基于随机森林模型的城市非法营运车辆识别OA

The rapid development of regional economy and society does not match the development of traffic de-mand,which provides market opportunities for illegal taxi operation.ETC(Electronic Toll Collection)data of urban expressways can effectively check illegal taxi operation on expressways,so as to optimize operation order and improve management level.This study extracts the effective fields of ETC data,uses the random forest algorithm to establish the illegal taxi operation recognition classifier,adds the classifiers of the CART(Classification and Regression Tree)classification tree model and the binary logistic regression model to conduct performance comparison,and makes an empirical analysis with the ETC index data of a highway in a southwest city from February 6,2022 to March 8,2022.The results show that performance the random forest model classifier is better than that of the CART classification tree model classifier and the binary logistic regression model classifier,and its accuracy score of the proposed model is 98.75%.