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and it belongs to scientific edge science of the artificial intelligence and system Engineering. As a kind of nonlinear dynamic system of large-scale parallel processing, artificial neural networks in recent years in the economic analysis, optimization and forecast fields is applied and achieves good results including the back-propagation neural network referred to as the BP neural network, and the feedforward neural network  that are the most widely used in neural network models. The BP neural network is a one-way transmission network of multilayer feedforward, and it is already very mature whether in theory or network performance. And its advantage is strong nonlinear mapping capability and flexible network structure. But it has the disadvantages of local optimal, low training speed and low efficiency, and to some extent, it limits the scope of application. In feedforward Neural network the most commonly used network model is RBF neural network which is mainly used to solve pattern classification and function approximation. In mathematics, the RBF neural network may solve the low-dimensional space difficult problems in typical high-dimensional data space. It takes a radial basis function as the activation function, and it has fast convergence and high accuracy, small network scale   characteristics. The approximation ability, classification ability and learning speed of radial basis function (RBF) network is better than BP network. So this paper uses the RBF network model for prediction of RMB exchange rate.
To the complex problem of RMB exchange rate, according to the complicated nonlinear relation between RMB exchange rate and inflation rate, GDP, an international payment of rate and interest rate, and nonlinear characteristics of RMB exchange rate data, with SPSS17.0 software, with RBF neural network technology as the main tools, the paper researches the RMB exchange rate fluctuations and development trend. Based on the relationship between RMB exchange rate and the factors of inflation rate, GDP, an international payment of rate and interest rate, it establishes the RBF network model to predict RMB exchange rate, and verify the effectiveness of the prediction value with correlation analysis.

 

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