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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:

A Novel Hybrid Soft Computing Model Using Random Forest and Particle Swarm Optimization for Estimation of Undrained Shear Strength of Soil
Binh Thai Pham, Chongchong Qi, Lanh Si Ho, et al.
Sustainability (2020) Vol. 12, Iss. 6, pp. 2218-2218
Open Access | Times Cited: 109

Showing 1-25 of 109 citing articles:

Influence of Data Splitting on Performance of Machine Learning Models in Prediction of Shear Strength of Soil
Quang Hung Nguyen, Haï-Bang Ly, Lanh Si Ho, et al.
Mathematical Problems in Engineering (2021) Vol. 2021, pp. 1-15
Open Access | Times Cited: 468
Predicting TBM penetration rate in hard rock condition: A comparative study among six XGB-based metaheuristic techniques
Jian Zhou, Yingui Qiu, Danial Jahed Armaghani, et al.
Geoscience Frontiers (2020) Vol. 12, Iss. 3, pp. 101091-101091
Open Access | Times Cited: 231
Soft Computing Ensemble Models Based on Logistic Regression for Groundwater Potential Mapping
Phong Tung Nguyen, Duong Hai Ha, Mohammadtaghi Avand, et al.
Applied Sciences (2020) Vol. 10, Iss. 7, pp. 2469-2469
Open Access | Times Cited: 155
Comparison of neural network, Gaussian regression, support vector machine, long short-term memory, multi-gene genetic programming, and M5 Trees methods for solving civil engineering problems
Erdal Uncuoğlu, Hatice Çıtakoğlu, Levent Latifoğlu, et al.
Applied Soft Computing (2022) Vol. 129, pp. 109623-109623
Closed Access | Times Cited: 82
Predicting occurrence of liquefaction-induced lateral spreading using gradient boosting algorithms integrated with particle swarm optimization: PSO-XGBoost, PSO-LightGBM, and PSO-CatBoost
Selçuk Demir, Emrehan Kutluğ Şahin
Acta Geotechnica (2023) Vol. 18, Iss. 6, pp. 3403-3419
Closed Access | Times Cited: 69
InSAR time-series analysis and susceptibility mapping for land subsidence in Semarang, Indonesia using convolutional neural network and support vector regression
Wahyu Luqmanul Hakim, Muhammad Fulki Fadhillah, Sungjae Park, et al.
Remote Sensing of Environment (2023) Vol. 287, pp. 113453-113453
Closed Access | Times Cited: 51
Groundwater Potential Mapping Combining Artificial Neural Network and Real AdaBoost Ensemble Technique: The DakNong Province Case-study, Vietnam
Phong Tung Nguyen, Duong Hai Ha, Abolfazl Jaafari, et al.
International Journal of Environmental Research and Public Health (2020) Vol. 17, Iss. 7, pp. 2473-2473
Open Access | Times Cited: 125
Integrated neuro-swarm heuristic with interior-point for nonlinear SITR model for dynamics of novel COVID-19
Muhammad Umar, Zulqurnain Sabir, Muhammad Asif Zahoor Raja, et al.
Alexandria Engineering Journal (2021) Vol. 60, Iss. 3, pp. 2811-2824
Open Access | Times Cited: 87
Integrated intelligent computing with neuro-swarming solver for multi-singular fourth-order nonlinear Emden–Fowler equation
Zulqurnain Sabir, Muhammad Asif Zahoor Raja, Juan L. G. Guirao, et al.
Computational and Applied Mathematics (2020) Vol. 39, Iss. 4
Closed Access | Times Cited: 83
Computational Hybrid Machine Learning Based Prediction of Shear Capacity for Steel Fiber Reinforced Concrete Beams
Haï-Bang Ly, Tien-Thinh Le, Huong-Lan Thi Vu, et al.
Sustainability (2020) Vol. 12, Iss. 7, pp. 2709-2709
Open Access | Times Cited: 82
Assessing agricultural salt-affected land using digital soil mapping and hybridized random forests
Kamal Nabiollahi, Ruhollah Taghizadeh–Mehrjardi, Aram Shahabi, et al.
Geoderma (2020) Vol. 385, pp. 114858-114858
Closed Access | Times Cited: 82
Risk Assessment of Resources Exposed to Rainfall Induced Landslide with the Development of GIS and RS Based Ensemble Metaheuristic Machine Learning Algorithms
