Abstract
In this paper, we apply cluster analysis to "Okayama parking data" that is one of the spatial point patterns data that includes locations and the fare structure of car parking space in Okayama central area. This study classifies the characteristics of small areas through Okayama parking data as well as visualizes the results of the cluster analysis. We develop web applications that connect the results of a cluster analysis and overlay objects including points of balloons and rectangles of small areas over a map of Okayama central area.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Communications for Statistical Applications and Methods
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
