B. Yang

Pages: 97-106

Abstract
In order to overcome the problem of low prediction accuracy of traditional traffic accident frequency prediction methods, a new traffic accident frequency prediction method based on deep data mining is proposed in this paper. Firstly, the association rule algorithm is used to deeply mine and collect traffic accident data. Secondly, based on the data collection results, the proportional sequence of traffic accident data is constructed and tested. Finally, the grey prediction model is used to construct the traffic accident frequency prediction function, and the traffic accident frequency prediction results are obtained. The experimental results show that this method can achieve high-precision traffic accident data collection, and get accurate frequency prediction results. The prediction results of traffic accident frequency basically reach 99%.
Keywords: deep data mining; traffic accident frequency; prediction; association rules