Construction decision support system by using Bayesian network’s theory for modeling behavior of complex systems
Developed some of methods for solving ill-structed problems for modeling, prediction and classification. All methods use Bayesian networks. Proposed a new five step method for finding the parameters of Bayesian networks with hidden nodes. Method bases on an expectation maximization algorithm. Suggested Pearson's, Chuprov's, Cramer's, Goodman's and mutual information coefficients for finding interconnections between Bayesian network's nodes. For solving the problem of modeling the behavior of complex systems proposed original method for construction and application hybrid Bayesian networks.