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    基于神经网络的股市预测

    STOCK PREDICTION BASED ON NEURAL NETWORK

    • 摘要: 本文讨论了有关神经网络用于股市预测方面的问题,包括股市原始数据的预处理、训练样本的确定。提出了适合于描述股市动态特性和时序特性的网络模型及学习算法,并对上海股市作了实际的预测。实验结果表明本文提出的方法是可行的和有效的。

       

      Abstract: in this paperl problems about stock prediction based on neural network arediscussed, which include original stock data pre-processing and training-set determining. A neural network model , that can describe the dynamic and time sequence characteristics of a stock market, and the modified training algorithm are proposed. Results ofprediction experiments with real data of Shanghai stock market prove the efficiency ofour method for its high accuracy.

       

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