Analysis of Datamining Technique for Traffic Accident Severity Problem : A Review

• Autorzy: Gupta Meenu , Solanki Vijender Kumar , Singh Vijay Kumar

Identyfikatory

DOI

10.15439/2017R121

• Konferencja: The Second International Conference on Research in Intelligent and Computing in Engineering
• Języki publikacji: EN

Abstrakty

EN

This paper is discussing about the road accident severity survey using data mining, where different approaches have been considered. We have collected research work carried out by different researchers based on road accidents. Article describing the review work in context of road accident case's using data mining approach. The article is consisting of collections of methods in different scenario with the aim to resolve the road accident. Every method is somewhere seeming to productive in some ways to decrease the no of causality. It will give a better edge to different country where the no of accidents is leading to fatality of life.

Słowa kluczowe

EN

data mining; cluster analysis and algorithms; naive bayes classifiers; hybrid decision tree; association rule mining

• Wydawca: Polskie Towarzystwo Informatyczne
• Czasopismo: Annals of Computer Science and Information Systems
• Rocznik: 2017
• Tom: Vol. 10
• Strony: 197--199
• Opis fizyczny: Bibliogr. 21 poz.

Twórcy

autor

Gupta Meenu

• Ansal University, Gurgaon

autor

Solanki Vijender Kumar

• ITS, Ghaziabad

autor

Singh Vijay Kumar

• Ansal University Gurgaon

Bibliografia

• 1. Zhexue Huang, “Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Values”, Data Mining and Knowledge Discovery 2, 283-304 (1998).
• 2. Sachin Kumar and Durga Toshniwal, “A data mining framework to analyse road accident data”, Journal of Big Data (2015) 2:26 DOI 10.1186/s40537-015-0035-y.
• 3. S. Krishnaveni ans Dr. M. Hemalatha, “A perspective analysis of Traffic Accident Using Data Mining Techniques”, International Journal of Computer Application.
• 4. Olutayo V.A and Eludire A.A, “Traffic Accident Analysis Using Decision Trees and Neural Networks”, I.J. Information Technology and Computer Science, 2014, 02, 22-28 Published Online January 2014 in MECS (http://www.mecs-press.org/) http://dx.doi.org/10.5815/ijitcs.2014.02.03.
• 5. K. Geetha and C. Vaishnavi, “Analysis on Traffic Accident Injury Level Using Classification”, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 5, Issue 2, February 2015, ISSN: 2277 128X.
• 6. Sachin Kumar and Durga Toshniwal, “A data mining approach to characterize road accident locations”, J. Mod. Transport. (2016) 24(1):62-72 DOI 10.1007/s40534-016-0095-5.
• 7. Tibebe Beshah, Shawndra Hill, “Mining Road Traffic Accident Data to Improve Safety: Role of Road- elated Factors on Accident Severity in Ethiopia”
• 8. Quinlan, J. R. C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers, 1993.
• 9. K. Jayasudha and Dr. C. Chandrasekar, “An overview of Data Mining in Road Traffic and Accident Analysis”, Journal of Computer Applications, Vol - II, No.4, Oct - Dec 2009.
• 10. Miao Chong, Ajith Abraham and Marcin Paprzycki, “Traffic Accident Analysis Using Machine Learning Paradigms”, Informatica 29 (2005) 89-98.
• 11. M. Sowmya and Dr.P. Ponmuthuramalingam, “Analyzing the Road Traffic and Accidents with Classification Techniques”, International Journal of Computer Trends and Technology (IJCTT) - volume 5 number 4 -Nov 2013.
• 12. Sohn, S. and S. Lee (2002), "Data fusion, ensemble and clustering to improve the classification accuracy for the severity of road traffic accidents in Korea", Safety Science 41(1): 1-14.
• 13. Depaire B, Wets G and Vanhoof K. Traffic accident segmentation by means of latent class clustering, accident analysis and prevention, vol. 40. Elsevier; 2008.
• 14. Mario De Luca et. al., “Before-After Freeway Accident Analysis using Cluster Algorithms”, Procedia Social and Behavioral Sciences 20 (2011) 723-731, science direct.
• 15. Raffaele Mauro et. al., “Using a K-Means Clustering Algorithm to Examine Patterns of Vehicle Crashes in Before-After Analysis”.
• 16. Naina Mahajan and Bikram Pal Kaur, “Analysis of Factors of Road Traffic Accidents using Enhanced Decision Tree Algorithm “, International Journal of Computer Applications (0975 - 8887) Volume 135 - No.6, February 2016.
• 17. S. Shanthi, “Classification of Vehicle Collision Patterns in Road Accidents using Data Mining Algorithms”, International Journal of Computer Applications (0975 - 8887) Volume 35- No.12, December 2011.
• 18. Sami Ayramo et. al., “Mining Road Traffic accident”, Reports of the Department of Mathematical Information Technology Series C. Software and Computational Engineering No. C. 2/2009, University of Jyväskylä Department of Mathematical Information Technology P.O. Box 35 (Agora) FI-40014 University of Jyväskylä FINLAND fax [phone] http://www.mit.jyu.fi.
• 19. Global status reporton roadsafety: time for action, WHO, 2009.
• 20. G. Jost, M. Popolizio, R. Allsop, And V. Eksler, 3rd road safety pin report: 2010 on the horizon, report, European Transport and Safety Council (ETSC), 2009.
• 21. Dinesh Mohan et. al., Road Safety in India Status Report, Transportation Research and Injury Prevention Programme, IIT Delhi 2015.