An improved nearest neighbor clustering algorithm for RBF(Radial basis function) neural network is presented and applied to the prediction of stock market.
提出了一种改进的 RBF (Radial Basis Functions,径向基函数 )神经网络最近邻聚类学习算法 ,并将其应用于股市预测问题。
参考来源 - 改进的神经网络最近邻聚类学习算法及其应用·2,447,543篇论文数据，部分数据来源于NoteExpress
It is shown that the rough network is accurate and available for prediction of stock market.
计算结果表明，粗神经网络用于股市预测是可行的，结果也较准确。
The prediction of stock market based on the artificial neural network has almost the same precision as that based on time series models.
通过人工神经网络得到的预测结果基本上与较传统的时间序列理论得到的预测结果精度相似。
Set up one time door limit prediction model of autoregression of array, study for nonlinearity of stock market this front field make new try a bit.
建立了一个时间序列的门限自回归的预测模型，为股票市场的非线性研究这一前沿领域作了一点新的尝试。
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