DocumentCode :
3237289
Title :
Cooperative coevolutionary genetic algorithms to find optimal elimination orderings for Bayesian networks
Author :
Dong, Xuchu ; Yu, Haihong ; Ouyang, Dantong ; Cai, Dianbo ; Ye, Yuxin ; Zhang, Yonggang
Author_Institution :
Dept. of Comput. Sci. & Technol., Jilin Univ., Changchun, China
fYear :
2010
fDate :
23-26 Sept. 2010
Firstpage :
1388
Lastpage :
1394
Abstract :
According to the characteristics of the optimal elimination ordering problem in Bayesian networks, a heuristic-based genetic algorithm, a cooperative coevolutionary genetic framework and five grouping schemes are proposed. Based on these works, six cooperative coevolutionary genetic algorithms are constructed. Numerical experiments show that these algorithms are more robust than other existing swarm intelligence methods when solving the elimination ordering problem.
Keywords :
belief networks; genetic algorithms; Bayesian network; cooperative coevolutionary genetic algorithm; heuristic-based genetic algorithm; optimal elimination ordering; Bayesian methods; Genetics; Robustness; Bayesian networks; cooperative coevolution; elimination ordering; genetic algorithms; grouping scheme;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bio-Inspired Computing: Theories and Applications (BIC-TA), 2010 IEEE Fifth International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4244-6437-1
Type :
conf
DOI :
10.1109/BICTA.2010.5645605
Filename :
5645605
Link To Document :
بازگشت