO Qing,LI Shan-ping,YANG Zhao-hui. Virtual force-field based energy efficient geo-routing in
wireless sensor network
[J]. J4, 2012, 46(1): 98-104.
[8] QIAN Jian-feng, YIN Jian-wei, DONG Jin-xiang. Load balancing algorithms of semantic publish/subscribe system
over structured P2P networks
[J]. J4, 2011, 45(10): 1710-1719.
[9] YANG Zhao-hui, LI Shan-ping, LIN Xin. Anonymity level adaptation algorithm to meet resource constraint
of K-anonymity service in LBS
[J]. J4, 2011, 45(7): 1154-1160.
[10] PAN Gang, LI Shi-jian, CHEN Yun-xing. ScudContext: large-scale environmental context services infrastructure
towards cyber-physical space integration
[J]. J4, 2011, 45(6): 991-998.
[11] CHE Jian-hua, HE Qin-ming, CHEN Jian-hai, WANG Bei. Software simulation-based fault injection tool of
virtual machine system
[J]. J4, 2011, 45(4): 614-620.
[12] LI Jian-ting, JIN Xin-yu, TANG Jun, ZHANG Yu. Target localization method based on wireless multimedia sensor network[J]. J4, 2011, 45(1): 45-49.
[13] ZHANG Li-ping, PAN Gang, ZHENG Neng-gan, YANG Guo-qing, LI Hong, ZHAO Min-de. Consistent bidirectional generation method and  development
platform based on SmartC models and codes
[J]. J4, 2011, 45(1): 20-29.
[14] SHU Ting, SUN Shou-qian, WANG Hai-ning, XU Wei-qiang. Adaptive generation algorithm for executable state identification
sequences in EFSM model
[J]. J4, 2010, 44(11): 2183-2187.
[15] CHEN You-Rong, SHU Li, DONG Ji-Fen, HONG Zhen. Power control in wireless sensor network based on
nearestneighbor algorithm
[J]. J4, 2010, 44(7): 1321-1326.