The advantage of artificial neural network and wavelet analysis are integrated through replacing the traditional S-shaped activation function with the wavelet function. One method of chaotic prediction based on wavelet BP network was put forward based on the reconstruction of state space. Training data construction and networks structure are determined by chaotic phase space, and nonlinear relationship of phase points was established by BP neural networks. As an example, the new method was applied on short term forecasting of monthly precipitation time series of Sanjiang Plain with chaotic characteristics. The results showed so higher precision of the method had that the theoretical evidence would be provided for applying the chaos theory to study the variable law of monthly precipitation.
