【摘要】 提出一种基于模糊神经网络的股票市场建模与预测方法，并采用遗传算法训练网络权值及模糊子集的划分．对于上证指数及个股（上海石化）的建模与预测结果表明，该方法具有很强的学习与泛化能力，在处理诸如股票市场这种具有一定程度不确定性的非线性系统的建模与预测方面有很好的应用价值更多还原

【Abstract】 This paper presents a method for stock market modeling and forecasting based on fuzzy neural network, genetic algorithm is used to learn the connection weights of the fuzzy neural network and partitions of fuzzy subsets. It has been shown by the modeling and forecasting results about Shanghai stock market price index and a company stock price that the method has reinforcement learning properties and mapping capabilities. With respect to modeling and forecasting of nonlinear system which has some uncertainties,the method is available.更多还原