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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:

High performance prediction of soil compaction parameters using multi expression programming
Hanlin Wang, Zhen‐Yu Yin
Engineering Geology (2020) Vol. 276, pp. 105758-105758
Open Access | Times Cited: 128

Showing 1-25 of 128 citing articles:

Predicting the compaction characteristics of expansive soils using two genetic programming-based algorithms
Fazal E. Jalal, Yongfu Xu, Mudassir Iqbal, et al.
Transportation Geotechnics (2021) Vol. 30, pp. 100608-100608
Closed Access | Times Cited: 142
Prediction of compaction parameters for fine-grained soil: Critical comparison of the deep learning and standalone models
Jitendra Khatti, Kamaldeep Singh Grover
Journal of Rock Mechanics and Geotechnical Engineering (2023) Vol. 15, Iss. 11, pp. 3010-3038
Open Access | Times Cited: 64
Development of predictive models for sustainable concrete via genetic programming-based algorithms
Lingling Chen, Zhiyuan Wang, Aftab Ahmad Khan, et al.
Journal of Materials Research and Technology (2023) Vol. 24, pp. 6391-6410
Open Access | Times Cited: 47
Assessment of fine-grained soil compaction parameters using advanced soft computing techniques
Jitendra Khatti, Kamaldeep Singh Grover
Arabian Journal of Geosciences (2023) Vol. 16, Iss. 3
Closed Access | Times Cited: 45
Prediction of soil compaction parameters through the development and experimental validation of Gaussian process regression models
Muhammad Hasnain Ayub Khan, Turab H. Jafri, Sameer Ud-Din, et al.
Environmental Earth Sciences (2024) Vol. 83, Iss. 4
Closed Access | Times Cited: 18
Predictive modelling of cohesion and friction angle of soil using gene expression programming: a step towards smart and sustainable construction
Muhammad Naqeeb Nawaz, Badee Alshameri, Zain Maqsood, et al.
Neural Computing and Applications (2024) Vol. 36, Iss. 18, pp. 10545-10566
Closed Access | Times Cited: 18
Multivariate formulation to predict the frictional strength of fiber reinforced soils using gene expression programming
Muhammad Naqeeb Nawaz, Ahmed Yar Akhtar, Tariq Ahmed Awan, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 134, pp. 108660-108660
Closed Access | Times Cited: 16
ELM-based adaptive neuro swarm intelligence techniques for predicting the California bearing ratio of soils in soaked conditions
Abidhan Bardhan, Pijush Samui, Kuntal Ghosh, et al.
Applied Soft Computing (2021) Vol. 110, pp. 107595-107595
Closed Access | Times Cited: 86
Efficient computational techniques for predicting the California bearing ratio of soil in soaked conditions
Abidhan Bardhan, Candan Gökçeoğlu, Avijit Burman, et al.
Engineering Geology (2021) Vol. 291, pp. 106239-106239
Closed Access | Times Cited: 85
Analytical approach to predict tunneling-induced subsurface settlement in sand considering soil arching effect
Renpeng Chen, Xu Song, Fan‐Yan Meng, et al.
Computers and Geotechnics (2021) Vol. 141, pp. 104492-104492
Closed Access | Times Cited: 65
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
Prediction of ultimate bearing capacity of shallow foundations on cohesionless soil using hybrid LSTM and RVM approaches: An extended investigation of multicollinearity
Jitendra Khatti, Kamaldeep Singh Grover, Hyeong-Joo Kim, et al.
Computers and Geotechnics (2023) Vol. 165, pp. 105912-105912
Closed Access | Times Cited: 37
Evolutionary and ensemble machine learning predictive models for evaluation of water quality
Ali Aldrees, Muhammad Faisal Javed, Abubakr Taha Bakheit Taha, et al.
Journal of Hydrology Regional Studies (2023) Vol. 46, pp. 101331-101331
Open Access | Times Cited: 34
Optimizing compressive strength prediction models for rice husk ash concrete with evolutionary machine intelligence techniques
Muhammad Nasir Amin, Waqas Ahmad, Kaffayatullah Khan, et al.
Case Studies in Construction Materials (2023) Vol. 18, pp. e02102-e02102
Open Access | Times Cited: 33
Prediction of UCS of fine-grained soil based on machine learning part 1: multivariable regression analysis, gaussian process regression, and gene expression programming
Jitendra Khatti, Kamaldeep Singh Grover
Multiscale and Multidisciplinary Modeling Experiments and Design (2023) Vol. 6, Iss. 2, pp. 199-222
Closed Access | Times Cited: 31
A data-driven approach to predict the compressive strength of alkali-activated materials and correlation of influencing parameters using SHapley Additive exPlanations (SHAP) analysis
Xinliang Zheng, Yi Xie, Xujiao Yang, et al.
Journal of Materials Research and Technology (2023) Vol. 25, pp. 4074-4093
Open Access | Times Cited: 31
Application of hybrid ANN paradigms built with nature inspired meta-heuristics for modelling soil compaction parameters
Abidhan Bardhan, Panagiotis G. Asteris
Transportation Geotechnics (2023) Vol. 41, pp. 100995-100995
Closed Access | Times Cited: 29
Modelling Soil Compaction Parameters Using an Enhanced Hybrid Intelligence Paradigm of ANFIS and Improved Grey Wolf Optimiser
Abidhan Bardhan, Raushan Kumar Singh, Sufyan Ghani, et al.
Mathematics (2023) Vol. 11, Iss. 14, pp. 3064-3064
Open Access | Times Cited: 27
A Scientometrics Review of Soil Properties Prediction Using Soft Computing Approaches
Jitendra Khatti, Kamaldeep Singh Grover
Archives of Computational Methods in Engineering (2023) Vol. 31, Iss. 3, pp. 1519-1553
Closed Access | Times Cited: 22
Intelligent prediction modeling for flexural capacity of FRP-strengthened reinforced concrete beams using machine learning algorithms
Majid Khan, Adil Khan, Asad U. Khan, et al.
Heliyon (2023) Vol. 10, Iss. 1, pp. e23375-e23375
Open Access | Times Cited: 21
Multi-expression programming based prediction of the seismic capacity of reinforced concrete rectangular columns
Raheel Asghar, Muhammad Faisal Javed, Muhammad Saqib, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 131, pp. 107834-107834
Closed Access | Times Cited: 11
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
Indirect estimation of resilient modulus (Mr) of subgrade soil: Gene expression programming vs multi expression programming
Laiba Khawaja, Muhammad Faisal Javed, Usama Asif, et al.
Structures (2024) Vol. 66, pp. 106837-106837
Closed Access | Times Cited: 11
Exploring the viability of AI-aided genetic algorithms in estimating the crack repair rate of self-healing concrete
Qiong Tian, Yijun Lü, Ji Zhou, et al.
REVIEWS ON ADVANCED MATERIALS SCIENCE (2024) Vol. 63, Iss. 1
Open Access | Times Cited: 8
Soft computing models for prediction of bentonite plastic concrete strength
Waleed Bin Inqiad, Muhammad Faisal Javed, Kennedy C. Onyelowe, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 7
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