基于径向基神经网络的股价预测

Stock price prediction based on Radial Basis Function neural network

借助径向基函数(Radial Basis Function)神经网络对非线性函数的逼近能力,对深能源A股价这个时间序列作了连续若干天的一步预测,并与其他预测方法进行了比较. 结果表明,用径向基神经网络预测股价是可行的和有效的.

The nonlinear-functional approximation ability of Radial Basis Function neural network leads us to forecast the time series of Shenzhen Energy A, and the one-step stock-price forecast is undertaken. The results by different methods are compared with respect to their performance on prediction. Results of prediction experiments with real data prove the efficiency of our prediction method based on Radial Basis Function neural network.