Javed Mallick, Saeed Alqadhi, Swapan Talukdar, et al.
Sustainability (2021) Vol. 13, Iss. 2, pp. 457-457
Open Access | Times Cited: 58
Random forest and nature-inspired algorithms for mapping groundwater nitrate concentration in a coastal multi-layer aquifer system
Quoc Bao Pham, Dang An Tran, Nam Thang Ha, et al.
Journal of Cleaner Production (2022) Vol. 343, pp. 130900-130900
Closed Access | Times Cited: 44
Estimation of unconfined compressive strength of marine clay modified with recycled tiles using hybridized extreme gradient boosting method
Daihong Li, Xiaoyu Zhang, Qian Kang, et al.
Construction and Building Materials (2023) Vol. 393, pp. 131992-131992
Closed Access | Times Cited: 31
Implementing ensemble learning models for the prediction of shear strength of soil
Ahsan Rabbani, Pijush Samui, Sunita Kumari
Asian Journal of Civil Engineering (2023) Vol. 24, Iss. 7, pp. 2103-2119
Closed Access | Times Cited: 29
A swarming neural network computing approach to solve the Zika virus model
Zulqurnain Sabir, Shahid Ahmad Bhat, Muhammad Asif Zahoor Raja, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 126, pp. 106924-106924
Open Access | Times Cited: 29
Optimizing the environmental design and management of public green spaces: Analyzing urban infrastructure and long-term user experience with a focus on streetlight density in the city of Las Vegas, NV
Xiwei Shen, Jie Kong, Yang Song, et al.
Information Fusion (2025) Vol. 118, pp. 102914-102914
Closed Access | Times Cited: 1
Enhancing undrained shear strength prediction: a robust hybrid machine learning approach with naïve Bayes modeling
Fang Chen, Ying Li, Shi Yang
Journal of Engineering and Applied Science (2025) Vol. 72, Iss. 1
Open Access | Times Cited: 1
Improved prediction of soil shear strength using machine learning algorithms: interpretability analysis using SHapley Additive exPlanations
Mahmood Ahmad, Mohammad Al-Zubi, Hamad Almujibah, et al.
Frontiers in Earth Science (2025) Vol. 13
Open Access | Times Cited: 1
Machine Learning as an Innovative Engineering Tool for Controlling Concrete Performance: A Comprehensive Review
Fatemeh Mobasheri, Masoud Hosseinpoor, Ammar Yahia, et al.
Archives of Computational Methods in Engineering (2025)
Closed Access | Times Cited: 1
Design deep neural network architecture using a genetic algorithm for estimation of pile bearing capacity
Tuan Anh Pham, Van Quan Tran, Huong-Lan Thi Vu, et al.
PLoS ONE (2020) Vol. 15, Iss. 12, pp. e0243030-e0243030
Open Access | Times Cited: 68
Soft-computing techniques for prediction of soils consolidation coefficient
Manh Duc Nguyen, Binh Thai Pham, Lanh Si Ho, et al.
CATENA (2020) Vol. 195, pp. 104802-104802
Closed Access | Times Cited: 55
A Survey on Applications of Artificial Intelligence for Pre-Parametric Project Cost and Soil Shear-Strength Estimation in Construction and Geotechnical Engineering
Sparsh Sharma, Suhaib Ahmed, Mohd Naseem, et al.
Sensors (2021) Vol. 21, Iss. 2, pp. 463-463
Open Access | Times Cited: 55
Application of Artificial Intelligence to Determined Unconfined Compressive Strength of Cement-Stabilized Soil in Vietnam
Huong Thi Thanh Ngo, Tuan Anh Pham, Huong Vu, et al.
Applied Sciences (2021) Vol. 11, Iss. 4, pp. 1949-1949
Open Access | Times Cited: 50
Proposing receiver operating characteristic-based sensitivity analysis with introducing swarm optimized ensemble learning algorithms for groundwater potentiality modelling in Asir region, Saudi Arabia
Javed Mallick, Swapan Talukdar, Majed Alsubih, et al.
Geocarto International (2021) Vol. 37, Iss. 15, pp. 4361-4389
Closed Access | Times Cited: 44
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