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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:

Data-driven interpretable ensemble learning methods for the prediction of wind turbine power incorporating SHAP analysis
Celal Çakıroğlu, Sercan Demir, Mehmet Hakan Özdemir, et al.
Expert Systems with Applications (2023) Vol. 237, pp. 121464-121464
Closed Access | Times Cited: 76

Showing 1-25 of 76 citing articles:

Hybrid data-driven approaches to predicting the compressive strength of ultra-high-performance concrete using SHAP and PDP analyses
Abul Kashem, Rezaul Karim, Somir Chandra Malo, et al.
Case Studies in Construction Materials (2024) Vol. 20, pp. e02991-e02991
Open Access | Times Cited: 45
Hybrid machine learning approach to prediction of the compressive and flexural strengths of UHPC and parametric analysis with shapley additive explanations
Pobithra Das, Abul Kashem
Case Studies in Construction Materials (2023) Vol. 20, pp. e02723-e02723
Open Access | Times Cited: 44
Explainable machine learning methods for predicting water treatment plant features under varying weather conditions
Mohammed Al Saleem, Fouzi Harrou, Ying Sun
Results in Engineering (2024) Vol. 21, pp. 101930-101930
Open Access | Times Cited: 21
ENHANCING LOAN APPROVAL DECISION-MAKING: AN INTERPRETABLE MACHINE LEARNING APPROACH USING LIGHTGBM FOR DIGITAL ECONOMY DEVELOPMENT
Teuku Rizky Noviandy, Ghalieb Mutig Idroes, Irsan Hardi
(2024) Vol. 9, Iss. 1, pp. 1734-1745
Open Access | Times Cited: 19
Feature fusion method for rock mass classification prediction and interpretable analysis based on TBM operating and cutter wear data
Wen‐Kun Yang, Zuyu Chen, Haitao Zhao, et al.
Tunnelling and Underground Space Technology (2025) Vol. 157, pp. 106351-106351
Closed Access | Times Cited: 1
Explainable AI-Enhanced Human Activity Recognition for Human–Robot Collaboration in Agriculture
Lefteris Benos, Dimitrios Tsaopoulos, Aristotelis C. Tagarakis, et al.
Applied Sciences (2025) Vol. 15, Iss. 2, pp. 650-650
Open Access | Times Cited: 1
Interpretable predictive modelling of outlet temperatures in Central Alberta’s hydrothermal system using boosting-based ensemble learning incorporating Shapley Additive exPlanations (SHAP) approach
Ruyang Yu, Kai Zhang, Tao Li, et al.
Energy (2025), pp. 134738-134738
Closed Access | Times Cited: 1
A comparative study of machine learning models for construction costs prediction with natural gradient boosting algorithm and SHAP analysis
Pobithra Das, Abul Kashem, Imrul Hasan, et al.
Asian Journal of Civil Engineering (2024) Vol. 25, Iss. 4, pp. 3301-3316
Closed Access | Times Cited: 13
Explainable ensemble models for predicting wall thickness loss of water pipes
Ridwan Taiwo, Abdul‐Mugis Yussif, Mohamed El Amine Ben Seghier, et al.
Ain Shams Engineering Journal (2024) Vol. 15, Iss. 4, pp. 102630-102630
Open Access | Times Cited: 9
Enhancing wind power prediction with self-attentive variational autoencoders: A comparative study
Fouzi Harrou, Abdelkader Dairi, Abdelhakim Dorbane, et al.
Results in Engineering (2024) Vol. 23, pp. 102504-102504
Open Access | Times Cited: 8
Complex-valued artificial hummingbird algorithm for global optimization and short-term wind speed prediction
Liuyan Feng, Yongquan Zhou, Qifang Luo, et al.
Expert Systems with Applications (2024) Vol. 246, pp. 123160-123160
Closed Access | Times Cited: 7
Estimating Carbon Dioxide Solubility in Brine Using Mixed Effects Random Forest Based on Genetic Algorithm: Implications for Carbon Dioxide Sequestration in Saline Aquifers
