电子科技2024，Vol.37Issue(1)：66-71,6.DOI:10.16180/j.cnki.issn1007-7820.2024.01.010
基于随机森林模型的城市非法营运车辆识别
Research on Identification of Urban Illegal Vehicles Based on Random Forest Model
摘要
Abstract
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%.关键词
非法营运车辆/随机森林模型/CART分类树模型/二元逻辑回归模型/分类算法/机器学习/深度学习/识别算法Key words
illegal taxi operation/random forest model/CART classification tree model/binary logistic regression model/classification algorithm/machine learning/deep learning/recognition algorithm分类
信息技术与安全科学引用本文复制引用
黄子璇,李桥兴..基于随机森林模型的城市非法营运车辆识别[J].电子科技,2024,37(1):66-71,6.基金项目
国家自然科学基金(71663011) （71663011）
贵州大学"研究基地及智库"重点专项课题(GDZX 2021030) （GDZX 2021030）
贵州大学人文社会科学一般项目(GDYB2021020)National Natural Science Foundation of China(71663011) （GDYB2021020）
Key Spe-cial Project of"Research Base and Think Tank"of Guizhou Univer-sity(GDZX 2021030) （GDZX 2021030）
General Humanities and Social Sciences Pro-gram of Guizhou University(GDYB2021020) （GDYB2021020）
