Data Mining in Traffic Flow Analysis of City Tunnel

Author

Ma, Chengqian ; Yuan, Jingling ; Zhong, Luo ; Yue, Xi

Author_Institution

Comput. Sci. & Technol. Sch., Wuhan Univ. of Technol., Wuhan, China

fYear

2009

fDate

25-26 April 2009

Firstpage

199

Lastpage

201

Abstract

The elementary theories and methods of data mining technology is introduced, and specifically applied the data mining technology to the Uprising Square Tunnel traffic flow in the city of Wuhan. Using the clustering analysis tools provided by SQL SERVER 2000, we first carry on the clean to the primary data, and then set up a data mining model, finally carry on the analysis to the result to obtain some traffic characteristics of the tunnel. This information not only helps the tunnel administrative personnel to manage the tunnel more effectively, but also facilitate driving personnel´s going on a journey.

Keywords

SQL; data mining; pattern clustering; traffic engineering computing; tunnels; SQL SERVER 2000; Uprising Square Tunnel traffic flow; city tunnel; clustering analysis tool; data mining; traffic flow analysis; Algorithm design and analysis; Cities and towns; Clustering algorithms; Computer science; Data analysis; Data mining; Databases; Iterative algorithms; Pattern analysis; Traffic control; analysis services; clustering analysis; data minning; traffic flow;

fLanguage

English

Publisher

ieee

Conference_Titel

Database Technology and Applications, 2009 First International Workshop on

Conference_Location

Wuhan, Hubei

Print_ISBN

978-0-7695-3604-0

Type

conf

DOI

10.1109/DBTA.2009.59

Filename

5207780