Study of BP neural network based on MECA

This paper designs BP neural network with mind evolution clone algorithm (MECA). Taking the relation between diversity of mind evolution population and clone mechanism of biology into account, MECA is proposed in the paper. Not only can the algorithm converge to globally optimal solution, but also it solves premature convergence problem efficiently. The algorithm has been applied to training XOR. Simulation results show that MECA presented in this thesis performs better in contrast with simple genetic algorithm and BP algorithm. There is a great improvement in the quality and efficiency of the training of neural network.