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。
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.
出处
《软科学》
CSSCI
北大核心
2010年第10期127-130,共4页
Soft Science
基金
国家社会科学基金资助项目(08BJY154)
教育部新世纪人才项目(NCET-07-0905)
关键词
BP神经网络
ROUGH集
属性简约
大非减持度预测
BP neural network
rough set
attribute reduction
subtraction degree forecast of large-scale non-circulation
