ПРИМЈЕНА СИСТЕМА ПОСЛОВНЕ ИНТЕЛИГЕНЦИЈЕ У БЕЗБЕДНОСТИ САОБРАЋАЈА
Ključne reči:
Безбедност саобраћаја, систем пословне интелигенције
Apstrakt
Напретком информатичке технологије могуће је прикупити све веће количине релевантних података, као што су свеобухватне базе података о незгодама, као и податке о вожњи у реалном времену. Иновације у информационим технологијама омогућиле су развој унапријеђеног система, па се тако појавио и почео користити концепт пословне интелигенције у различитим областима, те и у области анализе саобраћајних незгода и безбједности саобраћаја.
Reference
[1] Anda, I., Isah, R. O., & Enesi, F. A. (2017). A Safety Data Model for data analysis and decision making.
[2] Dedić N., Stanier C., Measuring the Success of Changes to Existing Business Intelligence Solutions to Improve Business Intelligence Reporting, Беч, 2016
[3] Hamidi, A., Fontaine, M. D., & Demetsky, M. J. (2010). A Planning-Level Methodology for Identifying High-Crash Sections of Virginia's Primary System (No. FHWA/VTRC 11-R4). Virginia Transportation Research Council.
[4] Hancock, Ј., Toren, R., Practical Business Intelligence With SQL Server 2005, Addison Wesley Professional, 2006.
[5] Negash., S., Business Intelligence, Kennesaw State University, 2004.
[6] Reinschmidt, J., Francoise, A. Business Intelligence Certification Guide, IBM International Technical Support Organization, San Jose, CA, 2000.
[7] Shimko, G. & Walbaum, C., City of Edmonton traffic safety strategy. Road Safety Session of the 2010 Annual Conference of the Transportation Association of Canada, Halifax, Nova Scotia., 2010.
[8] Tjandra, S. A. (2014). Business Intelligence system for traffic data integration: linking roadway, collision and traffic flow data to improve traffic safety. NATMEC 2014 Improving Traffic Data Collection, Analysis, and Use.
[9] Veeramisti, K., A Business Intelligence F A Business Intelligence Framework for Network-le amework for Network-level Traffic Safety Analyses, University of Nevada, Las Vegas, 2016.
[10] Wang, H., Wang S., A Knowledge Management Approach to Data Mining Process for Business Intelligence, Industrial Management & Data Systems, 2008.
[11] World Health Organization. WHO. (2020). The Top 10 Causes of Death.
[2] Dedić N., Stanier C., Measuring the Success of Changes to Existing Business Intelligence Solutions to Improve Business Intelligence Reporting, Беч, 2016
[3] Hamidi, A., Fontaine, M. D., & Demetsky, M. J. (2010). A Planning-Level Methodology for Identifying High-Crash Sections of Virginia's Primary System (No. FHWA/VTRC 11-R4). Virginia Transportation Research Council.
[4] Hancock, Ј., Toren, R., Practical Business Intelligence With SQL Server 2005, Addison Wesley Professional, 2006.
[5] Negash., S., Business Intelligence, Kennesaw State University, 2004.
[6] Reinschmidt, J., Francoise, A. Business Intelligence Certification Guide, IBM International Technical Support Organization, San Jose, CA, 2000.
[7] Shimko, G. & Walbaum, C., City of Edmonton traffic safety strategy. Road Safety Session of the 2010 Annual Conference of the Transportation Association of Canada, Halifax, Nova Scotia., 2010.
[8] Tjandra, S. A. (2014). Business Intelligence system for traffic data integration: linking roadway, collision and traffic flow data to improve traffic safety. NATMEC 2014 Improving Traffic Data Collection, Analysis, and Use.
[9] Veeramisti, K., A Business Intelligence F A Business Intelligence Framework for Network-le amework for Network-level Traffic Safety Analyses, University of Nevada, Las Vegas, 2016.
[10] Wang, H., Wang S., A Knowledge Management Approach to Data Mining Process for Business Intelligence, Industrial Management & Data Systems, 2008.
[11] World Health Organization. WHO. (2020). The Top 10 Causes of Death.
Objavljeno
2023-01-09
Sekcija
Saobraćajno inženjerstvo
