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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:

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

Showing 1-25 of 46 citing articles:

Optimized machine learning modelling for predicting the construction cost and duration of tunnelling projects
Arsalan Mahmoodzadeh, Hamid Reza Nejati, Mokhtar Mohammadi
Automation in Construction (2022) Vol. 139, pp. 104305-104305
Closed Access | Times Cited: 45
Use of machine learning for classification of sand particles
Linzhu Li, Magued Iskander
Acta Geotechnica (2022) Vol. 17, Iss. 10, pp. 4739-4759
Closed Access | Times Cited: 37
An enhanced deep learning method for accurate and robust modelling of soil stress–strain response
Ning Zhang, Annan Zhou, Yin‐Fu Jin, et al.
Acta Geotechnica (2023) Vol. 18, Iss. 8, pp. 4405-4427
Closed Access | Times Cited: 34
Utilizing undisturbed soil sampling approach to predict elastic modulus of cohesive soils: a Gaussian process regression model
Muhammad Naqeeb Nawaz, Muhammad Hasnain Ayub Khan, Waqas Hassan, et al.
Multiscale and Multidisciplinary Modeling Experiments and Design (2024) Vol. 7, Iss. 4, pp. 4255-4270
Closed Access | Times Cited: 11
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
State-of-the-art review on the use of AI-enhanced computational mechanics in geotechnical engineering
Hongchen Liu, Huaizhi Su, Lizhi Sun, et al.
Artificial Intelligence Review (2024) Vol. 57, Iss. 8
Open Access | Times Cited: 5
Uncertainty quantification in tree structure and polynomial regression algorithms toward material indices prediction
Geng‐Fu He, Pin Zhang, Zhen‐Yu Yin
Data-Centric Engineering (2025) Vol. 6
Open Access
A predictive deep learning framework for path-dependent mechanical behavior of granular materials
Gang Ma, Shaoheng Guan, Qiao Wang, et al.
Acta Geotechnica (2022) Vol. 17, Iss. 8, pp. 3463-3478
Closed Access | Times Cited: 24
Developing six hybrid machine learning models based on gaussian process regression and meta-heuristic optimization algorithms for prediction of duration and cost of road tunnels construction
Arsalan Mahmoodzadeh, Hamid Reza Nejati, Mokhtar Mohammadi, et al.
Tunnelling and Underground Space Technology (2022) Vol. 130, pp. 104759-104759
Closed Access | Times Cited: 23
Data-driven constitutive modelling of granular soils considering multiscale particle morphology
Wei Xiong, Jianfeng Wang, Mengmeng Wu
Computers and Geotechnics (2023) Vol. 162, pp. 105699-105699
Closed Access | Times Cited: 14
Soil parameter inversion modeling using deep learning algorithms and its application to settlement prediction: a comparative study
Anfeng Hu, Senlin Xie, Tang Li, et al.
Acta Geotechnica (2023) Vol. 18, Iss. 10, pp. 5597-5618
Closed Access | Times Cited: 13
Principal component analysis–artificial neural network-based model for predicting the static strength of seasonally frozen soils
Yiqiang Sun, Shijie Zhou, Shangjiu Meng, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 13
Ensemble Learning Methods for Shear Strength Prediction of Fly Ash-Amended Soils with Lignin Reinforcement
Weihang Chen, Shujun Qu, Luo-bin Lin, et al.
Journal of Materials in Civil Engineering (2023) Vol. 35, Iss. 4
Closed Access | Times Cited: 12
Utilizing DEM and interpretable ML algorithms to examine particle size distribution's role in small-strain shear modulus of gap-graded granular mixtures
Xingyang Liu, Jiaqi Yang, Degao Zou, et al.
Construction and Building Materials (2024) Vol. 428, pp. 136232-136232
Closed Access | Times Cited: 4
A novel FDEM-GSA method with applications in deformation and damage analysis of surrounding rock in deep-buried tunnels
Huanling Wang, Yizhe Wu, Mei Li, et al.
Tunnelling and Underground Space Technology (2024) Vol. 154, pp. 106106-106106
Closed Access | Times Cited: 4
Efficient automatic estimation of soil constitutive model parameters via particle swarm optimization
Takayuki Sakai, Masaki Nakano
Acta Geotechnica (2025)
Open Access
Machine learning for time series prediction of valley deformation induced by impoundment for high arch dams
Hang‐Hang Zang, Dianqing Li, Xiaosong Tang, et al.
Bulletin of Engineering Geology and the Environment (2025) Vol. 84, Iss. 4
Closed Access
Evaluation of empirical and machine learning models for predicting shear wave velocity of granular soils based on laboratory element tests
Zohreh Mousavi, Meysam Bayat, Jun Yang, et al.
Soil Dynamics and Earthquake Engineering (2024) Vol. 183, pp. 108805-108805
Closed Access | Times Cited: 3
A unified critical state parameter model for sand and overconsolidated clay in the framework of subloading surface theory
Kai Cui, Xiaowen Wang, Ran Yuan, et al.
Canadian Geotechnical Journal (2023) Vol. 60, Iss. 10, pp. 1461-1474
Closed Access | Times Cited: 9
Theory-guided machine learning to predict density evolution of sand dynamically compacted under Ko condition
Amir Tophel, Jeffrey P. Walker, Troyee Tanu Dutta, et al.
Acta Geotechnica (2022) Vol. 17, Iss. 8, pp. 3479-3497
Closed Access | Times Cited: 14
Advancements in Understanding Interface Friction: A Combined Experimental and Machine Learning Approach Using Multiple Linear and Random Forest Regressions
Firas Daghistani, Hossam Abuel-Naga
Geotechnics (2024) Vol. 4, Iss. 1, pp. 109-126
Open Access | Times Cited: 2
Machine Learning Models for Predicting Shear Wave Velocity of Soils
Zohreh Mousavi, Meysam Bayat, Wei-Qiang Feng
IOP Conference Series Earth and Environmental Science (2024) Vol. 1334, Iss. 1, pp. 012039-012039
Open Access | Times Cited: 2
Application of ANN for prediction of settlement of ring foundation
Dipendra C. Swarnkar, Akhileshwar Kumar Singh, Kumar Shubham
Signal Image and Video Processing (2024) Vol. 18, Iss. 11, pp. 7537-7554
Closed Access | Times Cited: 2
Thermal and mechanical characteristics of recycled concrete aggregates mixed with plastic wastes: experimental investigation and mathematical modeling
Behnam Ghorbani, Ehsan Yaghoubi, Arul Arulrajah
Acta Geotechnica (2021) Vol. 17, Iss. 7, pp. 3017-3032
Closed Access | Times Cited: 16
Machine learning models to estimate stress wave velocities of cohesionless soils during triaxial compression influenced by particle characteristics
Amir Tophel, Troyee Tanu Dutta, M. Otsubo, et al.
Soil Dynamics and Earthquake Engineering (2022) Vol. 165, pp. 107649-107649
Closed Access | Times Cited: 11
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