Title :
Site Selection of Mechanical Parking Garage in High Density Vehicle Urban Area Based on Genetic Algorithm-Support Vector Machine
Author :
Tang, Minan ; Ren, Enen
Author_Institution :
Mechatron. T&R Inst., Lanzhou Jiaotong Univ., Lanzhou, China
fDate :
Nov. 30 2009-Dec. 1 2009
Abstract :
In the study, the novel method based on support vector machine and genetic algorithm (GA-SVM) is applied to site selection of mechanical parking garage in high density vehicle urban area, in which genetic algorithm (GA) dynamically optimizes the values of SVM´s parameters. On the basis of researching the influence factors for site selection of mechanical parking garage, the GA-SVM model in site selection of mechanical parking garage is constructed. Site selection of mechanical parking garage in central district of Lanzhou is used as application case of the proposed GA-SVM model. The experimental results indicate that GA-SVM is effective in site selection of mechanical parking garage.
Keywords :
facility location; genetic algorithms; road traffic; support vector machines; genetic algorithm-support vector machine; high density vehicle urban area; mechanical parking garage; site selection; Genetic algorithms; Kernel; Knowledge acquisition; Lagrangian functions; Neural networks; Optimization methods; Support vector machine classification; Support vector machines; Urban areas; Vehicles;
Conference_Titel :
Knowledge Acquisition and Modeling, 2009. KAM '09. Second International Symposium on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3888-4
DOI :
10.1109/KAM.2009.238