%0 Journal Article
%T The Forecasting Approach for Short-term Traffic Flow based on Principal Component Analysis and Combined NN<br>基于主成分分析和组合神经网络的短时交通流预测方法
%A ZHANG Xiao-li
%A HE Guo-guang
%A <br>张晓利
%A 贺国光
%J 系统工程理论与实践
%D 2007
%I 
%X A combination approach based on Principal Component Analysis(PCA) and combined NN is presented for short-term traffic flow forecasting.The historical data of the traffic flows of the forecasted road and interrelated roads have been processed by Principal Component Analysis.The results of PCA are input data for combined NN.It not only reduces the number of input variables and the size of NN,but also reserves the main information of original variables and irrelevance among variables.An example for explanation of validity is given.The forecast results show that this approach is better than the typical BP NN with the same data.
%K forecasting
%K short-term traffic flow
%K principal component analysis
%K combined NN<br>预测
%K 短时交通流
%K 主成分分析
%K 组合神经网络
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=01BA20E8BA813E1908F3698710BBFEFEE816345F465FEBA5&cid=962324E222C1AC1D&jid=1D057D9E7CAD6BEE9FA97306E08E48D3&aid=FC6F5C4FBA7C12E8&yid=A732AF04DDA03BB3&vid=DB817633AA4F79B9&iid=5D311CA918CA9A03&sid=ED01F5AE50BE09C0&eid=73579BC9CFB2D787&journal_id=1000-6788&journal_name=系统工程理论与实践&referenced_num=2&reference_num=9