Modelling non-linear time series using neural networks

被引：0

作者：

Zorin, A ^{[1
]}

机构：

[1] Riga Tech Univ, Decis Support Syst Grp, Riga, Latvia

来源：

SIMPLICITY BEHIND COMPLEXITY | 2004年 / 3卷

关键词：

neural networks; error back-propagation; time series analysis;

D O I：

暂无

中图分类号：

O3 [力学];

学科分类号：

08 ; 0801 ;

摘要：

This paper presents an application of neural networks to non-linear time series modelling. No additional indicators, but only the information contained in the sales time series was used to model and forecast stock exchange index values. The neural network approach proves to give better results when compared to standard methods like Box-Jenkins and exponential smoothing.

引用

页码：269 / 275

页数：7

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