摘要
从预测能力的角度采用径向基函数 (radialbasisfunction ,简称RBF)神经网络方法计算我国上海股票市场的分形维数 ,并通过RBF神经网络的实验 ,得到上海股市的最小嵌入维数为 6 ,验证了股市分形维数在 2～ 3之间 ,从而进一步确定了我国上海股票市场是一个具有混沌现象的系统 .最后探讨了利用股票市场的混沌特性进行短期预测的效果和可行性 .
This paper tests the fractal dimension of Shanghai stock market through the neural networks from the point view of forecasting. Through a data experiment of radial basis function neural network, we find that the optimal embedding dimension is 6. As a result the fractal dimension of Shanghai stock market is about in the interval between 2 and 3. Therefore, the stock market is a chaotic system, and we must take the nonlinear analytical instruments. Finally, we discuss the effect and the reliability of the stock prediction based on chaotic characteristic.
出处
《武汉大学学报（理学版）》
CAS
CSCD
北大核心
2003年第3期309-312,共4页
Journal of Wuhan University:Natural Science Edition
基金
国家教育部博士点基金资助项目 ( 0 1JB63 0 0 0 9)
