摘要
提出一种基于粗糙集理论的股市预测方法.首先选择"收盘价"、"成交量"、"日均线"等指标作为条件属性与决策属性;而后采用RS理论,选择不同的条件属性子集进行约简和属性重要度排序,并由此提取出股市的预测规则.结果表明,该方法不需要任何前提假设,而且可以根据不同的参考指标,形成不同的预测规则集.
A method to predict the trend of stocking is proposed based on rough set（RS） theory.First,some stocking market indexes,such as ＂close＂,＂total volume＂,＂moving average＂ are chosen as conditional attributions and decision attribution.Then the conditional attributes and their corresponding importance are calculated related to different conditional attributes subsets.Finally,the prediction rules of stocking market are extracted.The results show that the proposed method can extract different prediction rule sets with different reference indexes and without any hypothesis.
出处
《郑州大学学报（理学版）》
CAS
北大核心
2009年第4期40-44,共5页
Journal of Zhengzhou University:Natural Science Edition
关键词
股市走势
预测
粗糙集
知识发现
stocking market
prediction
rough set
knowledge discovery
作者简介
朱永明（1963-），男，副教授，主要从事管理科学与工程系统研究，E—mail：zhym809@sina．com．
