| 基于粗集理论与神经网络技术规则提取的研究 |
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| 引用本文： | 郑寒英 游自英 刘大中. 基于粗集理论与神经网络技术规则提取的研究[J]. 微机发展, 2003, 13(Z2): 43-45 |
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| 作者姓名： | 郑寒英 游自英 刘大中 |
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| 作者单位： | 河北大学数学与计算机学院，河北大学数学与计算机学院，河北大学数学与计算机学院 河北 保定 071002，河北 保定 071002，河北 保定 071002 |
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| 摘 要： | 为了从大量数据中获取有用的知识,提出了基于粗集与神经网络技术的数据挖掘方法。首先利用粗集理论消除冗余的属性,得到数据集的一些规则,然后利用这些规则构造神经网络,利用神经网络技术完善粗糙规则。文章就这一技术的研究方法作了综述,并提出了改进的粗集约简方法.
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| 关 键 词： | 粗集 神经网络 规则提取 数据挖掘 |
| 文章编号： | 1005-3751(2003)0043-03 |
| 修稿时间： | 2003-04-08 |
Rules Extraction Based on Neural Networks and Rough Set Theory:A Survey |
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| ZHENG Han-ying,YOU Zi-ying,LIU Da-zhong. Rules Extraction Based on Neural Networks and Rough Set Theory:A Survey[J]. Microcomputer Development, 2003, 13(Z2): 43-45 |
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| Authors: | ZHENG Han-ying YOU Zi-ying LIU Da-zhong |
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| Abstract: | In order to obtain useful knowledge from large database, an approach to data mining which integrates neural network and rough sets is presented. Present rough set to remove the redundant attribute and acquire a set of rough rule. Then the structure and model are designed according to these rules,and mend original rough rules. Here summarizes this theory, and presents an improved algorithm of attribute reduction . Finally, the paper puts forward a few of open question to be solved in the future studies. |
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| Keywords: | rough set neural network rules extraction data mining |
| 本文献已被 CNKI 等数据库收录！ |
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