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:
Correlating the Unconfined Compressive Strength of Rock with the Compressional Wave Velocity Effective Porosity and Schmidt Hammer Rebound Number Using Artificial Neural Networks
Tien-Thinh Le, Athanasia D. Skentou, Anna Mamou, et al.
Rock Mechanics and Rock Engineering (2022) Vol. 55, Iss. 11, pp. 6805-6840
Closed Access | Times Cited: 37
Tien-Thinh Le, Athanasia D. Skentou, Anna Mamou, et al.
Rock Mechanics and Rock Engineering (2022) Vol. 55, Iss. 11, pp. 6805-6840
Closed Access | Times Cited: 37
Showing 26-50 of 37 citing articles:
Comparative analysis of selected machine learning techniques for predicting the pull-off strength of the surface layer of eco-friendly concrete
Mateusz Moj, Sławomir Czarnecki
Advances in Engineering Software (2024) Vol. 195, pp. 103710-103710
Open Access | Times Cited: 3
Mateusz Moj, Sławomir Czarnecki
Advances in Engineering Software (2024) Vol. 195, pp. 103710-103710
Open Access | Times Cited: 3
A novel identification model for rock burst grades-taking Jinping II hydropower station hub engineering as an example
He Kuang, Zhi Yong Ai, Gan Lin Gu
Computers and Geotechnics (2024) Vol. 172, pp. 106440-106440
Closed Access | Times Cited: 2
He Kuang, Zhi Yong Ai, Gan Lin Gu
Computers and Geotechnics (2024) Vol. 172, pp. 106440-106440
Closed Access | Times Cited: 2
Unconfined compressive strength prediction of rock materials based on machine learning
Lihong Niu, Qiang Cui, Jiangyun Luo, et al.
Journal of Engineering and Applied Science (2024) Vol. 71, Iss. 1
Open Access | Times Cited: 2
Lihong Niu, Qiang Cui, Jiangyun Luo, et al.
Journal of Engineering and Applied Science (2024) Vol. 71, Iss. 1
Open Access | Times Cited: 2
Predicting Rock Unconfined Compressive Strength Based on Tunnel Face Boreholes Measurement-While-Drilling Data
Xuepeng Ling, Mingnian Wang, Wenhao Yi, et al.
KSCE Journal of Civil Engineering (2024) Vol. 28, Iss. 12, pp. 5946-5962
Closed Access | Times Cited: 2
Xuepeng Ling, Mingnian Wang, Wenhao Yi, et al.
KSCE Journal of Civil Engineering (2024) Vol. 28, Iss. 12, pp. 5946-5962
Closed Access | Times Cited: 2
Hybrid Wavelet Scattering Network-Based Model for Failure Identification of Reinforced Concrete Members
Mohammad Sadegh Barkhordari, Mohammad Mahdi Barkhordari, Danial Jahed Armaghani, et al.
Sustainability (2022) Vol. 14, Iss. 19, pp. 12041-12041
Open Access | Times Cited: 10
Mohammad Sadegh Barkhordari, Mohammad Mahdi Barkhordari, Danial Jahed Armaghani, et al.
Sustainability (2022) Vol. 14, Iss. 19, pp. 12041-12041
Open Access | Times Cited: 10
Comparative Analyses of Selected Neural Networks for Prediction of Sustainable Cementitious Composite Subsurface Tensile Strength
Sławomir Czarnecki, Mateusz Moj
Applied Sciences (2023) Vol. 13, Iss. 8, pp. 4817-4817
Open Access | Times Cited: 5
Sławomir Czarnecki, Mateusz Moj
Applied Sciences (2023) Vol. 13, Iss. 8, pp. 4817-4817
Open Access | Times Cited: 5
Integrated machine learning for modeling bearing capacity of shallow foundations
Yuzhen Liu, Yan Liang
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 1
Yuzhen Liu, Yan Liang
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 1
Multiobjective optimization of end milling parameters for enhanced machining performance on 42CrMo4 using machine learning and NSGA-III
Van-Hai Nguyen, Tien-Thinh Le, Anh-Tu Nguyen, et al.
Machining Science and Technology (2024), pp. 1-33
Closed Access | Times Cited: 1
Van-Hai Nguyen, Tien-Thinh Le, Anh-Tu Nguyen, et al.
Machining Science and Technology (2024), pp. 1-33
Closed Access | Times Cited: 1
Machine learning approach for evaluating soil liquefaction probability based on reliability method
Sophia Khatoon, Kishan Kumar, Pijush Samui, et al.
Natural Hazards (2024)
Closed Access | Times Cited: 1
Sophia Khatoon, Kishan Kumar, Pijush Samui, et al.
Natural Hazards (2024)
Closed Access | Times Cited: 1
Back-propagation neural network model enhanced by transfer learning for the prediction method of compressive strength of alkali residue-based foamed concrete
Yuhao Zhang, Zhengcheng Wang, Songyu Liu, et al.
Journal of Sustainable Cement-Based Materials (2024) Vol. 13, Iss. 12, pp. 1812-1828
Closed Access | Times Cited: 1
Yuhao Zhang, Zhengcheng Wang, Songyu Liu, et al.
Journal of Sustainable Cement-Based Materials (2024) Vol. 13, Iss. 12, pp. 1812-1828
Closed Access | Times Cited: 1
Deep Neural Networks for the Estimation of Masonry Structures Failures under Rockfalls
Olga Mavrouli, Athanasia D. Skentou, Josep Maria Carbonell, et al.
Geosciences (2023) Vol. 13, Iss. 6, pp. 156-156
Open Access | Times Cited: 2
Olga Mavrouli, Athanasia D. Skentou, Josep Maria Carbonell, et al.
Geosciences (2023) Vol. 13, Iss. 6, pp. 156-156
Open Access | Times Cited: 2
Comparative Study on Convolutional Neural Network and Regression Analysis to Evaluate Uniaxial Compressive Strength of Sandy Dolomite
Wei Xu, Meiqian Wang, Wenlian Liu, et al.
Research Square (Research Square) (2024)
Open Access
Wei Xu, Meiqian Wang, Wenlian Liu, et al.
Research Square (Research Square) (2024)
Open Access
Artificial Neural Network based Model for Fruit Grade Empirical Thresholding and Feature Extraction based Back Propagation
Kuldeep Godiyal
International Journal on Recent and Innovation Trends in Computing and Communication (2022) Vol. 10, Iss. 1s, pp. 108-114
Open Access
Kuldeep Godiyal
International Journal on Recent and Innovation Trends in Computing and Communication (2022) Vol. 10, Iss. 1s, pp. 108-114
Open Access
