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Application of spatial data mining for traffic management: case study of a city of Calgary street

عنوان مقاله: Application of spatial data mining for traffic management: case study of a city of Calgary street
شناسه ملی مقاله: ICSAU07_1155
منتشر شده در هفتمین کنگره سالانه بین المللی عمران، معماری و توسعه شهری در سال 1400
مشخصات نویسندگان مقاله:

Iman rajabi pour - Department of Surveying Engineering, Technical and Vocational University (TVU), Tehran, Iran,
Mohammad ali rastkhiz sarokolaei - Department of Geomatics, Faculty of Civil Engineering, Babol Noshirvani University of Technology,Shariaty St, Babol, ۴۷۱۴۸۷۱۱۶۷, Iran,

خلاصه مقاله:
The flow of data coming from modern sensing devices enables the development of novel research techniques related to data management and knowledge extraction. In this research, the investigation is on the analysis of traffic movement in a road network using the density based clustering algorithm, DBSCAN. The objective of this research is to present a methodology that can aid city authorities in the optimization of traffic flow by identifying congestion within the street network. In this paper, it has been focused on the spatial characteristics of traffic movement, which provides insight into the flow of traffic within the street network. A case study was conducted to illustrate the use of densitybased cluster analysis. Experimental results illustrate the applicability and usefulness of the proposed approach.

کلمات کلیدی:
Spatial data mining, DBSCAN, Traffic management, clustering.

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/1374422/