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The Application of RBF Neural Networks to Stock Price Forecasting

JIANG Yi 1, LIN Yong-peng 2 (Department of Computer Science, Xiamen University,Xiamen 361005,China)  
In this paper, a stock price forecasting model based on RBF (Radial Basis Function) neural network was presented. The model was developed by combining the Clustering Algorithms to search for the network centers width the Gradient Descent Algorithms to adjust the network weight. Aim to enhance the adaptive capacity of the RBF network; some improvement was made against the highly nonlinear characteristics of stock price. Then, selected stock prices trend was forecasted using the model and approving results were achieved.
【CateGory Index】: F830.9;F224
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