模糊组合神经网络智能选股模型的建立

针对传统的股票市场预测模型,为了准确地预测股票价格趋势、为广大投资者规避风险,应用模糊逻辑和组合神经网络,利用贝叶斯统计学与组合理论使二者有机结合,提出一种股票市场建模及预测方法。组合神经网络结合BP网络和径向基函数网络(RBF),神经元模糊系统有更强的学习和推理机制,能避免黑箱问题。实证研究结果表明,该方法有较高的预测精度和更好的稳定性。

Intelligent Stock Choosing Model Based on Fuzzy Combined Neural Network

According to traditional forecasting methods of stock market,stock market modeling and forecasting is proposed using Bayesian statistics and combined principle and adopting fuzzy logic and combined neural network to forecast stock price trend and avoid venture.Combined neural network includes Back-Propagation and radial basis function neural networks.Fuzzy neural networks have stronger information managing ability and can avoid the black-boxproblem.The concrete research results show its predicting veracity and better stability.