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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:

Prediction of maximum tensile stress in plain-weave composite laminates with interacting holes via stacked machine learning algorithms: A comparative study
Faramarz Bagherzadeh, Torkan Shafighfard, Raja Muhammad Awais Khan, et al.
Mechanical Systems and Signal Processing (2023) Vol. 195, pp. 110315-110315
Closed Access | Times Cited: 66

Showing 1-25 of 66 citing articles:

Spatiotemporal heterogeneity of ecosystem service interactions and their drivers at different spatial scales in the Yellow River Basin
Qi Liu, Jiajun Qiao, Mengjuan Li, et al.
The Science of The Total Environment (2023) Vol. 908, pp. 168486-168486
Closed Access | Times Cited: 68
Machine-learning methods for estimating compressive strength of high-performance alkali-activated concrete
Torkan Shafighfard, Farzin Kazemi, Neda Asgarkhani, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 136, pp. 109053-109053
Closed Access | Times Cited: 52
Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams
Torkan Shafighfard, Farzin Kazemi, Faramarz Bagherzadeh, et al.
Computer-Aided Civil and Infrastructure Engineering (2024) Vol. 39, Iss. 23, pp. 3573-3594
Open Access | Times Cited: 49
Data-Driven Modeling of Mechanical Properties of Fiber-Reinforced Concrete: A Critical Review
Farzin Kazemi, Torkan Shafighfard, Doo‐Yeol Yoo
Archives of Computational Methods in Engineering (2024) Vol. 31, Iss. 4, pp. 2049-2078
Closed Access | Times Cited: 46
Machine-Learning Methods for Estimating Performance of Structural Concrete Members Reinforced with Fiber-Reinforced Polymers
Farzin Kazemi, Neda Asgarkhani, Torkan Shafighfard, et al.
Archives of Computational Methods in Engineering (2024)
Open Access | Times Cited: 30
Enhancing wastewater treatment efficiency through machine learning-driven effluent quality prediction: A plant-level analysis
Maria Alice Prado Cechinel, Juliana Neves, João Vitor Rios Fuck, et al.
Journal of Water Process Engineering (2024) Vol. 58, pp. 104758-104758
Closed Access | Times Cited: 15
RAGN-R: A multi-subject ensemble machine-learning method for estimating mechanical properties of advanced structural materials
Farzin Kazemi, Aybike Özyüksel Çiftçioğlu, Torkan Shafighfard, et al.
Computers & Structures (2025) Vol. 308, pp. 107657-107657
Closed Access | Times Cited: 2
Bettered Strength and Fracture Behavior of Plain Weave CFRE Laminate with Open Hole under the Influence of Hole Shape/Size and Strain Rate
Rzgar M. Abdalrahman, Sarkawt Rostam, Hameed D. Lafta
Results in Engineering (2025) Vol. 25, pp. 103906-103906
Open Access | Times Cited: 1
Grey wolf optimizer integrated within boosting algorithm: Application in mechanical properties prediction of ultra high-performance concrete including carbon nanotubes
Aybike Özyüksel Çiftçioğlu, Farzin Kazemi, Torkan Shafighfard
Applied Materials Today (2025) Vol. 42, pp. 102601-102601
Closed Access | Times Cited: 1
Design and implementation of the adaptive vibration control for bolted composite plates under variable loads
Yu Zhang, Wei Sun, Hui Zhang, et al.
Mechanical Systems and Signal Processing (2025) Vol. 229, pp. 112496-112496
Closed Access | Times Cited: 1
A systematic review of deep learning approaches for surface defect detection in industrial applications
Rasoul Ameri, Chung-Chian Hsu, Shahab S. Band
Engineering Applications of Artificial Intelligence (2023) Vol. 130, pp. 107717-107717
Closed Access | Times Cited: 27
Graph neural network-based bearing fault diagnosis using Granger causality test
Zhewen Zhang, Lifeng Wu
Expert Systems with Applications (2023) Vol. 242, pp. 122827-122827
Closed Access | Times Cited: 26
The Impact of Artificial Intelligence on Organizational Justice and Project Performance: A Systematic Literature and Science Mapping Review
Xinran Zhang, Maxwell Fordjour Antwi‐Afari, Yongcheng Zhang, et al.
Buildings (2024) Vol. 14, Iss. 1, pp. 259-259
Open Access | Times Cited: 13
Active learning on stacked machine learning techniques for predicting compressive strength of alkali-activated ultra-high-performance concrete
Farzin Kazemi, Torkan Shafighfard, Robert Jankowski, et al.
Archives of Civil and Mechanical Engineering (2024) Vol. 25, Iss. 1
Open Access | Times Cited: 10
Machine learning approach to evaluating impact behavior in fabric-laminated composite materials
Shivashankar Hiremath, Yu Zhang, Lu Zhang, et al.
Results in Engineering (2024) Vol. 23, pp. 102576-102576
Open Access | Times Cited: 8
Application of Machine Learning (ML)-based multi-classifications to identify corrosion fatigue cracking phenomena in Naval steel weldments
Vivek Srivastava, B. N. Basu, N. Prabhu
Materials Today Communications (2024) Vol. 39, pp. 108591-108591
Closed Access | Times Cited: 7
A vulnerability evaluation method of earthen sites based on entropy weight-TOPSIS and K-means clustering
Ningbo Peng, Chaokai Zhang, Ye Zhu, et al.
Heritage Science (2024) Vol. 12, Iss. 1
Open Access | Times Cited: 7
An Adaptive Security Framework for Internet of Things Networks Leveraging SDN and Machine Learning
Ala Hamarsheh
Applied Sciences (2024) Vol. 14, Iss. 11, pp. 4530-4530
Open Access | Times Cited: 7
Experimental and Mesoscopic Simulation Study of Size Effect on Splitting Tensile Performance of Spontaneous-combustion Coal Gangue Concrete
Jiaqi Jiang, Haiqing Liu, Jinli Wang
Journal of Building Engineering (2024) Vol. 92, pp. 109677-109677
Closed Access | Times Cited: 5
Leveraging machine learning to minimize experimental trials and predict hot deformation behaviour in dual phase high entropy alloys
Sandeep Jain, Reliance Jain, K. Raja Rao, et al.
Materials Today Communications (2024), pp. 110813-110813
Closed Access | Times Cited: 5
Inspection of cracking in stamping parts surfaces using anomaly detection
Xingjun Dong, Changsheng Zhang, Dawei Wang, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 143, pp. 110006-110006
Closed Access
Development of Robust Machine Learning Models for Predicting Flexural Strengths of Fiber-Reinforced Polymeric Composites
Abdulhammed K. Hamzat, Umar Salman, Md Shafinur Murad, et al.
Hybrid Advances (2025), pp. 100385-100385
Open Access
Investigation of particle deposition characteristics in flue gas heat exchanger with variable-direction twisted-oval tubes
Songzhen Tang, Liang Ding, Junjie Zhou, et al.
Applied Thermal Engineering (2025), pp. 125617-125617
Closed Access
Predicting mechanical properties of RX4E electric aircraft wing composite panels using deep learning
Jian Zang, Duo Xu, Kang Yang, et al.
Mechanical Systems and Signal Processing (2025) Vol. 227, pp. 112398-112398
Closed Access
Machine Learning Techniques for Estimating High–Temperature Mechanical Behavior of High Strength Steels
Cüneyt Yazıcı, F. J. Domínguez-Gutiérrez
Results in Engineering (2025) Vol. 25, pp. 104242-104242
Closed Access
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