Quantifying incident impacts and identifying influential features in urban traffic networks-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Quantifying incident impacts and identifying influential features in urban traffic networks

Published:2022-04-18 Issue:1 Volume:11 Page:279-300
ISSN:2168-0566
Container-title:Transportmetrica B: Transport Dynamics
language:en
Short-container-title:Transportmetrica B: Transport Dynamics

Author:

Lee JuYeong¹^ORCID,Kwak JiIn²^ORCID,Oh YongKyung¹^ORCID,Kim Sungil¹²^ORCID

Affiliation:

1. Department of Industrial Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea

2. Artificial Intelligence Graduate School, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea

Funder

NAVER Corp.

Institute of Information & communications Technology Planning & Evaluation

Korea government

Publisher

Informa UK Limited

Subject

Transportation,Modeling and Simulation,Software

Link

https://www.tandfonline.com/doi/pdf/10.1080/21680566.2022.2063205

Reference55 articles.

1. A Survey of Road Traffic Congestion Measures towards a Sustainable and Resilient Transportation System

2. Mechanistic approach to generalized technical analysis of share prices and stock market indices

3. Analyzing the Cascading Effect of Traffic Congestion Using LSTM Networks

4. Parametric Models, Duration Dependence, and Time-Varying Data Revisited

Cited by 4 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. Prediction of the traffic incident duration using statistical and machine-learning methods: A systematic literature review;Technological Forecasting and Social Change;2024-10

2. RoadFormer: Road-Anchored Adversarial Dynamic Graph Transformer for Unlimited-Range Traffic Incident Impact Prediction;2023 IEEE International Conference on Big Data (BigData);2023-12-15

3. Spatially‐correlated time series clustering using location‐dependent Dirichlet process mixture model;Statistical Analysis and Data Mining: The ASA Data Science Journal;2023-11-22

4. Time delay estimation of traffic congestion propagation due to accidents based on statistical causality;Electronic Research Archive;2023

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