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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:

State-of-the-Art Review of Machine Learning Applications in Constitutive Modeling of Soils
Pin Zhang, Zhen‐Yu Yin, Yin-Fu Jin
Archives of Computational Methods in Engineering (2021) Vol. 28, Iss. 5, pp. 3661-3686
Closed Access | Times Cited: 105

Showing 1-25 of 105 citing articles:

Integrating BIM and AI for Smart Construction Management: Current Status and Future Directions
Yue Pan, Limao Zhang
Archives of Computational Methods in Engineering (2022) Vol. 30, Iss. 2, pp. 1081-1110
Closed Access | Times Cited: 182
Past, present, and future of virtual tourism-a literature review
Sanjeev Verma, Lekha Warrier, Brajesh Bolia, et al.
International Journal of Information Management Data Insights (2022) Vol. 2, Iss. 2, pp. 100085-100085
Open Access | Times Cited: 124
Deep active learning for constitutive modelling of granular materials: From representative volume elements to implicit finite element modelling
Tongming Qu, Shaoheng Guan, Y.T. Feng, et al.
International Journal of Plasticity (2023) Vol. 164, pp. 103576-103576
Open Access | Times Cited: 45
A physics-informed deep neural network for surrogate modeling in classical elasto-plasticity
Mahdad Eghbalian, Mehdi Pouragha, Richard Wan
Computers and Geotechnics (2023) Vol. 159, pp. 105472-105472
Open Access | Times Cited: 40
Analysis and Prediction of Grouting Reinforcement Performance of Broken Rock Considering Joint Morphology Characteristics
Guanglin Liang, Linchong Huang, Chengyong Cao
Mathematics (2025) Vol. 13, Iss. 2, pp. 264-264
Open Access | Times Cited: 1
Bayesian neural network-based uncertainty modelling: application to soil compressibility and undrained shear strength prediction
Pin Zhang, Zhen‐Yu Yin, Yin‐Fu Jin
Canadian Geotechnical Journal (2021) Vol. 59, Iss. 4, pp. 546-557
Closed Access | Times Cited: 80
A novel deep learning-based modelling strategy from image of particles to mechanical properties for granular materials with CNN and BiLSTM
Pin Zhang, Zhen‐Yu Yin
Computer Methods in Applied Mechanics and Engineering (2021) Vol. 382, pp. 113858-113858
Open Access | Times Cited: 74
Machine Learning-Based Modelling of Soil Properties for Geotechnical Design: Review, Tool Development and Comparison
Pin Zhang, Zhen‐Yu Yin, Yin-Fu Jin
Archives of Computational Methods in Engineering (2021) Vol. 29, Iss. 2, pp. 1229-1245
Closed Access | Times Cited: 61
Physics-Informed Multifidelity Residual Neural Networks for Hydromechanical Modeling of Granular Soils and Foundation Considering Internal Erosion
Pin Zhang, Zhen‐Yu Yin, Yin‐Fu Jin, et al.
Journal of Engineering Mechanics (2022) Vol. 148, Iss. 4
Closed Access | Times Cited: 51
Physics‐constrained hierarchical data‐driven modelling framework for complex path‐dependent behaviour of soils
Pin Zhang, Zhen‐Yu Yin, Yin‐Fu Jin, et al.
International Journal for Numerical and Analytical Methods in Geomechanics (2022) Vol. 46, Iss. 10, pp. 1831-1850
Closed Access | Times Cited: 37
Extensive overview of soil constitutive relations and applications for geotechnical engineering problems
Kennedy C. Onyelowe, Ahmed M. Ebid, Evangelin Ramani Sujatha, et al.
Heliyon (2023) Vol. 9, Iss. 3, pp. e14465-e14465
Open Access | Times Cited: 26
Liquefaction Potential Assessment of Soils Using Machine Learning Techniques: A State-of-the-Art Review from 1994–2021
Kaushik Jas, G. R. Dodagoudar
