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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:

Application of machine learning techniques for predicting the consequences of construction accidents in China
Rongchen Zhu, Xiaofeng Hu, Jiaqi Hou, et al.
Process Safety and Environmental Protection (2020) Vol. 145, pp. 293-302
Closed Access | Times Cited: 121

Showing 26-50 of 121 citing articles:

A novel voting ensemble model empowered by metaheuristic feature selection for accurate flash flood susceptibility mapping
Radhwan A. A. Saleh, Ahmed M. Al‐Areeq, Amran A. Al Aghbari, et al.
Geomatics Natural Hazards and Risk (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 6
Data-Driven Approaches for Accident Analysis in Sociochemical Systems
Kamran Gholamizadeh, Esmaeil Zarei, Mohammad Yazdi, et al.
Studies in systems, decision and control (2024), pp. 457-486
Closed Access | Times Cited: 5
Applications of Bayesian approaches in construction management research: a systematic review
Carol K.H. Hon, Chenjunyan Sun, Bo Xia, et al.
Engineering Construction & Architectural Management (2021) Vol. 29, Iss. 5, pp. 2153-2182
Open Access | Times Cited: 29
A Data-Driven Recommendation System for Construction Safety Risk Assessment
Fatemeh Mostofi, Vedat Toğan
Journal of Construction Engineering and Management (2023) Vol. 149, Iss. 12
Closed Access | Times Cited: 12
Predicting Safety Accident Costs in Construction Projects Using Ensemble Data-Driven Models
Xin Xia, Pengcheng Xiang, Sadegh Khanmohammadi, et al.
Journal of Construction Engineering and Management (2024) Vol. 150, Iss. 7
Closed Access | Times Cited: 4
Classification machine learning models for urban flood hazard mapping: case study of Zaio, NE Morocco
Maelaynayn El Baida, Farid Boushaba, Mimoun Chourak, et al.
Natural Hazards (2024) Vol. 120, Iss. 11, pp. 10013-10041
Closed Access | Times Cited: 4
Predicting types of human-related maritime accidents with explanations using selective ensemble learning and SHAP method
He Lan, Shutian Wang, Wenfeng Zhang
Heliyon (2024) Vol. 10, Iss. 9, pp. e30046-e30046
Open Access | Times Cited: 4
Integrated approaches for flash flood susceptibility mapping: spatial modeling and comparative analysis of statistical and machine learning models. A case study of the Rheraya watershed, Morocco
Akram Elghouat, Ahmed Algouti, Abdellah Algouti, et al.
Journal of Water and Climate Change (2024) Vol. 15, Iss. 8, pp. 3624-3646
Open Access | Times Cited: 4
Investigating occupational and operational industrial safety data through Business Intelligence and Machine Learning
Antonio Javier Nakhal Akel, Riccardo Patriarca, Giulio Di Gravio, et al.
Journal of Loss Prevention in the Process Industries (2021) Vol. 73, pp. 104608-104608
Closed Access | Times Cited: 27
Emergency and Disaster Management, Preparedness, and Planning (EDMPP) and the ‘Social’: A Scoping Review
Brielle Lillywhite, Gregor Wolbring
Sustainability (2022) Vol. 14, Iss. 20, pp. 13519-13519
Open Access | Times Cited: 17
A machine learning and data analytics approach for predicting evacuation and identifying contributing factors during hazardous materials incidents on railways
Hadiseh Ebrahimi, Fereshteh Sattari, Lianne Lefsrud, et al.
Safety Science (2023) Vol. 164, pp. 106180-106180
Closed Access | Times Cited: 11
An Application of Machine Learning to Logistics Performance Prediction: An Economics Attribute-Based of Collective Instance
Suriyan Jomthanachai, Wai Peng Wong, Khai Wah Khaw
Computational Economics (2023) Vol. 63, Iss. 2, pp. 741-792
Open Access | Times Cited: 10
An integration of intelligent approaches and economic criteria for predictive analytics of occupational accidents
Kamran Gholamizadeh, Esmaeil Zarei, Mohammad Yazdi, et al.
Decision Analytics Journal (2023) Vol. 9, pp. 100357-100357
Open Access | Times Cited: 10
A hybrid STAMP-fuzzy DEMATEL-ISM approach for analyzing the factors influencing building collapse accidents in China
Xue Chen, Wanguan Qiao
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 10
A deep neural network algorithm-based approach for predicting recovery period of accidents according to construction scale
Ji-Myong Kim, Manik Das Adhikari, Junseo Bae, et al.
Heliyon (2024) Vol. 10, Iss. 11, pp. e32215-e32215
Open Access | Times Cited: 4
Examining safety conditions in the construction sector across Chinese provinces: an input-output analysis
Liangguo Kang
Environment Development and Sustainability (2025)
Closed Access
Comparative Analysis of Deep Learning Algorithms for Predicting Construction Project Delays in Saudi Arabia
Saleh Alsulamy
Applied Soft Computing (2025), pp. 112890-112890
Closed Access
Applications of interpretable ensemble learning for workplace risk assessment: The Chinese coal industry as an example
Qifei Wang, Yong Zhao, Junlong Wang, et al.
Risk Analysis (2025)
Closed Access
Classification of Damage on Wind Turbine Blades Using Automatic Machine Learning and Pressure Coefficient
Javier A. Carmona‐Troyo, Leonardo Trujillo, J. Enríquez‐Zárate, et al.
Expert Systems (2025) Vol. 42, Iss. 4
Closed Access
Enhancing flood susceptibility mapping in Sana’a, Yemen with random forest and eXtreme gradient boosting algorithms
Yahia Alwathaf, Ahmed M. Al‐Areeq, Yousef A. Al-Masnay, et al.
Geocarto International (2025) Vol. 40, Iss. 1
Open Access
A review of machine learning for analysing accident reports in the construction industry
May Shayboun, Dimosthenis Kifokeris, Christian Koch
Journal of Information Technology in Construction (2025) Vol. 30, pp. 439-460
Open Access
Machine learning based risk prediction system for bituminous plant using random forest model
K. Balamurugan, M Manickam, Senthilkumar Duraisamy
AIP conference proceedings (2025) Vol. 3279, pp. 020140-020140
Closed Access
Automated information mining in hazardous chemical accident reporting: An improved deep learning approach
Kai Zhao, L.H Wan, Xilei Lu, et al.
Journal of Loss Prevention in the Process Industries (2025), pp. 105660-105660
Closed Access
MetaInjury: Meta-learning framework for reusing the risk knowledge of different construction accidents
Xin Li, Rongchen Zhu, Han Ye, et al.
Safety Science (2021) Vol. 140, pp. 105315-105315
Closed Access | Times Cited: 23
Big Data Technology in Construction Safety Management: Application Status, Trend and Challenge
Qingfeng Meng, Qiyuan Peng, Zhen Li, et al.
Buildings (2022) Vol. 12, Iss. 5, pp. 533-533
Open Access | Times Cited: 15

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