Based on BP neural network discrete data forecast

Artificial neural network is based on human brain structure and operational mechanism based on knowledge and understanding of its structure and behavior of simulated an engineering system. BP artificial neural network is an important component of neural networks, as it can on the linear or nonlinear multivariable without preconditions in the case of statistical analysis, with the traditional statistical methods, analysis of the variables need to be consistent with certain conditions compared to its own advantage. The BP neural network does not need the precise mathematical model, does not have any supposition request to the material itself. Its processing non-linear problem's. ability is stronger than traditional statistical methods. This article uses two groups of data to establish the BP neural network model separately, and carries on the comparison to the model fitting ability and the forecast performance, discovered BP neural network when data distribution relative centralism fits ability, forecasts the stable property. But the predictive ability is unable in the discrete data application to achieve anticipated ideally.