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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:

Slope stability prediction based on a long short-term memory neural network: comparisons with convolutional neural networks, support vector machines and random forest models
Faming Huang, Haowen Xiong, Shixuan Chen, et al.
International Journal of Coal Science & Technology (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 70

Showing 1-25 of 70 citing articles:

Reliability of Information-Theoretic Displacement Detection and Risk Classification for Enhanced Slope Stability and Safety at Highway Construction Sites
Odey Alshboul, Ali Shehadeh, Ghassan Almasabha
Reliability Engineering & System Safety (2025), pp. 110813-110813
Closed Access | Times Cited: 5
Uncertainties of landslide susceptibility prediction: Influences of random errors in landslide conditioning factors and errors reduction by low pass filter method
Faming Huang, Zuokui Teng, Chi Yao, et al.
Journal of Rock Mechanics and Geotechnical Engineering (2023) Vol. 16, Iss. 1, pp. 213-230
Open Access | Times Cited: 31
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: 24
Comparison of machine learning algorithms for slope stability prediction using an automated machine learning approach
Талас Фикрет Курназ, Caner Erden, Угур Дагдевирен, et al.
Natural Hazards (2024) Vol. 120, Iss. 8, pp. 6991-7014
Closed Access | Times Cited: 17
Utilization of machine learning for the estimation of production rates in wells operated by electrical submersible pumps
Okorie E. Agwu, Ahmad Alkouh, Saad Alatefi, et al.
Journal of Petroleum Exploration and Production Technology (2024) Vol. 14, Iss. 5, pp. 1205-1233
Open Access | Times Cited: 14
Uncertainties of landslide susceptibility prediction: influences of different study area scales and mapping unit scales
Faming Huang, Yu Cao, Wenbin Li, et al.
International Journal of Coal Science & Technology (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 14
Late Ming Dynasty weak monsoon induced a harmonized megadrought across north-to-south China
Weipeng Yue, Feng Chen, Max C. A. Torbenson, et al.
Communications Earth & Environment (2024) Vol. 5, Iss. 1
Open Access | Times Cited: 12
Comparison of boosting and genetic programming techniques for prediction of tensile strain capacity of Engineered Cementitious Composites (ECC)
Waleed Bin Inqiad, Muhammad Faisal Javed, Muhammad Shahid Siddique, et al.
Materials Today Communications (2024) Vol. 39, pp. 109222-109222
Closed Access | Times Cited: 10
State-of-the-art review on the use of AI-enhanced computational mechanics in geotechnical engineering
Hongchen Liu, Huaizhi Su, Lizhi Sun, et al.
Artificial Intelligence Review (2024) Vol. 57, Iss. 8
Open Access | Times Cited: 9
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: 9
Predicting slope stability potential failure surface using machine learning algorithms
Myoung-Soo Won, Shamsher Sadiq, Jianbin Wang, et al.
Arabian Journal of Geosciences (2025) Vol. 18, Iss. 1
Closed Access | Times Cited: 1
Spatio-temporal fusion of meteorological factors for multi-site PM2.5 prediction: A deep learning and time-variant graph approach
Hongqing Wang, Lifu Zhang, Rong Wu, et al.
Environmental Research (2023) Vol. 239, pp. 117286-117286
Closed Access | Times Cited: 19
Predicting compressive strength of hollow concrete prisms using machine learning techniques and explainable artificial intelligence (XAI)
Waleed Bin Inqiad, Elena Valentina Dumitrascu, Robert Alexandru Dobre, et al.
Heliyon (2024) Vol. 10, Iss. 17, pp. e36841-e36841
Open Access | Times Cited: 8
Enhancing shear strength predictions of rocks using a hierarchical ensemble model
Xiaohua Ding, Maryam Amiri, Mahdi Hasanipanah
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 8
Predicting natural vibration period of concrete frame structures having masonry infill using machine learning techniques
Waleed Bin Inqiad, Muhammad Faisal Javed, Muhammad Shahid Siddique, et al.
Journal of Building Engineering (2024) Vol. 96, pp. 110417-110417
Closed Access | Times Cited: 7
Prediction of rock loading stages using average infrared radiation temperature under shear and uniaxial loading
Liqiang Ma, Naseer Muhammad Khan, Tariq Feroze, et al.
Infrared Physics & Technology (2023) Vol. 136, pp. 105084-105084
Closed Access | Times Cited: 14
Pseudo-static slope stability analysis using explainable machine learning techniques
Abdul Waris Kenue, Sheikh Junaid Fayaz, Alluri Harshith Reddy, et al.
Natural Hazards (2024)
Closed Access | Times Cited: 6
Enhancing deep learning-based slope stability classification using a novel metaheuristic optimization algorithm for feature selection
Bilel Zerouali, Nadjem Bailek, Aqil Tariq, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 6
Machine learning regression algorithms for predicting the susceptibility of jointed rock slopes to planar failure
Avishek Dutta, Kripamoy Sarkar, K. Sai Tarun
Earth Science Informatics (2024) Vol. 17, Iss. 3, pp. 2477-2493
Closed Access | Times Cited: 5
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
Advanced machine learning approaches for uniaxial compressive strength prediction of Indian rocks using petrographic properties
Md Shayan Sabri, Amit Jaiswal, A. K. Verma, et al.
Multiscale and Multidisciplinary Modeling Experiments and Design (2024) Vol. 7, Iss. 6, pp. 5265-5286
Closed Access | Times Cited: 5
Integrating Feature Selection with Machine Learning for Accurate Reservoir Landslide Displacement Prediction
Qi Ge, Jingyong Wang, Cheng Liu, et al.
Water (2024) Vol. 16, Iss. 15, pp. 2152-2152
Open Access | Times Cited: 5
AI-based rock strength assessment from tunnel face images using hybrid neural networks
Lianbaichao Liu, Zhanping Song, Ping Zhou, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 5
Predicting residual strength of hybrid fibre-reinforced Self-compacting concrete (HFR-SCC) exposed to elevated temperatures using machine learning
Muhammad Saud Khan, Liqiang Ma, Waleed Bin Inqiad, et al.
Case Studies in Construction Materials (2024) Vol. 22, pp. e04112-e04112
Closed Access | Times Cited: 5
Machine learning-based constitutive modelling for material non-linearity: A review
Arif Hussain, Amir Hosein Sakhaei, Mahmood Shafiee
Mechanics of Advanced Materials and Structures (2024), pp. 1-19
Open Access | Times Cited: 5
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