基于遗传算法的模糊神经网络股市建模与预测

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上这种具有一定程度不确定性的非互性的建模与预测方面有很发的价值。

STOCK MARKET MODELING AND FORECASTING BY USING FUZZY NEURAL NETWORK BASED ON GENETIC ALGORITHM

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.