Comparison of traffic accident injury severity prediction models with explainable machine learning-Reference-Cited by-同舟云学术

Comparison of traffic accident injury severity prediction models with explainable machine learning

Published:2023-05-17 Issue:9 Volume:15 Page:1043-1054
ISSN:1942-7867
Container-title:Transportation Letters
language:en
Short-container-title:Transportation Letters

Author:

Cicek Elif¹,Akin Murat²,Uysal Furkan³,Topcu Aytas ReyhanMerve⁴

Affiliation:

1. Department of Civil Engineering, Hacettepe University, Ankara, Turkey

2. Engineering Faculty, Gazi University, Ankara, Turkey

3. College of Engineering and Technology, American University of the Middle East, Egaila, Kuwait

4. Department of Industrial Engineering, Gazi University, Ankara, Turkey

Publisher

Informa UK Limited

Subject

Transportation

Link

https://www.tandfonline.com/doi/pdf/10.1080/19427867.2023.2214758

Reference45 articles.

1. Development of Artificial Neural Network Models to Predict Driver Injury Severity in Traffic Accidents at Signalized Intersections

2. Human factors contributing to the road traffic accident occurrence

3. Fatalıty Rate Analysıs of Major and Extraordınary Road Traffıc Accıdents Based on C4. 5 Decısıon Tree Algorıthm;Chen T.;Part B, Applications: An İ̇nternational Journal of Research and Surveys,2019

4. Investigating driver injury severity patterns in rollover crashes using support vector machine models

5. Support-vector networks

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