Site selection of metropolitan shared mechanical parking garage based on spatial data mining

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.