A Identification Method on Traffic Accidents in the Lower Yangtze River

According to the complicated calculation process and low practicability of Support Vector Machine(SVM) model in the prediction of ship traffic accidents due to large number of variables, first Random Forest(RF) model is used to rank the importance of variables in the article, then filtered variables is used to construct a new SVM model, finally validity of the new model is verified based on historical data and compared it with the prediction results of the original model. By comparing with prediction results of the original model, results show that the new model is not only relatively simple in calculation but also has better prediction effect, and classification accuracy rate provides 4.12%.