基于变量选择-神经网络模型的复杂路网短时交通流预测

被引：11

作者：

蒋士正

许榕

陈启美

机构：

[1] 南京大学电子科学与工程学院

来源：

上海交通大学学报 | 2015年 / 49卷 / 02期

关键词：

短时交通流预测; 最小绝对收缩和选择算子; 变量选择; 神经网络;

D O I：

10.16183/j.cnki.jsjtu.2015.02.024

中图分类号：

U491.14 [];

学科分类号：

082302 ; 082303 ;

摘要：

针对传统交通流预测模型正在由单断面历史数据处理向多断面、多时刻历史数据处理转变,但在考虑各断面间的影响时,多变的交通状况往往会使预测模型复杂化的问题,引入一种多元线性回归最小绝对收缩和选择算子方法(Lasso),并利用其优秀的变量选择能力,在复杂路网多断面中选出相关性较高的断面;结合神经网络(NN)的非线性特性,提出了Lasso-NN组合模型.结果表明:Lasso-NN模型在路网交叉口对未来15min交通流数据预测的误差率低于9.2%;在非交叉口的误差率低于6.7%,总体优于各自单独使用得出的结果.

引用

页码：281 / 286

页数：6

共 11 条

[1] 一种星形神经网络的混沌同步 [J].

张文龙 ;

于洪洁 .

上海交通大学学报, 2013, 47 (02) :220-225

[2] 短时交通流预测模型综述 [J].

王进 ;

史其信 .

中国公共安全(学术卷), 2005, (01) :92-98

[3]

Short-term traffic forecasting: Where we are and where we’re going[J] . Eleni I. Vlahogianni,Matthew G. Karlaftis,John C. Golias.Transportation Research Part C . 2014

[4] Network-Scale Traffic Modeling and Forecasting with Graphical Lasso and Neural Networks [J].

Sun, Shiliang ;

Huang, Rongqing ;

Gao, Ya .

JOURNAL OF TRANSPORTATION ENGINEERING, 2012, 138 (11) :1358-1367

[5] Real-time road traffic forecasting using regime-switching space-time models and adaptive LASSO [J].

Kamarianakis, Yiannis ;

Shen, Wei ;

Wynter, Laura .

APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, 2012, 28 (04) :297-315

[6]

DALASS: Variable selection in discriminant analysis via the LASSO[J] . Nickolay T. Trendafilov,Ian T. Jolliffe.Computational Statistics and Data Analysis . 2007 (8)

[7] Sparse principal component analysis [J].

Zou, Hui ;

Hastie, Trevor ;

Tibshirani, Robert .

JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS, 2006, 15 (02) :265-286

[8]

Regularization and variable selection via the elastic net[J] . HuiZou,TrevorHastie.Journal of the Royal Statistical Society: Series B (Statistical Methodology) . 2005 (2)

[9]

Least Angle Regression[J] . Bradley Efron,Trevor Hastie,Iain Johnstone,Robert Tibshirani.The Annals of Statistics . 2004 (2)

[10]

Neural Networks in Civil Engineering: 1989–2000[J] . HojjatAdeli.Computer‐Aided Civil and Infrastructure Engineering . 2002 (2)

← 1 2 →