Paper Title:
Root Node Vaccines for Bayesian Network Structure Learning Based on Immune Algorithm
  Abstract

To facilitate the application of Bayesian network in engineering fields, learning proper structure from dataset is one of the most efficiency Bayesian network modeling technique. In this paper, the description and characteristics of Bayesian networks and immune algorithms are discussed at first. Then, the extraction method of root node vaccines is proposed to accelerate the model structure learning process. Thirdly, the immune algorithm based method is also applied to search the best Bayesian network structure. Finally, the simulation studies based on a car start BN model are carried out and the results verify that the proposed Bayesian network structure learning method can build the objective structure from dataset more effectively and more efficiently with the root node vaccines.

  Info
Periodical
Chapter
Chapter 3: Computational Methods for Engineering
Edited by
Elwin Mao and Linli Xu
Pages
268-272
DOI
10.4028/www.scientific.net/AEF.1.268
Citation
Z. Q. Cai, S. D. Sun, S. B. Si, N. Wang, "Root Node Vaccines for Bayesian Network Structure Learning Based on Immune Algorithm", Advanced Engineering Forum, Vol. 1, pp. 268-272, 2011
Online since
September 2011
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