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Reseach Article

A Review on Injury Severity in Traffic System using Various Data Mining Techniques

by Dheeraj Khera, Williamjeet Singh
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 100 - Number 3
Year of Publication: 2014
Authors: Dheeraj Khera, Williamjeet Singh
10.5120/17506-8056

Dheeraj Khera, Williamjeet Singh . A Review on Injury Severity in Traffic System using Various Data Mining Techniques. International Journal of Computer Applications. 100, 3 ( August 2014), 17-22. DOI=10.5120/17506-8056

@article{ 10.5120/17506-8056,
author = { Dheeraj Khera, Williamjeet Singh },
title = { A Review on Injury Severity in Traffic System using Various Data Mining Techniques },
journal = { International Journal of Computer Applications },
issue_date = { August 2014 },
volume = { 100 },
number = { 3 },
month = { August },
year = { 2014 },
issn = { 0975-8887 },
pages = { 17-22 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume100/number3/17506-8056/ },
doi = { 10.5120/17506-8056 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:29:00.717792+05:30
%A Dheeraj Khera
%A Williamjeet Singh
%T A Review on Injury Severity in Traffic System using Various Data Mining Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 100
%N 3
%P 17-22
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Road Traffic Accidents (RTAs) are a major public health concern, resulting in an estimated 1. 2 million deaths and 50 million injuries worldwide each year. In the developing world, RTAs are among the leading cause of death and injury. The objective of this study is to evaluate a set of variables that contribute to the degree of injury severity in traffic crashes. The issue of traffic safety has raised great concerns across the globe and it has become one of the key issues challenging the sustainable development of modern traffic and transportation. The study on road traffic accident causes can identify the key factors rapidly, efficiently and provide instructional methods to the traffic accidents prevention and road traffic accidents reduction, which could greatly reduce personal casualty and property loss caused by road traffic accidents. Using the method of traffic data analysis, can improve the road traffic safety management level effectively.

References
  1. Ali Tavakoli Kashani, Afshin Shariat, Andishe Ranjbari ," A Data Mining Approach to identify key factors of traffic injury severity" Traffic & Transportation, Vol. 23, 2011, No. 1, 11-17.
  2. Bouckaert Remco, Eibe Frank, Mark Hall, Richard Kirkby, Peter Reutemann, and Alex Seewald, 2008. WEKA Manual for Version 3-6-0. University of Waikato, New Zealand.
  3. Brijesh Kumar Baradwaj, Saurabh Pal," Mining Educational Data to Analyze Students Performance" (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 2, No. 6, 2011
  4. Chaozhong Wu, Ming Ma, Hu Lei, Xinping Yan,"Severity Analyses of Single-Vehicle Crashes Based on Rough Set Theory" 2009 International Conference on Computational Intelligence and Natural Computing.
  5. DipoT. Akomolafe, Akinbola Olutayo," Using Data Mining Technique to Predict Cause of Accident and Accident Prone Locations on Highways" American Journal of Database Theory and Application 2012, 1(3): 26-38.
  6. Han, Jiawei and Kamber, Micheline. (2006). Data Mining: concepts and Techniques. San Fransisco; Morgan kufman Publishers
  7. Hand, D. J. , Mannila, H. , and Smyth, P. (2001). Principles of Data Mining, MIT Press
  8. http://en. wikipedia. org/wiki/weka (machine learning)/ accessed on May 2014.
  9. http://rapid-i. com/content/view/181/190/ accessed on May 2014.
  10. Liping Guan, Weiming Liu, Xiangyuan Yin, Luping Zhang," Traffic Incident Duration Prediction Based on Artificial Neural Network" 2010 International Conference on Intelligent Computation Technology and Automation
  11. Mehmed Kantardzic (2003). Data mining: Concepts, Models, Methods, and Algorithms, ISBN13: 9780471228523, John Wiley & Sons Publisher
  12. Pasko Konjevoda and Nikola Stambuk, "Open-Source Tools for Data Mining in Social Science," Theoretical and Methodological Approaches to Social Sciences and Knowledge Management, pp. 163-176
  13. S. Krishnaveni, Dr. M. Hemalatha," A Perspective Analysis of Traffic Accident using Data Mining Techniques", International Journal of Computer Applications (0975 – 8887) Volume 23– No. 7, June 2011.
  14. S. Shanthi, R. Geetha Ramani " Feature Relevance Analysis and Classification of Road Traffic Accident Data through Data Mining Techniques" Proceedings of the World Congress on Engineering and Computer Science 2012 Vol. I WCECS 2012, October 24-26, 2012, San Francisco, USA
  15. Tibebe Shah, Shawndra Hill (2013)," Mining Road Traffic Accident Data to Improve Safety: Role of Road- related Factors on Accident Severity in Ethiopia".
  16. Tanagra – a Free Data Mining Software for Teaching and Research, Available at: http://eric. univ-lyon2. fr/~ricco/tanagra/en/tanagra. html.
  17. WHO (2004),"World report on road traffic injury prevention", Switzerland, Geneva
Index Terms

Computer Science
Information Sciences

Keywords

Road Traffic Accidents Data Mining Influential Factors Weka Tanagra R Data Mining Techniques.