%0 Journal Article
%T Method of the Wavelet Neural Network in the Prediction of Stock Market<br>股市预测中的小波神经网络方法
%A YAO Hong-xing
%A {
%A }
%A SHENG Zhao-han
%A CHEN Hong-xiang
%A <br>姚洪兴
%A 盛昭瀚
%A 陈洪香
%J 系统工程理论与实践
%D 2002
%I 
%X This paper briefly discusses apparent randomness in stock market time serials first; it may be due to chaotic behavior of a nonlinear but deterministic system. It is possible to make short-term prediction by using the determinism. This is done by making full use of the advantages of wavelet transform time-frequency localization, the paper proposed an improved wavelet network structure, and considered the model for stock market prediction. It can be seen from the example that this method can effectively improve the prediction accuracy, the intrinsic defects of artificial neural network and exponent auto-regression are avoided.
%K stock market prediction
%K wavelet neural network
%K chaos
%K phase space reconstruction<br>股市预测
%K 小波神经网络
%K 混沌
%K 相空间重构
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=01BA20E8BA813E1908F3698710BBFEFEE816345F465FEBA5&cid=962324E222C1AC1D&jid=1D057D9E7CAD6BEE9FA97306E08E48D3&aid=B445A5FE4401D87A&yid=C3ACC247184A22C1&vid=BC12EA701C895178&iid=B31275AF3241DB2D&sid=27746BCEEE58E9DC&eid=16D8618C6164A3ED&journal_id=1000-6788&journal_name=系统工程理论与实践&referenced_num=14&reference_num=9