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:
Estimation of the undrained shear strength of sensitive clays using optimized inference intelligence system
Quoc Anh Tran, Lanh Si Ho, Hiep Van Le, et al.
Neural Computing and Applications (2022) Vol. 34, Iss. 10, pp. 7835-7849
Closed Access | Times Cited: 12
Quoc Anh Tran, Lanh Si Ho, Hiep Van Le, et al.
Neural Computing and Applications (2022) Vol. 34, Iss. 10, pp. 7835-7849
Closed Access | Times Cited: 12
Showing 12 citing articles:
Computer vision-based classification of concrete spall severity using metaheuristic-optimized Extreme Gradient Boosting Machine and Deep Convolutional Neural Network
Hieu Nguyen, Nhat‐Duc Hoang
Automation in Construction (2022) Vol. 140, pp. 104371-104371
Closed Access | Times Cited: 40
Hieu Nguyen, Nhat‐Duc Hoang
Automation in Construction (2022) Vol. 140, pp. 104371-104371
Closed Access | Times Cited: 40
The effectiveness of data pre-processing methods on the performance of machine learning techniques using RF, SVR, Cubist and SGB: a study on undrained shear strength prediction
Selçuk Demir, Emrehan Kutluğ Şahin
Stochastic Environmental Research and Risk Assessment (2024) Vol. 38, Iss. 8, pp. 3273-3290
Open Access | Times Cited: 5
Selçuk Demir, Emrehan Kutluğ Şahin
Stochastic Environmental Research and Risk Assessment (2024) Vol. 38, Iss. 8, pp. 3273-3290
Open Access | Times Cited: 5
A deep learning-based surrogate model for probabilistic analysis of high-speed railway tunnel crown settlement in spatially variable soil considering construction process
Houle Zhang, Yongxin Wu, Jialiang Cheng, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 134, pp. 108752-108752
Closed Access | Times Cited: 4
Houle Zhang, Yongxin Wu, Jialiang Cheng, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 134, pp. 108752-108752
Closed Access | Times Cited: 4
Estimating shear strength parameters of a fine-grained alluvial soil using resedimented samples and multivariate regression
Muhammet Oğuz Sünnetci, Hakan Ersoy
Environmental Earth Sciences (2025) Vol. 84, Iss. 7
Open Access
Muhammet Oğuz Sünnetci, Hakan Ersoy
Environmental Earth Sciences (2025) Vol. 84, Iss. 7
Open Access
Modeling Undrained Shear Strength of Sensitive Alluvial Soft Clay Using Machine Learning Approach
Mohamed B. D. Elsawy, Mohammed F. Alsharekh, Mahmoud Shaban
Applied Sciences (2022) Vol. 12, Iss. 19, pp. 10177-10177
Open Access | Times Cited: 14
Mohamed B. D. Elsawy, Mohammed F. Alsharekh, Mahmoud Shaban
Applied Sciences (2022) Vol. 12, Iss. 19, pp. 10177-10177
Open Access | Times Cited: 14
Application of machine learning technique for predicting and evaluating chloride ingress in concrete
Van Quan Tran, Van Loi Giap, Dinh Phien Vu, et al.
Frontiers of Structural and Civil Engineering (2022) Vol. 16, Iss. 9, pp. 1153-1169
Closed Access | Times Cited: 13
Van Quan Tran, Van Loi Giap, Dinh Phien Vu, et al.
Frontiers of Structural and Civil Engineering (2022) Vol. 16, Iss. 9, pp. 1153-1169
Closed Access | Times Cited: 13
Prediction of Undrained Bearing Capacity of Skirted Foundation in Spatially Variable Soils Based on Convolutional Neural Network
Haifeng Cheng, Houle Zhang, Zihan Liu, et al.
Applied Sciences (2023) Vol. 13, Iss. 11, pp. 6624-6624
Open Access | Times Cited: 6
Haifeng Cheng, Houle Zhang, Zihan Liu, et al.
Applied Sciences (2023) Vol. 13, Iss. 11, pp. 6624-6624
Open Access | Times Cited: 6
CatBoost–Bayesian Hybrid Model Adaptively Coupled with Modified Theoretical Equations for Estimating the Undrained Shear Strength of Clay
Huajian Yang, Zhikui Liu, Yuantao Li, et al.
Applied Sciences (2023) Vol. 13, Iss. 9, pp. 5418-5418
Open Access | Times Cited: 5
Huajian Yang, Zhikui Liu, Yuantao Li, et al.
Applied Sciences (2023) Vol. 13, Iss. 9, pp. 5418-5418
Open Access | Times Cited: 5
Shrink–swell index prediction through deep learning
Bertrand Teodosio, P.L.P. Wasantha, Ehsan Yaghoubi, et al.
Neural Computing and Applications (2022) Vol. 35, Iss. 6, pp. 4569-4586
Open Access | Times Cited: 3
Bertrand Teodosio, P.L.P. Wasantha, Ehsan Yaghoubi, et al.
Neural Computing and Applications (2022) Vol. 35, Iss. 6, pp. 4569-4586
Open Access | Times Cited: 3
Modeling the impact of supplementary cementitious materials on compressive strength of recycled aggregate concrete forest-random approach
Joaquín Abellán García, M. Iqbal Khan, Yassir M. Abbas, et al.
DYNA (2024) Vol. 91, Iss. 231, pp. 94-104
Open Access
Joaquín Abellán García, M. Iqbal Khan, Yassir M. Abbas, et al.
DYNA (2024) Vol. 91, Iss. 231, pp. 94-104
Open Access
Compilation of Consolidation Properties Data of Champlain Sea Clay from Ottawa Region
N’eem Tavakkoli, Won Taek Oh, Sai K. Vanapalli
Geotechnical and Geological Engineering (2024) Vol. 42, Iss. 7, pp. 5847-5869
Open Access
N’eem Tavakkoli, Won Taek Oh, Sai K. Vanapalli
Geotechnical and Geological Engineering (2024) Vol. 42, Iss. 7, pp. 5847-5869
Open Access
Prediction of the Undrained Shear Strength of the Remolded Soil with Non-Linear Regression, Fuzzy Logic and Artificial Neural Network
Kaan Yünkül, Fatih Karaçor, Ayhan Gürbüz, et al.
Research Square (Research Square) (2023)
Open Access
Kaan Yünkül, Fatih Karaçor, Ayhan Gürbüz, et al.
Research Square (Research Square) (2023)
Open Access
