出版社:Academy & Industry Research Collaboration Center (AIRCC)
摘要:Nowadays, road traffic accidents are one of the leading causes of deaths in this world. It is a
complex phenomenon leaving a significant negative impact on human’s life and properties.
Classification techniques of data mining are found efficient to deal with such phenomena. After
collecting data from Lebanese Internal Security Forces, data are split into training and testing
sets using 10-fold cross validation. This paper aims to apply two different algorithms of
Decision Trees C4.5 and CART, and various Artificial Neural Networks (MLP) in order to
predict the fatality of road accidents in Lebanon. Afterwards, a comparative study is made to
find the best performing algorithm. The results have shown that MLP with 2 hidden layers and
42 neurons in each layer is the best algorithm with accuracy rate of prediction (94.6%) and
area under curve (AUC 95.71%).