给出了一种基于数据挖掘中的RBF人工神经网络的股票价格预测方法。RBF神经网络具备了可以逼近任何非线性连续函数的能力,可通过神经元连接权值的调整,更准确地逼近股票市场价格波动中反映出来的非线性映射关系,从而实现对股市价格的短期预测。阐述了RBF神经网络的结构及工作原理、股票价格的预测原理和方法,可以较为准确地指导人们进行股票投资。 A stock price forecast method based on RBF artificial neural network in data mining is given. RBF neural network possesses the ability of approximating any non-linear continuous function. By adjusting the weight of neuron connection, RBF neural network can more accurately approach the nonlinear mapping reflected in the stock market price fluctuation, so as to realize the short-term forecast of the stock market price . This paper describes the structure and working principle of RBF neural network, the forecasting principle and method of stock price, which can guide people to stock investment more accurately.