International Journal of Geomechanics (2023) Vol. 23, Iss. 7
Closed Access | Times Cited: 25
Interpretable data-driven constitutive modelling of soils with sparse data
Pin Zhang, Zhen‐Yu Yin, Brian Sheil
Computers and Geotechnics (2023) Vol. 160, pp. 105511-105511
Closed Access | Times Cited: 23
Neural Networks for Constitutive Modeling: From Universal Function Approximators to Advanced Models and the Integration of Physics
Johannes Dornheim, Lukas Morand, Hemanth Janarthanam Nallani, et al.
Archives of Computational Methods in Engineering (2023) Vol. 31, Iss. 2, pp. 1097-1127
Open Access | Times Cited: 22
Multifidelity Constitutive Modeling of Stress-Induced Anisotropic Behavior of Clay
Pin Zhang, Zhen‐Yu Yin, Brian Sheil
Journal of Geotechnical and Geoenvironmental Engineering (2024) Vol. 150, Iss. 3
Closed Access | Times Cited: 9
Physics-Informed neural network solver for numerical analysis in geoengineering
Xiaoxuan Chen, Pin Zhang, Zhen‐Yu Yin
Georisk Assessment and Management of Risk for Engineered Systems and Geohazards (2024) Vol. 18, Iss. 1, pp. 33-51
Open Access | Times Cited: 9
Artificial intelligence and Machine Learning for Real-world problems (A survey)
Javid Ghahremani-Nahr, Hamed Nozari, Mohammad Ebrahim Sadeghi
International Journal of Innovation in Engineering (2021) Vol. 1, Iss. 3, pp. 38-47
Open Access | Times Cited: 49
Machine learning–based uncertainty modelling of mechanical properties of soft clays relating to time‐dependent behavior and its application
Pin Zhang, Yin‐Fu Jin, Zhen‐Yu Yin
International Journal for Numerical and Analytical Methods in Geomechanics (2021) Vol. 45, Iss. 11, pp. 1588-1602
Open Access | Times Cited: 47
Estimating unconfined compressive strength of unsaturated cemented soils using alternative evolutionary approaches
Navid Kardani, Annan Zhou, Shui‐Long Shen, et al.
Transportation Geotechnics (2021) Vol. 29, pp. 100591-100591
Closed Access | Times Cited: 46
Modelling the mechanical behaviour of soils using machine learning algorithms with explicit formulations
Pin Zhang, Zhen‐Yu Yin, Yin-Fu Jin, et al.
Acta Geotechnica (2021) Vol. 17, Iss. 4, pp. 1403-1422
Closed Access | Times Cited: 46
Spatiotemporal air quality forecasting and health risk assessment over smart city of NEOM
Khalid Elbaz, Ibrahim Hoteit, Wafaa Mohamed Shaban, et al.
Chemosphere (2022) Vol. 313, pp. 137636-137636
Closed Access | Times Cited: 32
Finite element geotechnical analysis incorporating deep learning-based soil model
Qingzheng Guan, Z. X. Yang, Ning Guo, et al.
Computers and Geotechnics (2022) Vol. 154, pp. 105120-105120
Closed Access | Times Cited: 29
Modeling the Mechanical Response of Cement-Admixed Clay Under Different Stress Paths Using Recurrent Neural Networks
Chana Phutthananon, Praiya Ratanakijkul, Sompote Youwai, et al.
International Journal of Geosynthetics and Ground Engineering (2024) Vol. 10, Iss. 2
Closed Access | Times Cited: 6
Multi-hazard could exacerbate in coastal Bangladesh in the context of climate change
Mahfuzur Rahman, Shufeng Tian, Md Sakib Hasan Tumon, et al.
Journal of Cleaner Production (2024) Vol. 457, pp. 142289-142289
Closed Access | Times Cited: 6
Multifidelity-based Gaussian process for quasi-site-specific probabilistic prediction of soil properties
Geng‐Fu He, Pin Zhang, Zhen‐Yu Yin, et al.
Canadian Geotechnical Journal (2024) Vol. 61, Iss. 10, pp. 2304-2322
Closed Access | Times Cited: 5
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