Combined prediction research of city traffic flow based on genetic algorithm

被引：0

作者：

Song Yuecong ^{[1
]}

Hu Wei ^{[1
]}

Bi Guotong ^{[2
]}

机构：

[1] Mianyang Normal Univ, Dept Comp Sci & Engn, Mianyang 621000, Peoples R China

[2] Southwest Univ Sci & Technol, Coll Comp Sci & Technol, Mianyang, Peoples R China

来源：

ICEMI 2007: PROCEEDINGS OF 2007 8TH INTERNATIONAL CONFERENCE ON ELECTRONIC MEASUREMENT & INSTRUMENTS, VOL III | 2007年

关键词：

genetic algorithm; traffic flow; combined prediction; forecast; intelligent transportation system;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Interilligent Transprotation System is the best measure to solve the urban traffic jam in the world, Forecasting urban traffic network is the premise for developing urban intelligent transportation system. In this paper some important forecasting models, including the theory and characteristic,are discussed, and the factors are discussed to influence the forecasting model. In the end combined prediction of city traffic flow based on genetic algorithm is given, using the characteristics of genetic algorithm's colony search,the new algorithm combines all kinds of algorithms, optimizes the prediction way of thinking, fully discovers the advantages of different algorithms, and turns out to be practical and productive.

引用

页码：862 / +

页数：2