id: 06098266
dt: j
an: 06098266
au: GGao, Wen-Yu; Zhang, Li
ti: Approximation algorithm of variable elimination of Bayesian network.
so: J. Comput. Appl. 31, No. 8, 2072-2074 (2011).
py: 2011
pu: Science Press, Beijing
la: ZH
cc: 
ut: Bayesian network; Variable Elimination (VE); approximately algorithms;
    moral graph; clique
ci: 
li: doi:10.3724/SP.J.1087.2011.02072
ab: Summary: Variable Elimination (VE) is a basic reasoning method of Bayesian
    network; however, different order of elimination will lead to
    computational complexity of significant differences. It is a NP-hard
    problem to find the optimal order, so in practical application
    approximation algorithm is often used. Based on the analysis of the
    moral graph of Bayesian network, the added edges and the removed edges
    during elimination were considered, some methods of reducing graph
    complexity and controlling elimination cost were proposed, and a new
    algorithm was presented. Finally, the new algorithm was tested by
    random simulations. The simulation results show that the new algorithm
    outperforms the minimum deficiency search algorithm.
rv: