1. School of Software, Nanyang Normal University,Nanyang Henan 473061,China
2. College of Computer Science and Technology, Beijing University of Technology, Beijing 100124,China
Abstract:Bayesian network is one of the most important theoretical models for the representation and reasoning of uncertainty. At present, its structure learning has become a focus of study. In this paper, a Bayesian network structure learning algorithm was developed, which was based on topological order and quantum genetic algorithm. With the richness of the quantum information and the parallelism of quantum computation, this paper designed generator strategy of topological order based on a quantum chromosome to improve not only the efficiency of search, but also the quality of Bayesian network structure. And then by using self-adaptive quantum mutation strategy with upper-lower limit, the diversity of the population was increased, so that the search performance of the new algorithm was improved. Compared to some existing algorithms, the experimental results show that the new algorithm not only searches higher quality Bayesian structure, but also has a quicker convergence rate.
FAULKNER E. K2GA: Heuristically guided evolution of Bayesian network structures from data[C]// Proceedings of the 2007 IEEE Symposium on Computational Intelligence and Data Mining.Washington, DC:IEEE Computer Society,2007:18-25.
[3]
LARRANAGE P, POZA M, UURRAMENDI Y,et al.Structure learning of Bayesian networks by genetic algorithms:A performance analysis of control parameters[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence,1996,18(9):912-925.
HAN K H,KIM J H.Quantum-inspired evolutionary algorithm for a class of combinatorial optimization[J].IEEE Transactions on Evolutionary Computation, 2002, 6(6):580-593.
[7]
PLATELT M D, SCHLIEBS S, KASABOV N. A versatile quantum-inspired evolutionary algorithm[C] // IEEE Congress on Evolutionary Computation. Piscataway:IEEE,2007: 423-430.
[8]
TALBI H, DRAA A, BATOUCHE M. A new quantum-inspired genetic algorithm for solving the travelling salesman problem[C]// Proceedings of IEEE International Conference on Industrial Technology. Piscataway:IEEE, 2004: 1192-1197.
KE M, HONG G, ZHAO Y D,et al. Quantum-inspired particle swarm optimization for vale-point economic load dispatch[J].IEEE Transactions on Power Systems, 2010, 25(1):215-222.