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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:

Modeling coking coal indexes by SHAP-XGBoost: Explainable artificial intelligence method
Arman Homafar, Hamid Nasiri, Saeed Chehreh Chelgani
Fuel Communications (2022) Vol. 13, pp. 100078-100078
Closed Access | Times Cited: 24

Showing 24 citing articles:

Monthly sodium adsorption ratio forecasting in rivers using a dual interpretable glass-box complementary intelligent system: Hybridization of ensemble TVF-EMD-VMD, Boruta-SHAP, and eXplainable GPR
Mehdi Jamei, Mumtaz Ali, Masoud Karbasi, et al.
Expert Systems with Applications (2023) Vol. 237, pp. 121512-121512
Closed Access | Times Cited: 19
CatBoost-SHAP for modeling industrial operational flotation variables – A “conscious lab” approach
Saeed Chehreh Chelgani, Arman Homafar, Hamid Nasiri, et al.
Minerals Engineering (2024) Vol. 213, pp. 108754-108754
Open Access | Times Cited: 5
Effect of phosphorus fractions on benthic chlorophyll-a; Insight from the machine learning models
Yuting Wang, Sangar Khan, Zongwei Lin, et al.
Ecological Informatics (2025) Vol. 85, pp. 102990-102990
Open Access
Unveiling the Predictive Power of Machine Learning in Coal Gross Calorific Value Estimation: An Interpretability Perspective
Wei Zhu, Na Xu, James C. Hower
Energy (2025), pp. 134781-134781
Closed Access
Explainable Advanced Modelling of CO2-Dissolved Brine Density: Applications for Geological CO2 Storage in Aquifers
Amin Shokrollahi, Afshin Tatar, Sepideh Atrbarmohammadi, et al.
Inventions (2025) Vol. 10, Iss. 1, pp. 15-15
Open Access
Untargeted Lipidomic Biomarkers for Liver Cancer Diagnosis: A Tree-Based Machine Learning Model Enhanced by Explainable Artificial Intelligence
Cemil Çolak, Fatma Hilal Yağın, Abdulmohsen Algarni, et al.
Medicina (2025) Vol. 61, Iss. 3, pp. 405-405
Open Access
Diagnosis of Parkinson’s disease based on voice signals using SHAP and hard voting ensemble method
Paria Ghaheri, Hamid Nasiri, Ahmadreza Shateri, et al.
Computer Methods in Biomechanics & Biomedical Engineering (2023) Vol. 27, Iss. 13, pp. 1858-1874
Open Access | Times Cited: 14
Development of an expert system for the classification of myalgic encephalomyelitis/chronic fatigue syndrome
Fatma Hilal Yağın, Ahmadreza Shateri, Hamid Nasiri, et al.
PeerJ Computer Science (2024) Vol. 10, pp. e1857-e1857
Open Access | Times Cited: 4
Predicting the governing factors for the release of colloidal phosphorus using machine learning
Sangar Khan, Huimin Gao, Paul Milham, et al.
Chemosphere (2024) Vol. 362, pp. 142699-142699
Closed Access | Times Cited: 4
PD-ADSV: An automated diagnosing system using voice signals and hard voting ensemble method for Parkinson’s disease
Paria Ghaheri, Ahmadreza Shateri, Hamid Nasiri
Software Impacts (2023) Vol. 16, pp. 100504-100504
Open Access | Times Cited: 11
Machine learning framework for evaluating fracturing-flooding effectiveness: From prediction to decision recommendations
Xiang Wang, Xianxiang Chu, Yixin Xie, et al.
Fuel (2024) Vol. 381, pp. 133299-133299
Closed Access | Times Cited: 3
Pan-Cancer Classification of Gene Expression Data Based on Artificial Neural Network Model
Claudia Cava, Christian Salvatore, Isabella Castiglioni
Applied Sciences (2023) Vol. 13, Iss. 13, pp. 7355-7355
Open Access | Times Cited: 4
Modelling of fatty acids signatures predicts macroalgal carbon in marine sediments
Erlania Erlania, Peter I. Macreadie, David S. Francis, et al.
Ecological Indicators (2024) Vol. 160, pp. 111715-111715
Open Access | Times Cited: 1
Investigating the Impact of Agricultural, Financial, Economic, and Political Factors on Oil Forward Prices and Volatility: A SHAP Analysis
H.J. Kim, Hui-Sang Kim, Sun‐Yong Choi
Energies (2024) Vol. 17, Iss. 5, pp. 1001-1001
Open Access | Times Cited: 1
Optimization of Blast Furnace Ironmaking Using Machine Learning and Genetic Algorithms
Manendra Singh Parihar, Sri Harsha Nistala, Rajan Kumar, et al.
steel research international (2024)
Closed Access | Times Cited: 1
Analyzing Decision-Making in Cognitive Agent Simulations Using Generalized Linear Mixed-Effects Models
Shengkun Xie, Chong Gan, Anna T. Ławniczak
Mathematics (2024) Vol. 12, Iss. 23, pp. 3768-3768
Open Access | Times Cited: 1
Predicting the Governing Factors for the Release of Colloidal Phosphorus Using Machine Learning
Sangar Khan, Huimin Gao, Paul J. Milham, et al.
(2024)
Closed Access
Machine Learning Prediction of Benthic Chlorophyll-A in Thousand Island Catchment, China
Sangar Khan, Noël P. D. Juvigny‐Khenafou, Tatenda Dalu, et al.
(2024)
Closed Access
Employing Artificial Intelligence for Enhanced Microbial Fuel Cell Performance through Wolf Vitamin Solution Optimization
Hamed Farahani, Mostafa Ghasemi, Mehdi Sedighi, et al.
Sustainability (2024) Vol. 16, Iss. 15, pp. 6468-6468
Open Access
Prediction and analysis of dominant factors influencing moisture content during vacuum screening based on machine learning
Ling Nie, Weiguo Ma, Xiangdong Xie
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access
Assessment of noise pollution-prone areas using an explainable geospatial artificial intelligence approach
Seyed Vahid Razavi-Termeh, Abolghasem Sadeghi‐Niaraki, Xiaobai Yao, et al.
Journal of Environmental Management (2024) Vol. 370, pp. 122361-122361
Closed Access
Interpretable machine learning-assisted advanced exergy optimization for carbon-neutral olefins production
Qingchun Yang, Lei Zhao, Runjie Bao, et al.
Renewable and Sustainable Energy Reviews (2024) Vol. 208, pp. 115027-115027
Closed Access
Explainable machine learning model for predicting molten steel temperature in the LF refining process
Zicheng Xin, Jiangshan Zhang, Kaixiang Peng, et al.
International Journal of Minerals Metallurgy and Materials (2024) Vol. 31, Iss. 12, pp. 2657-2669
Closed Access
Predicting the Governing Factors for the Release of Colloidal Phosphorus from Arable, Forest, and Desert Soils to Different Water Bodies Using Structural Equation and Machine Learning Models
Sangar Khan, Huimin Gao, Paul J. Milham, et al.
(2023)
Closed Access
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