Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (27): 224-226.DOI: 10.3778/j.issn.1002-8331.2010.27.063

• 工程与应用 • Previous Articles     Next Articles

Application of wavelet neural network in prediction of gold price

ZHANG Kun1,YU Yong2,LI Tong2   

  1. 1.Department of Mathematics,Chuxiong Normal University,Chuxiong,Yunnan 675000,China
    2.School of Software,Yunnan University,Kunming 650091,China
  • Received:2009-02-27 Revised:2009-04-28 Online:2010-09-21 Published:2010-09-21
  • Contact: ZHANG Kun


张 坤1,郁 湧2,李 彤2   

  1. 1.楚雄师范学院 数学系,云南 楚雄 675000
    2.云南大学 软件学院,昆明 650091
  • 通讯作者: 张 坤

Abstract: According to the research on the main influencing factors of gold price,this paper proposes a prediction model of gold price based on wavelet neural network.Besides,detail learning algorithm is presented and used in the prediction of gold price.To validate effectiveness of the model,the test data are input separately wavelet neural network and BP neural network.By comparative test,higher precision and speed are achieved by using the model based on wavelet neural network.

摘要: 通过对影响黄金价格变动的主要因素的研究,提出一种基于小波神经网络的黄金价格预测模型。给出了具体的网络学习算法,并结合算法对黄金价格进行预测。为验证模型有效性,进行了对比测试。分析结果表明,小波神经网络模型比传统的BP神经网络模型具有收敛速度快、预测精度高的特点。

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