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With the technology development, the need of analyze and extraction of usefulinformation is increasing. Bayesian networks contain knowledge from data andexperts that could be used for decision making processes But they are noteasily understandable thus the rule extraction methods have been used but theyhave high computation costs. To overcome this problem we extract rules fromBayesian network using genetic algorithm. Then we generate the graphical chainby mutually matching the extracted rules and Bayesian network. This graphicalchain could shows the sequence of events that lead to the target which couldhelp the decision making process. The experimental results on small networksshow that the proposed method has comparable results with brute force methodwhich has a significantly higher computation cost.

Generating Graphical Chain by Mutual Matching of Bayesian Network and Extracted Rules of Bayesian Network Using Genetic Algorithm