Research on Road Traffic Fatal Accidents using Data Mining Techniques
S. P. Godlin Jasil1, K. Sai Preeti2, Shaik Arifa Banu3

1S .P. Godlin Jasil, Assistant professor, Deptmant of CSE, Sathyabama University, Chennai (TamilNadu), India.

2K. Sai Preeti, UG Student, Deptmant of CSE, Sathyabama University, Chennai (TamilNadu), India.

3Shaik Arifa Banu, UG Student, Deptmant of CSE, Sathyabama University, Chennai (TamilNadu), India

Manuscript received on 20 August 2019 | Revised Manuscript received on 27 August 2019 | Manuscript Published on 31 August 2019 | PP: 757-760 | Volume-8 Issue-9S2 August 2019 | Retrieval Number: I11570789S219/19©BEIESP DOI: 10.35940/ijitee.I1157.0789S219

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Road safety plays a major role in our day-to-day life and also transportation system, due to its priority, it has become the major concern for everyone. In order to increase the road safety, traffic rules are included in education, clear and careful predictive analysis and study is done on factors effecting fatal accidents. We apply predictive analysis, statistical analysis and some algorithms related to data mining which includes FARS such as Apriori algorithm, associative rule techniques are used. These methods help in encountering the road fatal accidents that cause due to mentioned factors. These factors may include climatic and surface conditions and also drunken drivers or may be condition of vehicles also. Clusters are formed using simple k-means clustering algorithms. Finally road safety driving rules are made based on the factors effecting, clusters formed and predictive analysis and prior information.

Keywords: Mentioned Factors, Data Mining Techniques.
Scope of the Article: Data Mining Methods, Techniques, and Tools