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Analysis of Causes of Traffic Accidents Based on Improved Apriori Association Rules

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DOI: 10.25236/meici.2019.056


Chunhe Shi, Yu Ding, Gaofeng Yue, and Yinghong Xie

Corresponding Author

Chunhe Shi


Road traffic Safety is a public safety issue, with the people of deaths from traffic accidents each year accounting for the highest proportion of total deaths due to all safety incidents. With the development of big data intelligent analysis technology, it is helpful to put forward targeted measures to prevent the occurrence of traffic accidents. This paper uses the traffic accident data source of a city in southern China to extract the related factors of traffic accident, such as time, weather, location and the type of accident, and then uses Apriori algorithm to mine the related factors, find out the various combination factors that lead to the accident, thus summed up the law of multiple traffic accidents. Some of the conclusions drawn from these rules could be made available to the authorities in order to take preventive and regulatory measures to reduce the incidence of accidents.


Association Rules, Apriori Algorithm, Data Mining, Road Traffic