The authors have presented a Hybrid Learning algorithm(HL algorithm) for Bayesian Network structure

which combines EM algorithm

Monte Carlo sampling algorithm and evolutionary algorithm.The HL algorithm uses EM algorithm and Monte Carlo sampling algorithm to convert uncompleted data to completed data and uses evolutionary algorithm to evolve the structure of Bayesian Network

which overcomes the defect of gaining local maximum of the EM algorithm.Since data processing in HL algorithm is based on posterior networks structures and the structures of Bayesian Network are optimized with evolution computing

the HL algorithms are of higher reliability of complementary data

higher learning rate

and better operational performance.