The complexity of inside structure and levity of exterior complication in system of stock market make stock market prediction a complex problem. The traditional methods and tools have not met its needs.
但是股价系统内部结构的复杂性、外部因素的多变性决定了股市预测这项任务的艰巨性,而传统的预测工具已不能满足这种需要。
参考来源 - 神经网络方法在股市预测中的应用研究Thus we do some research on the factors that influence the stock price and put forward a specific stock market forecasting model.
对影响股票价格的各种因素进行分析后,提出了具体的股市预测模型。
参考来源 - 基于复制理论的股市预测The following works have been done in this thesis:1. Several applications of the neural networks in the stock market prediction have been summarized.2.
本文的工作主要有以下几个方面： 1．概括总结了神经网络在股市预测模型中的应用。
参考来源 - 神经网络在股市预测中的建模及应用An improved nearest neighbor clustering algorithm for RBF(Radial basis function) neural network is presented and applied to the prediction of stock market.
提出了一种改进的 RBF (Radial Basis Functions,径向基函数 )神经网络最近邻聚类学习算法 ,并将其应用于股市预测问题。
参考来源 - 改进的神经网络最近邻聚类学习算法及其应用·2,447,543篇论文数据，部分数据来源于NoteExpress
概括总结了神经网络在股市预测模型中的应用。
Several applications of the neural networks in the stock market prediction have been summarized.
因此，股市预测方法的研究具有极其重要的应用价值和理论意义。
Therefore the study of stock prediction method has great application value and theoretical significance.
计算结果表明，粗神经网络用于股市预测是可行的，结果也较准确。
It is shown that the rough network is accurate and available for prediction of stock market.
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