混沌时序重构及上海股票指数预测的应用研究

被引：15

作者：

马军海

齐二石

莫馨

机构：

[1] 天津大学管理学院

[2] 天津大学管理学院天津

[3] 天津

来源：

系统工程理论与实践 | 2003年 / 12期

关键词：

非线性自相关混沌模型; 小波神经网络; 上海证券股票数据; 参数识别; 时序预测;

D O I：

暂无

中图分类号：

F224 [经济数学方法];

学科分类号：

0701 ; 070104 ;

摘要：

应用非线性自相关混沌模型,采用神经网络和小波理论相结合的方法对模型参数进行辨识,其辨识的准确程度较高.通过对混沌时序进行预处理和傅立叶滤波,然后再进行重构和预测工作其效果良好;文章采用该模型对上海证券市场的600062号股票数据的开盘、最高、最低、收盘价数据进行了建模和模型中参数辨识的工作,其预测的结果比较准确.

引用

页码：86 / 94

页数：9

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