Abstract: In this paper, the learning issue for artificial neural network is studied in several different aspects such as connection weight, network architecture, learning parameters and active function of unit. Some adaptive algorithms are proposed for the back propagation learning （BP）, which is well known in the artificial neural network literature. The experiments show that they have good effect on increasing learning speed and training network architecture.