Identification of high-risk roadway segments for wrong-way driving crash using rare event modeling and data augmentation techniques-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Identification of high-risk roadway segments for wrong-way driving crash using rare event modeling and data augmentation techniques

Published:2023-03 Issue: Volume:181 Page:106933
ISSN:0001-4575
Container-title:Accident Analysis & Prevention
language:en
Short-container-title:Accident Analysis & Prevention

Author:

Ashraf Md Tanvir,Dey Kakan,Mishra Sabyasachee

Publisher

Elsevier BV

Subject

Public Health, Environmental and Occupational Health,Safety, Risk, Reliability and Quality,Human Factors and Ergonomics

Reference49 articles.

1. SMOTE: synthetic minority over-sampling technique;Chawla;Journal of artificial intelligence research,2002

2. Wrong-Way Driving on Freeways : Problems;Cooner;Issues, and Countermeasures.,2007

3. Investigation on the wrong way driving crash patterns using multiple correspondence analysis;Das;Accident Analysis and Prevention,2018

4. Factors influencing the patterns of wrong-way driving crashes on freeway exit ramps and median crossovers: Exploration using ‘Eclat’association rules to promote safety;Das;International journal of transportation science and technology,2018

Cited by 17 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Path-Sampling and Machine Learning for Rare Abnormal Events: Application to Polymerization CSTRs;Chemical Engineering Science;2024-12

2. Considering multi-scale built environment in modeling severity of traffic violations by elderly drivers: An interpretable machine learning framework;Accident Analysis & Prevention;2024-11

3. An ensemble method for investigating maritime casualties resulting in pollution occurrence: Data augmentation and feature analysis;Reliability Engineering & System Safety;2024-11

4. Investigating the features of risky driving behaviors on expressway diverge area based on conflict and modeling analysis;Accident Analysis & Prevention;2024-10

5. Data Mining Approach to Explore the Contributing Factors to Fatal Wrong-Way Crashes by Local and Non-Local Drivers;Future Transportation;2024-09-02

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3