The performance of artificial neural network (ANN) is very sensitive to its structure and training method. Therefore, an adaptive structure ANN and its training method are proposed. The ANN model is with double-net structure and trained by early stopping, which reduces the sensitivity of model performance to structure. The ANN structure is proposed to be adjusted dynamically according to the information of data noise and model error, which further improves the model
performance with relatively high time efficiency. Simulation results show that the proposed methods can make up some defects of traditional methods such as early stopping, and has better performance.