Predicting chaotic time series using recurrent neural network

被引：117

作者：

Zhang, JS ^{[1
]}

Xiao, XC ^{[1
]}

机构：

[1] Univ Elect Sci & Technol China, Dept Elect Engn, Chengdu 610054, Peoples R China

来源：

CHINESE PHYSICS LETTERS | 2000年 / 17卷 / 02期

关键词：

Time series - Forecasting;

D O I：

10.1088/0256-307X/17/2/004

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

A new proposed method, i.e. the recurrent neural network (RNN), is introduced to predict chaotic time series, The effectiveness of using RNN for making one-step and multi-step predictions is tested based an remarkable few datum points by computer-generated chaotic time series. Numerical results show that the RNN proposed here is a very powerful tool for making prediction of chaotic time series.

引用

页码：88 / 90

页数：3

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