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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:

Prediction of shear strength of soft soil using machine learning methods
Binh Thai Pham, Lê Hoàng Sơn, Tuan-Anh Hoang, et al.
CATENA (2018) Vol. 166, pp. 181-191
Closed Access | Times Cited: 204

Showing 1-25 of 204 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: 467
Artificial Intelligence Approaches for Prediction of Compressive Strength of Geopolymer Concrete
Dong Van Dao, Haï-Bang Ly, Son Hoang Trinh, et al.
Materials (2019) Vol. 12, Iss. 6, pp. 983-983
Open Access | Times Cited: 304
Spatial prediction of groundwater potential mapping based on convolutional neural network (CNN) and support vector regression (SVR)
Mahdi Panahi, Nitheshnirmal Sãdhasivam, Hamid Reza Pourghasemi, et al.
Journal of Hydrology (2020) Vol. 588, pp. 125033-125033
Closed Access | Times Cited: 290
Applying population-based evolutionary algorithms and a neuro-fuzzy system for modeling landslide susceptibility
Wei Chen, Mahdi Panahi, Paraskevas Tsangaratos, et al.
CATENA (2018) Vol. 172, pp. 212-231
Closed Access | Times Cited: 243
Evaluating compressive strength of concrete made with recycled concrete aggregates using machine learning approach
Van Quan Tran, Viet Quoc Dang, Lanh Si Ho
Construction and Building Materials (2022) Vol. 323, pp. 126578-126578
Closed Access | Times Cited: 242
Landslide spatial modelling using novel bivariate statistical based Naïve Bayes, RBF Classifier, and RBF Network machine learning algorithms
Qingfeng He, Himan Shahabi, Ataollah Shirzadi, et al.
The Science of The Total Environment (2019) Vol. 663, pp. 1-15
Closed Access | Times Cited: 220
A novel hybrid intelligent model of support vector machines and the MultiBoost ensemble for landslide susceptibility modeling
Binh Thai Pham, Abolfazl Jaafari, Indra Prakash, et al.
Bulletin of Engineering Geology and the Environment (2018) Vol. 78, Iss. 4, pp. 2865-2886
Closed Access | Times Cited: 219
Machine learning techniques for structural health monitoring of heritage buildings: A state-of-the-art review and case studies
Mayank Mishra
Journal of Cultural Heritage (2020) Vol. 47, pp. 227-245
Closed Access | Times Cited: 194
A comparison study of DRASTIC methods with various objective methods for groundwater vulnerability assessment
Khabat Khosravi, Majid Sartaj, Frank T.‐C. Tsai, et al.
The Science of The Total Environment (2018) Vol. 642, pp. 1032-1049
Closed Access | Times Cited: 188
A Sensitivity and Robustness Analysis of GPR and ANN for High-Performance Concrete Compressive Strength Prediction Using a Monte Carlo Simulation
Dong Van Dao, Hojjat Adeli, Haï-Bang Ly, et al.
Sustainability (2020) Vol. 12, Iss. 3, pp. 830-830
Open Access | Times Cited: 181
A novel artificial intelligence approach based on Multi-layer Perceptron Neural Network and Biogeography-based Optimization for predicting coefficient of consolidation of soil
Binh Thai Pham, Manh Duc Nguyen, Kien-Trinh Thi Bui, et al.
CATENA (2018) Vol. 173, pp. 302-311
Closed Access | Times Cited: 179
Real-time water quality monitoring using Internet of Things in SCADA
K. Saravanan, E. Anusuya, Raghvendra Kumar, et al.
Environmental Monitoring and Assessment (2018) Vol. 190, Iss. 9
Closed Access | Times Cited: 171
A novel hybrid surrogate intelligent model for creep index prediction based on particle swarm optimization and random forest
Pin Zhang, Zhen‐Yu Yin, Yin-Fu Jin, et al.
Engineering Geology (2019) Vol. 265, pp. 105328-105328
Open Access | Times Cited: 155
Random Forest Algorithm for the Strength Prediction of Geopolymer Stabilized Clayey Soil
Husein Ali Zeini, Duaa Al-Jeznawi, Hamza Imran, et al.
Sustainability (2023) Vol. 15, Iss. 2, pp. 1408-1408
Open Access | Times Cited: 46
Estimating compressive strength of coral sand aggregate concrete in marine environment by combining physical experiments and machine learning-based techniques
Zhiming Chao, Zhikang Li, Youkou Dong, et al.
Ocean Engineering (2024) Vol. 308, pp. 118320-118320
Closed Access | Times Cited: 30
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: 19
Spatial prediction of groundwater spring potential mapping based on an adaptive neuro-fuzzy inference system and metaheuristic optimization
Khabat Khosravi, Mahdi Panahi, Dieu Tien Bui
Hydrology and earth system sciences (2018) Vol. 22, Iss. 9, pp. 4771-4792
Open Access | Times Cited: 156
Spatial pattern assessment of tropical forest fire danger at Thuan Chau area (Vietnam) using GIS-based advanced machine learning algorithms: A comparative study
Nguyễn Ngọc Thạch, Dang Bao-Toan Ngo, Pham Xuan-Canh, et al.
Ecological Informatics (2018) Vol. 46, pp. 74-85
Open Access | Times Cited: 153
Prediction of soil compression coefficient for urban housing project using novel integration machine learning approach of swarm intelligence and Multi-layer Perceptron Neural Network
Dieu Tien Bui, Viet‐Ha Nhu, Nhat‐Duc Hoang
Advanced Engineering Informatics (2018) Vol. 38, pp. 593-604
Closed Access | Times Cited: 140
A novel hybrid approach of Bayesian Logistic Regression and its ensembles for landslide susceptibility assessment
Mousa Abedini, Bahareh Ghasemian, Ataollah Shirzadi, et al.
Geocarto International (2018) Vol. 34, Iss. 13, pp. 1427-1457
Closed Access | Times Cited: 131
A similarity-based approach to sampling absence data for landslide susceptibility mapping using data-driven methods
A‐Xing Zhu, Miao Yamin, Junzhi Liu, et al.
CATENA (2019) Vol. 183, pp. 104188-104188
Closed Access | Times Cited: 126
Groundwater spring potential mapping using population-based evolutionary algorithms and data mining methods
Wei Chen, Paraskevas Tsangaratos, Ioanna Ilia, et al.
The Science of The Total Environment (2019) Vol. 684, pp. 31-49
Closed Access | Times Cited: 122
Permeability prediction of porous media using a combination of computational fluid dynamics and hybrid machine learning methods
Jianwei Tian, Chongchong Qi, Yingfeng Sun, et al.
Engineering With Computers (2020) Vol. 37, Iss. 4, pp. 3455-3471
Closed Access | Times Cited: 119
35 Years of (AI) in Geotechnical Engineering: State of the Art
Ahmed M. Ebid
Geotechnical and Geological Engineering (2020) Vol. 39, Iss. 2, pp. 637-690
Closed Access | Times Cited: 119
A Novel and Comprehensive Trust Estimation Clustering Based Approach for Large Scale Wireless Sensor Networks
Tayyab Khan, Karan Singh, Lê Hoàng Sơn, et al.
IEEE Access (2019) Vol. 7, pp. 58221-58240
Open Access | Times Cited: 115
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