| 基于rough集与BP神经网络的大非减持度预测研究 |
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| 引用本文： | 曹国华,赵晰,尹林林.基于rough集与BP神经网络的大非减持度预测研究[J].软科学,2010,24(10). |
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| 作者姓名： | 曹国华 赵晰 尹林林 |
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| 基金项目： | 国家社会科学基金资助项目，教育部新世纪人才项目 |
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| 摘 要： | 以深交所大非股东为研究对象,将BP神经网络结合rough集理论应用于大非减持度预测,构建一套减持度预测系统,测试结果表明该预测系统平均预测准确度较高,具有实用性,能够为普通投资者及监管者提供参考作用。
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| 关 键 词： | BP神经网络 rough集 属性简约 大非减持度预测 |
Research on Subtraction Degree Forecast of Large-scale Non-circulation Based on Rough Sets and BP Neural Network |
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| CAO Guo-hua,ZHAO Xi,YIN Lin-lin.Research on Subtraction Degree Forecast of Large-scale Non-circulation Based on Rough Sets and BP Neural Network[J].Soft Science,2010,24(10). |
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| Authors: | CAO Guo-hua ZHAO Xi YIN Lin-lin |
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| Abstract: | The article takes the large-scale non-circulation in Shenzhen stock market as research example,applying BP neural network and rough set theory to building a prediction system for subtraction degree of large-scale non-circulation.The results show that the system has a high-average accuracy and high practicality,which can provide a reference for ordinary investors and regulators. |
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| Keywords: | BP neural network rough set attribute reduction subtraction degree forecast of large-scale non-circulation |
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