Title :
Site selection of metropolitan shared mechanical parking garage based on spatial data mining
Author :
Tang, Minan ; Ren, Enen
Author_Institution :
Mechatron. T&R Inst., Lanzhou Jiaotong Univ., Lanzhou, China
Abstract :
The parking has become a social problem that seriously restricts the development of society and economy and affects the life quality of people in many metropolises. The site selection of metropolitan shared mechanical parking garage is involved with the utility proficiency of garage. By combing inductive learning with GIS spatial analysis the site selection analysis and evaluation of shared mechanical parking garage in metropolis is presented. The results show that: inductive learning and spatial analysis can promote mutually and the intellectual level of GIS spatial data analysis and decision-making support are enhanced. With comparison of case research analysis, the effectiveness of this approach has been proved.
Keywords :
data mining; decision support systems; geographic information systems; learning by example; traffic control; GIS spatial analysis; decision making support; inductive learning; metropolitan shared mechanical parking garage; site selection analysis; spatial data mining; Cities and towns; Computational intelligence; Computer industry; Data analysis; Data mining; Decision making; Geographic Information Systems; Legged locomotion; Mechatronics; Statistics; inductive learning; mechanical parking system; site selection analysis and evaluation; spatial data analysis; spatial data mining;
Conference_Titel :
Computational Intelligence and Industrial Applications, 2009. PACIIA 2009. Asia-Pacific Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4606-3
DOI :
10.1109/PACIIA.2009.5406448