Grant Charles Mwakipunda, AL-Wesabi Ibrahim, Allou Koffi Franck Kouassi, et al.
SPE Journal (2024) Vol. 29, Iss. 11, pp. 6530-6546
Closed Access | Times Cited: 6
Fuzzy Logic-Enhanced Direct Power Control for Wind Turbines with Doubly Fed Induction Generators
Karim Fathi Sayeh, Salah Tamalouzt, Djamel Ziane, et al.
Results in Engineering (2024), pp. 103557-103557
Open Access | Times Cited: 6
Ensemble learning for predicting average thermal extraction load of a hydrothermal geothermal field: A case study in Guanzhong Basin, China
Ruyang Yu, Kai Zhang, R. Brindha, et al.
Energy (2024) Vol. 296, pp. 131146-131146
Closed Access | Times Cited: 5
Predicting removal efficiency of organic pollutants by soil vapor extraction based on an optimized machine learning method
Shuai Zhang, Jiating Zhao, Lizhong Zhu
The Science of The Total Environment (2024) Vol. 927, pp. 172438-172438
Closed Access | Times Cited: 5
An Efficient and Interpretable Stacked Model for Wind Speed Estimation Based on Ensemble Learning Algorithms
Ankit Jha, Vansh Goel, Manish Kumar, et al.
Energy Technology (2024) Vol. 12, Iss. 6
Closed Access | Times Cited: 5
Enhancing Solar Forecasting Accuracy with Sequential Deep Artificial Neural Network and Hybrid Random Forest and Gradient Boosting Models across Varied Terrains
Muhammad Farhan Hanif, Muhammad Umar Siddique, Jicang Si, et al.
Advanced Theory and Simulations (2024) Vol. 7, Iss. 7
Closed Access | Times Cited: 5
Investigating the effect of fuel properties and environmental parameters on low-octane gasoline-like fuel spray combustion and emissions using machine learning-global sensitivity analysis method
Yinjie Ma, Dong Yang, Deyi Xie, et al.
Energy (2024) Vol. 306, pp. 132551-132551
Closed Access | Times Cited: 5
Interpretable Machine Learning Models for Predicting Ebus Battery Consumption Rates in Cold Climates with and without Diesel Auxiliary Heating
Kareem Othman, Diego Da Silva, Amer Shalaby, et al.
Green Energy and Intelligent Transportation (2025), pp. 100250-100250
Open Access
Revealing the effects of environmental and spatio-temporal variables on changes in Japanese sardine (Sardinops melanostictus) high abundance fishing grounds based on interpretable machine learning approach
Yongchuang Shi, Lei Yan, Shengmao Zhang, et al.
Frontiers in Marine Science (2025) Vol. 11
Open Access
Predicting employee attrition and explaining its determinants
Shahin Manafi Varkiani, Francesco Pattarin, Tommaso Fabbri, et al.
Expert Systems with Applications (2025), pp. 126575-126575
Open Access
Insights into the strength development in cement-treated soils: An explainable AI-based approach for optimized mix design
Muhammad Hasnain Ayub Khan, Adel Abdallah, Olivier Cuisinier
Computers and Geotechnics (2025) Vol. 180, pp. 107103-107103
Closed Access
Predicting hydropower generation: A comparative analysis of Machine learning models and optimization algorithms for enhanced forecasting accuracy and operational efficiency
Chunyang Wang, Chao Li, Yu-Dong Feng, et al.
Ain Shams Engineering Journal (2025) Vol. 16, Iss. 3, pp. 103299-103299
Closed Access
Effective depression detection and interpretation: Integrating machine learning, deep learning, language models, and explainable AI
Gazi Hasan Al Masud, Rejaul Islam Shanto, Ishmam Sakin, et al.
Array (2025), pp. 100375-100375
Open Access
Overview of Data-Driven Models for Wind Turbine Wake Flows
Maokun Ye, Min Li, Mingqiu Liu, et al.
Journal of Marine Science and Application (2025)
Open Access
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