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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:

Buckling response of CNT based hybrid FG plates using finite element method and machine learning method
Ravi Kumar, Ajay Kumar, Divesh Ranjan Kumar
Composite Structures (2023) Vol. 319, pp. 117204-117204
Closed Access | Times Cited: 24

Showing 24 citing articles:

Application of Machine Learning and Deep Learning in Finite Element Analysis: A Comprehensive Review
Dipjyoti Nath, Ankit, Debanga Raj Neog, et al.
Archives of Computational Methods in Engineering (2024) Vol. 31, Iss. 5, pp. 2945-2984
Closed Access | Times Cited: 21
Tribological properties of CNT-filled epoxy-carbon fabric composites: Optimization and modelling by machine learning
M. D. Kiran, B.R. Lokesh Yadhav, Atul Babbar, et al.
Journal of Materials Research and Technology (2023) Vol. 28, pp. 2582-2601
Open Access | Times Cited: 21
Nanotechnological advances in cancer: therapy a comprehensive review of carbon nanotube applications
Siyang Gao, Binhan Xu, Jianwei Sun, et al.
Frontiers in Bioengineering and Biotechnology (2024) Vol. 12
Open Access | Times Cited: 13
State-of-the-art XGBoost, RF and DNN based soft-computing models for PGPN piles
Manish Kumar, Pijush Samui, Divesh Ranjan Kumar, et al.
Geomechanics and Geoengineering (2024) Vol. 19, Iss. 6, pp. 975-990
Closed Access | Times Cited: 12
A novel approach to estimate rock deformation under uniaxial compression using a machine learning technique
Thalappil Pradeep, Divesh Ranjan Kumar, Manish Kumar, et al.
Bulletin of Engineering Geology and the Environment (2024) Vol. 83, Iss. 7
Closed Access | Times Cited: 10
Soft computing-based prediction models for compressive strength of concrete
Manish Kumar, Rahul Biswas, Divesh Ranjan Kumar, et al.
Case Studies in Construction Materials (2023) Vol. 19, pp. e02321-e02321
Open Access | Times Cited: 18
Liquefaction susceptibility using machine learning based on SPT data
Divesh Ranjan Kumar, Pijush Samui, Avijit Burman, et al.
Intelligent Systems with Applications (2023) Vol. 20, pp. 200281-200281
Open Access | Times Cited: 16
Performance Evaluation and Triangle Diagram of Deep Learning Models for Embedment Depth Prediction in Cantilever Sheet Piles
Thalappil Pradeep, Divesh Ranjan Kumar, Nitish Kumar, et al.
Engineered Science (2024)
Open Access | Times Cited: 6
XGBoost and genetic programming methods for analysing the vitreous transition of the epoxy adhesive
Songbo Wang, Yaqiong Cai, Jun Su, et al.
Journal of Adhesion Science and Technology (2025), pp. 1-26
Closed Access
Finite Element and Machine Learning-Based Prediction of Buckling Strength in Additively Manufactured Lattice Stiffened Panels
Saiaf Bin Rayhan, Md Mazedur Rahman, Jakiya Sultana, et al.
Metals (2025) Vol. 15, Iss. 1, pp. 81-81
Open Access
BGG-REPT and ROF-REPT: ensemble machine learning models for the prediction of compressive strength of concrete
Binh Thai Pham
Innovative Infrastructure Solutions (2025) Vol. 10, Iss. 2
Closed Access
Advancements in CNT research: Integrating machine learning with microscopic simulations, macroscopic techniques, and application of performance prediction and functional optimization
Dianming Chu, Chenyu Gao, Zongchao Ji, et al.
Materials Today Chemistry (2025) Vol. 45, pp. 102616-102616
Closed Access
Accelerating Finite Element Simulation of Metallic Glasses Using Data-Driven Constitutive Models Trained by Deep Neural Networks
Bo Pang, Zhilin Long, Tao Long, et al.
Materials Today Communications (2025), pp. 112252-112252
Closed Access
Bearing Capacity of Eccentrically Loaded Footings on Rock Masses Using Soft Computing Techniques
Divesh Ranjan Kumar, Pijush Samui, Warit Wipulanusat, et al.
Engineered Science (2023)
Open Access | Times Cited: 11
Machine learning approaches for prediction of the bearing capacity of ring foundations on rock masses
Divesh Ranjan Kumar, Pijush Samui, Warit Wipulanusat, et al.
Earth Science Informatics (2023) Vol. 16, Iss. 4, pp. 4153-4168
Closed Access | Times Cited: 11
Appraisal of numerous machine learning techniques for the prediction of bearing capacity of strip footings subjected to inclined loading
Rashid Mustafa, Pijush Samui, Sunita Kumari, et al.
Modeling Earth Systems and Environment (2024) Vol. 10, Iss. 3, pp. 4067-4088
Closed Access | Times Cited: 3
Soft computing-based reliability analysis of simply supported beam: a comparative study of hybrid ANN models
Abhishek Kumar, Baboo Rai, Pijush Samui
Asian Journal of Civil Engineering (2024) Vol. 25, Iss. 4, pp. 3151-3166
Closed Access | Times Cited: 2
State-of-the-art advanced hybrid ANNs paradigm for assessment and prediction of slope stability
Nitish Kumar, Sunita Kumari
Multiscale and Multidisciplinary Modeling Experiments and Design (2024) Vol. 7, Iss. 4, pp. 3483-3509
Closed Access | Times Cited: 2
ANN- PSO modelling for predicting buckling of self-compacting concrete column containing RHA properties
Abdul Bari Jabar, T. Pradeep
Matéria (Rio de Janeiro) (2023) Vol. 28, Iss. 2
Open Access | Times Cited: 5
Analytical Solution of Stability Problem of Nanocomposite Cylindrical Shells under Combined Loadings in Thermal Environments
Mahmure Avey, Nicholas Fantuzzi, A.H. Sofiyev
Mathematics (2023) Vol. 11, Iss. 17, pp. 3781-3781
Open Access | Times Cited: 5
Vibration behavior prediction of submerged nanobeams with axially traveling supports: numerical, analytical, and machine learning approaches
Xiaolan Chen
Mechanics Based Design of Structures and Machines (2024) Vol. 52, Iss. 12, pp. 10273-10303
Closed Access | Times Cited: 1
Application of Advanced Machine Learning Models for Uplift and Penetration Resistance in Clay-Embedded Dual Interfering Pipelines
Divesh Ranjan Kumar, Warit Wipulanusat, Suraparb Keawsawasvong
Modeling Earth Systems and Environment (2024) Vol. 10, Iss. 5, pp. 6493-6517
Closed Access | Times Cited: 1
Machine Learning and Optimization Algorithms for Vibration, Bending and Buckling Analyses of Composite/Nanocomposite Structures: A Systematic and Comprehensive Review
Dervis Baris Ercument, Babak Safaei, Saeid Sahmani, et al.
Archives of Computational Methods in Engineering (2024)
Closed Access | Times Cited: 1
Inverse design of composite xylophone beams using finite element-based machine learning
Tatsuro Kimura, Ming Ji, Ryu Onodera, et al.
Discover Mechanical Engineering (2023) Vol. 2, Iss. 1
Open Access | Times Cited: 2
A nonlocal strain gradient model for buckling analysis of laminated composite nanoplates using CLPT and TSDT
P. Aurojyoti, Konda Shiva, P. Raghu, et al.
Meccanica (2023)
Closed Access
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