关键词: BP网络, 过拟合, 模糊熵

Abstract: Due to their simple topological structure and universal approximation ability，Backpropagation（BP） neural networks have been widely used in prediction and nonlinear system modeling.But some kinds of problems may happen because of the deficiency of the algorithm itself.Therefore，the optimization of neural network has become an important research topic.In order to improve generalization of neural networks，the fuzzy entropy is added to the backpropagation neural networks and the BP neural network based on fuzzy entropy is proposed.The two algorithms are compared in the experiments and the results prove that the improved algorithm can effectively improve the test accuracy and avoid over-fitting.

Key words: backpropagation neural networks, over-fitting, fuzzy entropy