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证券市场预测
相关语句
  stock market prediction
     Neural Network Method for Stock Market Prediction
     证券市场预测的神经网络方法
短句来源
     Application Research on Stock Market Prediction Based on GA Neural Network
     GA神经网络在证券市场预测中的应用研究
短句来源
     Then, We creatively make use of the nonlinear reflection ability and association learning ability of arti ficial neural network, and propose a general model of the stock market prediction.
     然后运用神经网络模型的非线性映射能力和学习联想能力,提出了证券市场预测的通用模型。
短句来源
  “证券市场预测”译为未确定词的双语例句
     The Prediction of Security Market based on Trend Smoothing and GARCH
     基于趋势平滑和GARCH的证券市场预测
短句来源
     Financial prediction based on BP neural network
     BP神经网络在证券市场预测中的应用
     ④according to the theory of “pattern reappearance” of stock technical analysis, we establish stock market forecasting models for forecasting “buying opportunity” based on classified wavelet networks.
     ④基于分类小波网络,并根据证券技术分析的“模式重现”原理,建立综合指数“买入时机”预测的分类小波网络证券市场预测模型。
短句来源
     This paper considers the problem of financial prediction based on BP neural networks.
     本文研究基于BP神经网络的证券市场预测问题。
  相似匹配句对
     Neural Network Method for Stock Market Prediction
     证券市场预测的神经网络方法
短句来源
     AN ANALYSIS ON APPLICATION OF NEURO-NETWORK IN SCURITY PREDICTION
     证券市场的神经网络预测应用分析
短句来源
     PREDICTIONS OF THE EARTH ROTATION PARAMETERS
     地球自转参数预测
短句来源
     The prediction of the rock burst
     冲击地压的预测
短句来源
     INDIA'S STOCK MARKET
     印度的证券市场
短句来源
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  stock market prediction
Stock market prediction using artificial neural networks with optimal feature transformation
      
In this study, the GA is incorporated to improve the learning and generalizability of ANNs for stock market prediction.
      
Experimental results show that the proposed approach reduces the dimensionality of the feature space and decreases irrelevant factors for stock market prediction.
      
Stock market prediction is attractive and challenging.
      
A stock market prediction example is used to show that making a large fuzzy tree is an attractive alternative to pruning.
      
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In this paper, we first discuss each of the affecting factors, prediction analysis method and the selection of the quantitative prediction models of stock markets.Then, We creatively make use of the nonlinear reflection ability and association learning ability of arti ficial neural network, and propose a general model of the stock market prediction.Finally, through a real prediction example of buying opportunity, we verify that our model is effective.

首先讨论了证券市场的各种影响因素、预测分析方法和定量预测模型的选择。然后运用神经网络模型的非线性映射能力和学习联想能力,提出了证券市场预测的通用模型。最后通过一个证券买入时机预测的实例,证明了该模型的有效性

Security market prediction is an important part of Behavior Finance. This paper is aimed to analyze and classify the present studies of the application of neuro-network in security market prediction. It brings forth the methods adopted in the construction of prediction model.

证券市场不仅包含了分形运动和随机运动 ,也包含了趋势运动和周期运动。因此 ,证券市场是可以预测的。近年来 ,人们运用非线性时间序列中的自回归条件异方差模型 (ARCH)与广义自回归条件异方差模型 (GARCH)等模型来描述股价的变动特征 ,国际间的主要资本市场的股价波动与主要的货币现期及远期汇率均可由这些模型进行有效的解释。神经网络是人类大脑的一种高度简化的抽象 ,它是一个解决复杂问题的强大工具 ,在证券市场的预测问题上已显示出较高的价值。

>=This paper considers the problem of financial prediction based on BP neural networks. By analyzing the factors that affect stock values, two groups of variables are chosen as the input of the neural network. Furthermore, this paper provides a new prediction method, termed as two-steps-prediction method, to improve the predicting precision. It is seen that the new prediction method includes the simulating step and the predicting step, and the predicting errors of the former are used to adjust the output of...

>=This paper considers the problem of financial prediction based on BP neural networks. By analyzing the factors that affect stock values, two groups of variables are chosen as the input of the neural network. Furthermore, this paper provides a new prediction method, termed as two-steps-prediction method, to improve the predicting precision. It is seen that the new prediction method includes the simulating step and the predicting step, and the predicting errors of the former are used to adjust the output of the latter. Finally, some simulations illustrate the applicability of the present method

本文研究基于BP神经网络的证券市场预测问题。通过分析影响股价变动的各种因素,选取了两组变量作为神经网络的输入。为了提高神经网络的预测精度,本文提出了一种两阶段预测法,包括模拟预测阶段和实际预测阶段,其中,模拟预测阶段的预测误差作为实际预测阶段的调整量。仿真结果显示,这种新的神经网络预测方法具有较好的预测效果。

 
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