Forecasting model of exchange rate based on chaotic time series and RBF neural network

被引：0

作者：

Zhao Jianna ^{[1
]}

Wang Xinying ^{[1
]}

Wu Zhuozheng ^{[1
]}

机构：

[1] N China Elect Power Univ, Sch Business Adm, Baoding, Peoples R China

来源：

PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON RISK MANAGEMENT & ENGINEERING MANAGEMENT, VOLS 1 AND 2 | 2008年

关键词：

chaos; chaotic time series; RBF neural network; exchange rate forecast;

D O I：

暂无

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

In order to forecast exchange rate more accuracy, a hybrid intelligent system is applied to improve the precision of forecasting, which combine with the chaos theory and RBF neural networks, this paper presents a RBF neural networks model based on chaotic analysis in the phase space. At first, we Use attractor of Chaos Theory phase-space reconstruction, then use RBF neural network to simulate the evaluation of spatial attractor. The effectiveness of our forecasting model was verified by experiment data.

引用

页码：521 / 524

页数：4