关键词: 粗糙集理论, 属性约简, RBF神经网络, 遗传算法, 股票预测

Abstract: Against the difficulties that the neural network encountered in the stock prediction，the rough set theory is introduced to the prediction model，and a new prediction method based on the combination of rough set and neural network is proposed.According to its weakness，the basic genetic algorithm is improved.Firstly，the attribute reduction method based on the genetic algorithm is introduced，and the genetic factors are improved.Then，adopt an attribute reduction method based on improved genetic algorithm to reduce the sample data of the model，delete the redundant data，and obtain the smallest reduction of the sample inputs.At last，the reduced samples are used to train and test the prediction model.The experimental result indicates that this method has high prediction accuracy，and can solve the problems of complex network structure and studying slowly and effectively.

Key words: rough set theory, attribute reduction, Radial Basis Function（RBF） neural network, genetic algorithm, stock prediction