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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

A hybrid approach of random forest and random parameters logit model of injury severity modeling of vulnerable road users involved crashes
Zhiyuan Sun, Duo Wang, Xin Gu, et al.
Accident Analysis & Prevention (2023) Vol. 192, pp. 107235-107235
Closed Access | Times Cited: 29

Showing 1-25 of 29 citing articles:

An interpretable model for landslide susceptibility assessment based on Optuna hyperparameter optimization and Random Forest
Xin Xiao, Yi Zou, Jiangcheng Huang, et al.
Geomatics Natural Hazards and Risk (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 17
Analyzing the transition from two-vehicle collisions to chain reaction crashes: A hybrid approach using random parameters logit model, interpretable machine learning, and clustering
Seyed Alireza Samerei, Kayvan Aghabayk
Accident Analysis & Prevention (2024) Vol. 202, pp. 107603-107603
Closed Access | Times Cited: 14
Injury severity prediction and exploration of behavior-cause relationships in automotive crashes using natural language processing and extreme gradient boosting
Yichang Shao, Xiaomeng Shi, Yuhan Zhang, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108542-108542
Closed Access | Times Cited: 13
Inversion of large-scale citrus soil moisture using multi-temporal Sentinel-1 and Landsat-8 data
Zongjun Wu, Ningbo Cui, Wenjiang Zhang, et al.
Agricultural Water Management (2024) Vol. 294, pp. 108718-108718
Open Access | Times Cited: 11
A hybrid Machine learning and statistical modeling approach for analyzing the crash severity of mobility scooter users considering temporal instability
Matin Sadeghi, Kayvan Aghabayk, Mohammed Quddus
Accident Analysis & Prevention (2024) Vol. 206, pp. 107696-107696
Closed Access | Times Cited: 11
Understanding key contributing factors on the severity of traffic violations by elderly drivers: a hybrid approach of latent class analysis and XGBoost based SHAP
Zhiyuan Sun, Zhicheng Wang, Xin Qi, et al.
International Journal of Injury Control and Safety Promotion (2024) Vol. 31, Iss. 2, pp. 273-293
Closed Access | Times Cited: 8
A hybrid approach for modeling bicycle crash frequencies: Integrating random forest based SHAP model with random parameter negative binomial regression model
Hongliang Ding, Ruiqi Wang, Tiantian Chen, et al.
Accident Analysis & Prevention (2024) Vol. 208, pp. 107778-107778
Closed Access | Times Cited: 7
Investigating older driver crashes on high-speed roadway segments: a hybrid approach with extreme gradient boosting and random parameter model
Ahmed Hossain, Xiaoduan Sun, Subasish Das, et al.
Transportmetrica A Transport Science (2024), pp. 1-35
Closed Access | Times Cited: 5
How does distraction affect cyclists’ severe crashes? A hybrid CatBoost-SHAP and random parameters binary logit approach
Ali Agheli, Kayvan Aghabayk
Accident Analysis & Prevention (2024) Vol. 211, pp. 107896-107896
Closed Access | Times Cited: 5
Exploring the Factors Affecting the Injury Severity of Crashes on Mountainous Freeways with High Proportions of Heavy Vehicles Considering Their Heterogeneous and Interactive Effects
Keqiang Sun, Yongquan Li, Qiang Zeng, et al.
Sustainability (2025) Vol. 17, Iss. 4, pp. 1624-1624
Open Access
Analyzing Feature Importance for Older Pedestrian Crash Severity: A Comparative Study of DNN Models, Emphasizing Road and Vehicle Types with SHAP Interpretation
Rocksana Akter, Susilawati Susilawati, Hamza Zubair, et al.
Multimodal Transportation (2025), pp. 100203-100203
Open Access
E-scooter crash severity in the United Kingdom: A comparative analysis using machine learning techniques and random parameters logit with heterogeneity in means and variances
Ali Agheli, Kayvan Aghabayk, Matin Sadeghi, et al.
IATSS Research (2025) Vol. 49, Iss. 2, pp. 155-168
Closed Access
Cyclist crash severity modeling: A hybrid approach of XGBoost-SHAP and random parameters logit with heterogeneity in means and variances
Antonella Scarano, Matin Sadeghi, Filomena Mauriello, et al.
Journal of Safety Research (2025) Vol. 93, pp. 373-398
Open Access
Identifying factors affecting crash injury severity of pillion riders using interpretable machine learning techniques
Anju K. Panicker, Gitakrishnan Ramadurai
International Journal of Injury Control and Safety Promotion (2025), pp. 1-13
Closed Access
Context-dependent effects of built environment factors on pedestrian-injury severities with imbalanced and high dimensional crash data
Zehao Wang, Wei Fan
Accident Analysis & Prevention (2025) Vol. 218, pp. 108104-108104
Closed Access
Pickup truck crash severity analysis via machine learning: policy insights for developing countries
Chamroeun Se, Thanapong Champahom, Sajjakaj Jomnonkwao, et al.
International Journal of Injury Control and Safety Promotion (2025), pp. 1-21
Closed Access
Analyzing the heterogenous effects of factors on high-range speeding likelihood of taxi speeders: Does explainable deep learning provides more insights than random parameter approach?
Yue Zhou, Chuanyun Fu, Xinguo Jiang, et al.
Accident Analysis & Prevention (2024) Vol. 207, pp. 107752-107752
Closed Access | Times Cited: 2
Tree-based approaches to understanding factors influencing crash severity across roadway classes: A Thailand case study
Thanapong Champahom, Chamroeun Se, Fareeda Watcharamaisakul, et al.
IATSS Research (2024) Vol. 48, Iss. 3, pp. 464-476
Open Access | Times Cited: 2
Young novice drivers’ road crash injuries and contributing factors: A crash data investigation
Yansong Zhu, Yubin Qian, Jiejie Xu, et al.
Traffic Injury Prevention (2024) Vol. 25, Iss. 8, pp. 1031-1038
Closed Access | Times Cited: 1
Real-time conflict risk at signalized intersection using drone video: A random parameters logit model with heterogeneity in means and variances
Shile Zhang, N.N. Sze
Accident Analysis & Prevention (2024) Vol. 207, pp. 107739-107739
Closed Access | Times Cited: 1
Gut and respiratory microbiota landscapes in IgA nephropathy: a cross-sectional study
Xiaoli Yuan, Jianbo Qing, Wenqiang Zhi, et al.
Renal Failure (2024) Vol. 46, Iss. 2
Open Access | Times Cited: 1
Modeling motorcycle crash-injury severity utilizing explainable data-driven approaches
Chamroeun Se, Jirapon Sunkpho, Warit Wipulanusat, et al.
Transportation Letters (2024), pp. 1-26
Closed Access | Times Cited: 1
Spatial analysis of daytime and nighttime crash severity on horizontal curves of mountainous rural highways: A case study in Northern Iran
Morteza Safari, Meysam Effati, Mahyar Arabani
Results in Engineering (2024) Vol. 24, pp. 103344-103344
Closed Access | Times Cited: 1
Visual hazardous models: A hybrid approach to investigate road hazardous events
Harikrishna Rangam, Sathish Kumar Sivasankaran, Venkatesh Balasubramanian
Accident Analysis & Prevention (2024) Vol. 200, pp. 107556-107556
Closed Access
Evaluating Crashes Involving Distracted Cyclists: A Hybrid Approach of Catboost-Shap and Random Parameters Binary Logit with Heterogeneity in Means and Variances
Ali Agheli, Kayvan Aghabayk, Dominique Lord
(2024)
Closed Access
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