06090614

j

06090614 Di, Ruohai Gao, Xiaoguang Bayesian network structure learning based on restricted particle swarm optimization. Syst. Eng. Electron. 33, No. 11, 2423-2427 (2011). 2011 Editorial Department of Systems Engineering and Electronics, Beijing ZH Bayesian network structure learning mutual information particle swarm optimization

doi:10.3969/j.issn.1001-506X.2011.11.15

Summary: The Bayesian network structure learning is one of the main research technologies in the field of data mining and knowledge discovery, while the search space of the network structure is relatively bigger, some existing algorithms have some defects that the convergent speed is slow and the accuracy is poor. In this paper, a kind of information theory combining particle swarm optimization algorithm is put forward, which uses mutual information to limit particle initialization, and makes the particle swarm optimization algorithm converge in a relatively short period of time, then an ASIA network is applied as the simulation model and the proposed algorithm is compared with K2 algorithm. Experimental results show that the proposed algorithm can rapidly and accurately get Bayesian network structures.