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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:

Automatic calibration of the groundwater simulation model with high parameter dimensionality using sequential uncertainty fitting approach
Fariborz Masoumi, Saeid Najjar‐Ghabel, Akbar Safarzadeh, et al.
Water Science & Technology Water Supply (2020) Vol. 20, Iss. 8, pp. 3487-3501
Open Access | Times Cited: 87

Showing 1-25 of 87 citing articles:

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
Accurate compressive strength prediction using machine learning algorithms and optimization techniques
Wenbin Lan
Journal of Engineering and Applied Science (2024) Vol. 71, Iss. 1
Open Access | Times Cited: 6
Strength properties prediction of RCA concrete via hybrid regression framework
Linlin Yu
Journal of Engineering and Applied Science (2024) Vol. 71, Iss. 1
Open Access | Times Cited: 4
Support Vector Machine to Predict the Pile Settlement using Novel Optimization Algorithm
Qingyun Ge, Caimei Li, Fulian Yang
Geotechnical and Geological Engineering (2023) Vol. 41, Iss. 7, pp. 3861-3875
Closed Access | Times Cited: 10
Implementing a radial basis function model to anticipate the outcomes of the gasification
Hong‐Liang Cui, Ning Su, Hongyan Cui
Chemical Product and Process Modeling (2025) Vol. 20, Iss. 1, pp. 57-78
Closed Access
Random Forest model for precise cooling load estimation in optimized and non-optimized form
Lei Wang, Hongmei Gu, Qingqing Zhang
Chemical Product and Process Modeling (2025)
Closed Access
Estimating the ultra-high-performance concrete compressive strength with a machine learning model via meta-heuristic algorithms
Bing Liu
Multiscale and Multidisciplinary Modeling Experiments and Design (2023) Vol. 7, Iss. 3, pp. 1807-1818
Closed Access | Times Cited: 9
A Critical Review of the Modelling Tools for the Reactive Transport of Organic Contaminants
Katarzyna Samborska-Goik, Marta Pogrzeba
Applied Sciences (2024) Vol. 14, Iss. 9, pp. 3675-3675
Open Access | Times Cited: 3
Predict the compressive strength of ultra high-performance concrete by a hybrid method of machine learning
Nana Gong, Naimin Zhang
Journal of Engineering and Applied Science (2023) Vol. 70, Iss. 1
Open Access | Times Cited: 8
Estimation of Heating Load Consumption in Residual Buildings using Optimized Regression Models Based on Support Vector Machine
Chao Wang, Xuehui QIU
International Journal of Advanced Computer Science and Applications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 2
Optimized systems of multi-layer perceptron predictive model for estimating pile-bearing capacity
Yaoyang Shen
Journal of Engineering and Applied Science (2024) Vol. 71, Iss. 1
Open Access | Times Cited: 2
Efficiency of Hybrid Decision Tree Algorithms in Evaluating the Academic Performance of Students
Yanxin Xie
International Journal of Advanced Computer Science and Applications (2024) Vol. 15, Iss. 2
Open Access | Times Cited: 2
Estimating the mechanical properties of high-performance concrete via automated and ensembled machine learning methods
Xiaohua Liu, Yu Zhang, Lei Song, et al.
Materials Today Communications (2023) Vol. 37, pp. 107386-107386
Closed Access | Times Cited: 6
Employing the optimization algorithms with machine learning framework to estimate the compressive strength of ultra-high-performance concrete (UHPC)
Yajing Zhang, Sai An, Hao Liu
Multiscale and Multidisciplinary Modeling Experiments and Design (2023) Vol. 7, Iss. 1, pp. 97-108
Closed Access | Times Cited: 5
Predicting the settlement of pile based on a hybrid form of the model by considering Least Square Support Vector Regression
Qiang Chen
Multiscale and Multidisciplinary Modeling Experiments and Design (2023) Vol. 7, Iss. 1, pp. 529-542
Closed Access | Times Cited: 5
Novel hybrid AOA and ALO optimized supervised machine learning approaches to predict the compressive strength of admixed concrete containing fly ash and micro-silica
Weixiang Zhu, Lihua Huang, Zhijun Zhang
Multiscale and Multidisciplinary Modeling Experiments and Design (2022) Vol. 5, Iss. 4, pp. 391-402
Closed Access | Times Cited: 9
Estimating high-performance concrete compressive strength with support vector regression in hybrid method
Li Wang
Multiscale and Multidisciplinary Modeling Experiments and Design (2023) Vol. 7, Iss. 1, pp. 477-490
Closed Access | Times Cited: 4
Prediction of compressive strength of concrete for high-performance concrete using two combined models, SVR-AVOA and SVR-SSA
Baorong Ding, Qiong Wang, Yue Ma, et al.
Multiscale and Multidisciplinary Modeling Experiments and Design (2023) Vol. 7, Iss. 2, pp. 961-974
Closed Access | Times Cited: 4
A Novel Approach Using Hybrid Fuzzy Vertex Method-MATLAB Framework Based on GMS Model for Quantifying Predictive Uncertainty Associated with Groundwater Flow and Transport Models
M. R. Nemati, Mahmoud Mohammad Rezapour Tabari, Seyed Abbas Hosseini, et al.
Water Resources Management (2021) Vol. 35, Iss. 12, pp. 4189-4215
Closed Access | Times Cited: 10
Novel hybrid HGSO optimized supervised machine learning approaches to predict the compressive strength of admixed concrete containing fly ash and micro-silica
Liangliang Chen, Fenghua Liu, Fufei Wu
Engineering Research Express (2022) Vol. 4, Iss. 2, pp. 025022-025022
Open Access | Times Cited: 7
Estimation of compressive strength and slump of HPC concrete using neural network coupling with metaheuristic algorithms
Wenqiao Li, Ruijie Wang, Qisheng Ai, et al.
Journal of Intelligent & Fuzzy Systems (2023) Vol. 45, Iss. 1, pp. 577-591
Closed Access | Times Cited: 4
Incorporation of radial basis function with Gorilla Troops Optimization and Moth-Flame Optimization to predict the compressive strength of high-performance concrete
Jin Zhao, Tingting Wu, Jun Li, et al.
Multiscale and Multidisciplinary Modeling Experiments and Design (2023) Vol. 7, Iss. 1, pp. 69-82
Closed Access | Times Cited: 4
Artificial rabbit optimization‐based ANFIS model development for predicting the compressive strength of GGBFS‐based concrete
Qingmei Sun
Structural Concrete (2023) Vol. 25, Iss. 1, pp. 334-348
Closed Access | Times Cited: 4
Optimal boosting method of HPC concrete compressive and tensile strength prediction
Chao Xu
Structural Concrete (2023) Vol. 25, Iss. 1, pp. 283-302
Open Access | Times Cited: 4
Automated machine learning techniques for estimating of elastic modulus of recycled aggregate concrete
Chen Chien‐Ta, Tsai Shing‐Wen, Hsiao Liang‐Hao
Structural Concrete (2023) Vol. 25, Iss. 2, pp. 1324-1342
Closed Access | Times Cited: 4
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