Analysis of Road Accidents Using Data Mining Techniques
-
2018-07-15 https://doi.org/10.14419/ijet.v7i3.10.15626
-
Apriori, Naïve Bayes, Pattern Prediction, Road Accident. -
Abstract
Road Accident is an all-inclusive disaster with consistently raising pattern. In India according to Indian road safety campaign every minute there is a road accident and almost 17 people die per hour in road accidents. There are different categories of vehicle accidents like rear end, head on and rollover accidents. The state recorded police reports or FIR’s are the documents which contains the information about the accidents. The incident may be self-reported by the people or recorded by the state police. In this paper the frequent patterns of road accidents is been predicted using Apriori and Naïve Bayesian techniques. This pattern will help the government or NGOs to improve the safety and take preventive measures in the roads that have major accident zones.Â
Â
-
References
[1] F.M.O.I. Forensic Medicine Organization of Iran; Statistical Data, Accidents, online avail-able on: http://www.lmo.ir/?siteid=1&pageid=1347
[2] A.T. Kashani et al., “A Data Mining Approach to Identify Key Factors of Traffic Injury Severityâ€, PROMETTraffic& Transportation, 23(1), pp. 11-17, 2011.
[3] L.Y. Chang, H.W. Wang, “Analysis of traffic injury severity: An application of non-parametric classification tree techniquesâ€, Accident Analysis and Prevention, 38(5), pp. 1019-1027, 2006.
[4] S. Yau-Ren et al. “The Application of Data Mining Technology to Build a Forecasting Model for Classification of Road Traffic Accidentsâ€, Mathematical Problems in Engineering, Volume 2015 (2015), pp. 1-8., 2015. F. Babiô€ƒ¾ and K. Zuskáô€ƒ¾ová • Descriptive and Predictive Mining on Road Accidents Data– 92
[5] R. Nayak et al., “Road Crash Proneness Prediction using Data Miningâ€. Ailamaki, Anastasia & Amer-Yahia , Sihem (Eds.) Proceedings of the 14th International Conference on Extending Database Technology, Association for Computing Machinery (ACM), Upp-sala, Sweden, pp. 521-526, 2011.
[6] V. Shankar, J. Milton, F. Mannering, “Modeling accident frequencies as zero-altered probability processes: An empirical inquiryâ€, Accident Analysis & Prevention, 29(6), pp. 829-837, 1997.
[7] A Araar et al., “Mining road traffic accident data to improve safety in Dubaiâ€, Journal of Theoretical and Applied Information Technology, 47(3), pp. 911-927, 2013.
[8] S. Vigneswaran et al., “Efficient Analysis of Traffic Accident Using Mining Techniquesâ€, International Journal of Software and Hardware Research in Engineering, Vol. 2, No. 3, 2014, pp. 110- 118, 2014.
[9] L. Martin et al. “Using data mining techniques to road safety improvement in Spanish roadsâ€, XI Congreso de IngenierÃa del Transporte (CIT 2014), Procedia - Social and Behavioral Sciences 160 (2014), pp. 607–614, 2014.
[10] P. Flach et al., “On the road to knowledge: Mining 21 years of UK traffic accident reportsâ€, Data Mining and Decision Support: Aspects of Integration and Collaboration, Springer, pp. 143-155, 2003.
[11] H. Zhang et al., “In-Memory Big Data Management and Processing: A Surveyâ€, IEEE Transactions on Knowledge and Data Engineering, Vol. 27, No. 7, pp. 1920–1948, 2015.
[12] J. Hipp, U. Güntzer, G. Nakhaeizadeh, “Algorithms for Association Rule Mining &Mdash; a General Survey and Comparisonâ€, SIGKDD Explor Newsl 2, pp. 58–64, 2000.
[13] A.T. Kashani et al., “A Data Mining Approach to Identify Key Factors of Traffic Injury Severityâ€, PROMETTraffic& Transportation, 23(1), pp. 11-17, 2011.
[14] P.J. Ossenbruggen, J. Pendharkar et al., “Roadway safety in rural and small urbanized areasâ€, Accidents Analysis & Prevention, 33(4), pp. 485-498, 2001.
[15] R. Agrawal, T. Imieliô€„”ski, A. Swami, “Mining Association Rules Between Sets of Items in Large Databasesâ€, Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data, ACM, New York, NY, USA, pp. 207–216, 1993.
[16] [16]R. Agrawal, R. Srikant, “Fast Algorithms for Mining Association Rules in Large Data-basesâ€, Proceedings of the 20th International Conference on Very Large Data Bases, Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, pp 487-499, 1994.
[17] L. Breiman, “Random Forestsâ€, Machine Learning, Vol. 45, pp. 5- 32, 2001.
[18] T. Calders et al., “Machine Learning and Knowledge Discovery in Databasesâ€, Part II. Nancy, France, Springer, pp. 203-232, 2014.
[19] EC: Mobility and Transport, Road Safety, Statistics – accidents data, online available on: http://ec.europa.eu/transport/road_safety/specialist/statistics/index_en.htm
[20] J. H. Friedman, “Stochastic gradient boostingâ€, Computational Statistics & Data Analysis - Nonlinear methods and data mining, 38(4), pp. 367-378, 2002
[21] Ahalya, C. S., Abin, K. O., & Kanchana, V. (2017, May). Building up an information archive for putting away pesticide data. In Recent Trends in Electronics, Information & Communication Technology (RTEICT), 2017 2nd IEEE International Conference on (pp. 2125-2128). IEEE.
[22] Devasia, T., Vinushree, T. P., & Hegde, V. (2016, March). Prediction of students performance using Educational Data Mining. In Data Mining and Advanced Computing (SAPIENCE), International Conference on (pp. 91-95). IEEE.
-
Downloads
-
How to Cite
Nidhi. R, M., & Kanchana V, M. (2018). Analysis of Road Accidents Using Data Mining Techniques. International Journal of Engineering & Technology, 7(3.10), 40-44. https://doi.org/10.14419/ijet.v7i3.10.15626Received date: 2018-07-14
Accepted date: 2018-07-14
Published date: 2018-07-15