Research on the Early Warning Model Based on the Fuzzy Rough Set and BP Neural Network

In this paper, a method of complement of fuzzy rough set and BP neural network was proposed, and an early warning model of electronic information products on Technical Barriers to Trade (TBT) was given by the method. The attribute reduction for indicators of early warning based on fuzzy rough set can not only enhance the veracity of attribute reduction, but also improve the accuracy of the training of BP neural network through reducing the input dimension of BP neural network at the same time. The new TBT early warning model of electronic information products was proved more feasible and effective.