%0 Journal Article
%T Rough Orthogonal Wavelet Network and Its Applications to the Traffic Flow Forecast<br>粗正交小波网络及其在交通流预测中的应用
%A YANG Li-cai
%A JIA Lei
%A KONG Qing-jie
%A LIN Shu
%A <br>杨立才
%A 贾磊
%A 孔庆杰
%A 林姝
%J 系统工程理论与实践
%D 2005
%I 
%X Based upon the characteristics of traffic flow forecast and the principal component analysis (PCA), a new traffic flow forecasting model combined rough sets and orthogonal wavelet network together, called rough orthogonal wavelet network forecasting model, is put forward. The model has been successfully used to forecast urban traffic flow. Using the principal component analysis about input vectors, the model keeps away from the dimension avalanche of orthogonal wavelet networks. The experiment results show that the model is superior to the BP networks and wavelet frame networks in the aspects of flow forecasting precision and network convergence. The rough neural network forecasting model is robust to the uncertain factors for the traffic flow forecast. The model given in this paper is of academic and practical value in forecasting applications.
%K wavelet network
%K traffic flow forecast
%K rough sets
%K PCA
%K intelligent transportation system<br>小波网络
%K 交通预测
%K 粗集
%K 主成分分析
%K 智能交通系统
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=01BA20E8BA813E1908F3698710BBFEFEE816345F465FEBA5&cid=962324E222C1AC1D&jid=1D057D9E7CAD6BEE9FA97306E08E48D3&aid=A26CB8A990F9D2D0&yid=2DD7160C83D0ACED&vid=C5154311167311FE&iid=5D311CA918CA9A03&sid=2F56B21F91C9B05B&eid=28F8B56DB6BEE30E&journal_id=1000-6788&journal_name=系统工程理论与实践&referenced_num=4&reference_num=8