文献类型：期刊文章

作　　者：熊伟[1] 孙璐[2] 周洁[3]

机构地区：[1]安徽省交通厅质量监督站,合肥230051 [2]东南大学交通学院,南京210096 [3]北伊利诺斯州大学计算机科学系,dekalb60115

出　　处：《Journal of Southeast University(English Edition)》

基　　金：The US National Science Foundation (No.BCS-0527508)

年　　份：2010

卷　　号：26

期　　号：1

起止页码：122-125

语　　种：中文

收录情况：AJ、CAS、CSA、CSA-PROQEUST、EI(收录号：20102012932862)、IC、INSPEC、JST、MR、SCOPUS、ZMATH、普通刊

摘　　要：In order to develop optimal multi-regime traffic stream models, a new method that integrates cluster analysis and B-spline regression is presented. First, for identifying the proper number of regimes, the K-means and the fuzzy c-means methods are applied in cluster analysis to actual traffic data, which suggests that dividing the traffic flow into two or three clusters can best reflect intrinsic patterns of traffic flows. Such information is then taken as guidance in spline regression, thus significantly reducing the computational burden of estimating spline models. Spline regression is used to estimate the locations of knots and the coefficients of the model so that the global error can be minimized. Model analysis results demonstrate that the proposed spline models have better fitting and generalization capability than the conventional models. In addition, the new method is more flexible in terms of data fitting and can provide smoother traffic stream models.

关 键 词：traffic stream  cluster analysis  spline regression  OPTIMIZATION

分 类 号：U491[物流管理与工程类]