DocumentCode
1733105
Title
Combined Prediction Research of City Traffic Flow Based On Genetic Algorithm
Author
Yuecong, Song ; Wei, Hu ; Guotang, Bi
Author_Institution
Mianyang Normal Univ., Mianyang
fYear
2007
Abstract
Intelligent transportation 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.
Keywords
forecasting theory; genetic algorithms; road traffic; search problems; city traffic flow; colony search; combined prediction research; forecasting models; genetic algorithm; intelligent transportation system; urban traffic jam; urban traffic network; Cities and towns; Communication system traffic control; Demand forecasting; Genetic algorithms; Intelligent transportation systems; Neural networks; Predictive models; Technology forecasting; Telecommunication traffic; Traffic control; Forecast; Intelligent Transportation System; combined prediction; genetic algorithm; traffic flow;
fLanguage
English
Publisher
ieee
Conference_Titel
Electronic Measurement and Instruments, 2007. ICEMI '07. 8th International Conference on
Conference_Location
Xi´an
Print_ISBN
978-1-4244-1136-8
Electronic_ISBN
978-1-4244-1136-8
Type
conf
DOI
10.1109/ICEMI.2007.4351054
Filename
4351054
Link To Document