#$%^&*AU2018101512A420181115.pdf#####ABSTRACT A stock trend predicting method with social economic features based on neural networks is disclosed.Stock movement prediction is crucial to stock market analysis. The accuracy of existing methods may not achieve investors increasing requirements to predict the stock market. This invention provides a new method to predict the stock moving trend. It provides users with a valid reference to have a prediction to the stock movement. In this invention, we use Gated Recurrent Unit (GRU), Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN) which belong to Artificial Neural Network (ANN) as main computing methods and blend in stock-related information factors and the social economic features. This invention provides investors with a clear reference on whether the investment will make profits in the next five days.reaeJeoo i 4 nf rnai nf a u e dat prfmesn EI Figure I
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机译：＃$％^＆* AU2018101512A420181115.pdf #####抽象基于社会经济特征的股票趋势预测方法披露了神经网络。股票走势预测对于股票市场分析。现有方法的准确性可能无法达到投资者对预测股市的要求越来越高。这个本发明提供了一种预测库存趋势的新方法。它为用户提供有效参考，以对股票进行预测运动。在本发明中，我们使用门控循环单元（GRU）短期记忆（LSTM）和卷积神经网络（CNN）属于人工神经网络（ANN）的主要计算方法以及与股票相关的信息因素和社会因素的融合经济特征。本发明为投资者提供了清晰的有关投资在未来五年是否会盈利的参考天。丽珠我4 nf rnai n a u etprfmesnEI图一
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