Design of Freeway Traffic Block Multi-Dimensional Data Warehouse

Abstract:

Article Preview

Through analysis of large sample data of freeway traffic block event, the data source of freeway traffic block is found out and summarized. Based on that, this paper propose a national level, distributed, freeway traffic block multidimensional data warehouse (FTBMDW) , and present the concept model , logical model and physical models of the data warehouse. The purpose of the FTBMDW is to support inter-provincial and inter-regional freeway traffic block analysis with reliable data.

Info:

Periodical:

Advanced Materials Research (Volumes 779-780)

Edited by:

Jimmy (C.M.) Kao, Wen-Pei Sung and Ran Chen

Pages:

954-957

DOI:

10.4028/www.scientific.net/AMR.779-780.954

Citation:

L. He et al., "Design of Freeway Traffic Block Multi-Dimensional Data Warehouse", Advanced Materials Research, Vols. 779-780, pp. 954-957, 2013

Online since:

September 2013

Export:

Price:

$38.00

[1] Ye ke, Dong Leihong: The national Freeway traffic blocking information data statistics and analysis, JOURNAL OF FREEWAY AND TRANSPORTATION RESEARCH AND DEVELOPMENT Vol. 26 (2009), p.121.

[2] Transportation ministry unit of the People's Republic of China: 2010 the national main road network run reports (2011).

[3] W.H. Inmon: Building the Data Warehouse( 2002), John Wiley & Sons, Inc.

[4] Transportation ministry unit of the People's Republic of China: Freeway traffic blocking information submitted to the system (commissioning )(2006).

[5] Transportation ministry unit of the People's Republic of China: Freeway traffic blocking information submitted to the system (2011).

[6] Traffic administration of Ministry of public security: The People's Republic of China on road traffic safety guidelines (2003) , Chinese people's public security university press.

[7] Lenzerini, M., Data integration: a theoretical perspective, in Proceedings of the Twenty-first ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems Madison ( 2002), Wisconsin. pp.233-246.

DOI: 10.1145/543643.543644

[8] Chen Yan: Data warehouse and data mining , Dalian maritime university press. (2006).

In order to see related information, you need to Login.