Generating Graphical Chain by Mutual Matching of Bayesian Network and
  Extracted Rules of Bayesian Network Using Genetic Algorithm
  With the technology development, the need of analyze and extraction of useful
information is increasing. Bayesian networks contain knowledge from data and
experts that could be used for decision making processes But they are not
easily understandable thus the rule extraction methods have been used but they
have high computation costs. To overcome this problem we extract rules from
Bayesian network using genetic algorithm. Then we generate the graphical chain
by mutually matching the extracted rules and Bayesian network. This graphical
chain could shows the sequence of events that lead to the target which could
help the decision making process. The experimental results on small networks
show that the proposed method has comparable results with brute force method
which has a significantly higher computation cost.
