The use of LS-SVM for short-term passenger flow prediction / Mažiausių kvadratų atraminių vektorių metodo taikymas trumpalaikiam keleivių srautui prognozuoti /

The use of LS-SVM for short-term passenger flow prediction / Mažiausių kvadratų atraminių vektorių metodo taikymas trumpalaikiam keleivių srautui prognozuoti /

Transit flow is the basement of transit planning and scheduling. The paper presents a new transit flow prediction model based on Least Squares Support Vector Machine (LS-SVM). With reference to the theory of Support Vector Machine and Genetic Algorithm, a new short-term passenger flow prediction mo...

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Bibliographic Details
Main Authors: Qian Chen, Wenquan Li, Jinhuan Zhao
Format: Article
Language:English
Published: Vilnius Gediminas Technical University 2011-04-01
Series:Transport
Subjects:
short-term passenger flow prediction
least squares support vector machine
genetic algorithm
Online Access:https://www.tede.vgtu.lt/index.php/Transport/article/view/5541

Internet

https://www.tede.vgtu.lt/index.php/Transport/article/view/5541

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