This paper presents the prediction of traffic-violations using data mining techniques, more specifically, when most likely a traffic-violation may happen. Also, the contributing factors that may cause more damages (e.g., personal injury, property damage, etc.) are discussed in this paper. The national database for traffic-violation was considered for the mining and analyzed results indicated that a few specific times are probable for traffic-violations. Moreover, most accidents happened on specific days and times. The findings of this work could help prevent some traffic-violations or reduce the chance of occurrence. These results can be used to increase cautions and traffic-safety tips.
CITATION STYLE
Amiruzzaman, M. (2019). Prediction of traffic-violation using data mining techniques. In Advances in Intelligent Systems and Computing (Vol. 880, pp. 283–297). Springer Verlag. https://doi.org/10.1007/978-3-030-02686-8_23
Mendeley helps you to discover research relevant for your work.