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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:

Accurate estimation of tool wear levels during milling, drilling and turning operations by designing novel hyperparameter tuned models based on LightGBM and stacking
Jawad Mahmood, Ghulam-e Mustafa, Muhammad Ali
Measurement (2022) Vol. 190, pp. 110722-110722
Closed Access | Times Cited: 40

Showing 1-25 of 40 citing articles:

Interpretable machine learning for predicting the strength of 3D printed fiber-reinforced concrete (3DP-FRC)
Md Nasir Uddin, Junhong Ye, Bo-Yu Deng, et al.
Journal of Building Engineering (2023) Vol. 72, pp. 106648-106648
Closed Access | Times Cited: 42
Toward accurate prediction of carbon dioxide (CO2) compressibility factor using tree-based intelligent schemes (XGBoost and LightGBM) and equations of state
Behnam Amiri-Ramsheh, Aydin Larestani, Saeid Atashrouz, et al.
Results in Engineering (2025), pp. 104035-104035
Open Access | Times Cited: 1
Performance Analysis of Steel W18CR4V Grinding Using RSM, DNN-GA, KNN, LM, DT, SVM Models, and Optimization via Desirability Function and MOGWO
Sofiane Touati, Haithem Boumediri, Yacine Karmi, et al.
Heliyon (2025) Vol. 11, Iss. 4, pp. e42640-e42640
Open Access | Times Cited: 1
A State-of-the-Art Review on Chatter Stability in Machining Thin−Walled Parts
Yuwen Sun, Zheng Meng, Shanglei Jiang, et al.
Machines (2023) Vol. 11, Iss. 3, pp. 359-359
Open Access | Times Cited: 22
Prediction of compressive strength and tensile strain of engineered cementitious composite using machine learning
Md Nasir Uddin, N. Shanmugasundaram, S. Praveenkumar, et al.
International Journal of Mechanics and Materials in Design (2024) Vol. 20, Iss. 4, pp. 671-716
Closed Access | Times Cited: 13
Prediction model for high arch dam stress during the operation period using LightGBM with MSSA and SHAP
Bo Li, Jing Ning, Shengmei Yang, et al.
Advances in Engineering Software (2024) Vol. 192, pp. 103635-103635
Closed Access | Times Cited: 7
Artificial neural network and random forest regression models for modelling fatty acid and tocopherol content in oil of winter rapeseed
Dragana Rajković, Ana Marjanović‐Jeromela, Lato Pezo, et al.
Journal of Food Composition and Analysis (2022) Vol. 115, pp. 105020-105020
Open Access | Times Cited: 34
Prediction and evaluation of surface roughness with hybrid kernel extreme learning machine and monitored tool wear
Minghui Cheng, Li Jiao, Pei Yan, et al.
Journal of Manufacturing Processes (2022) Vol. 84, pp. 1541-1556
Closed Access | Times Cited: 32
Assessing the Influence of Sensor-Induced Noise on Machine-Learning-Based Changeover Detection in CNC Machines
Vinai George Biju, Anna-Maria Schmitt, Bastian Engelmann
Sensors (2024) Vol. 24, Iss. 2, pp. 330-330
Open Access | Times Cited: 5
Predicting and Detecting Wear Properties of Arecanut Fiber Reinforced Carbon Composites Using Artificial Neural Networks
Tomasz Kik, Swapnaja Amol Ubale, K Rajesh Sai, et al.
SSRN Electronic Journal (2025)
Closed Access
Development of a resource-efficient real-time vibration-based tool condition monitoring system using PVDF accelerometers
Miha Kodrič, Jure Korbar, Miha Pogačar, et al.
Measurement (2025), pp. 117183-117183
Open Access
Investigations on the Surface Integrity and Wear Mechanisms of TiAlYN-Coated Tools in Inconel 718 Milling Operations
F.J.G. Silva, Naiara P. V. Sebbe, Rúben D. F. S. Costa, et al.
Materials (2024) Vol. 17, Iss. 2, pp. 443-443
Open Access | Times Cited: 4
Spatial Mapping and Prediction of Groundwater Quality Using Ensemble Learning Models and SHapley Additive exPlanations with Spatial Uncertainty Analysis
Shilong Yang, Danyuan Luo, Jiayao Tan, et al.
Water (2024) Vol. 16, Iss. 17, pp. 2375-2375
Open Access | Times Cited: 4
Predicting Penetration Depth in Ultra-High-Performance Concrete Targets under Ballistic Impact: An Interpretable Machine Learning Approach Augmented by Deep Generative Adversarial Network
Majid Khan, Muhammad Faisal Javed, N. Othman, et al.
Results in Engineering (2025), pp. 103909-103909
Open Access
Development of tool life prediction system for square end-mills based on database of servo motor current value
Hiroyuki Kodama, Makoto Suzuki, Kazuhito Ohashi
Journal of Advanced Mechanical Design Systems and Manufacturing (2025) Vol. 19, Iss. 1, pp. JAMDSM0001-JAMDSM0001
Open Access
Predicting Road Traffic Accidents—Artificial Neural Network Approach
Dragan Gatarić, Nenad Ruškić, Branko Aleksić, et al.
Algorithms (2023) Vol. 16, Iss. 5, pp. 257-257
Open Access | Times Cited: 11
Construction of a Cutting-Tool Wear Prediction Model through Ensemble Learning
Shen-Yung Lin, Chia-Jen Hsieh
Applied Sciences (2024) Vol. 14, Iss. 9, pp. 3811-3811
Open Access | Times Cited: 3
Stacking ensemble learning fused with whale optimisation algorithm based method for crown prediction of hot-rolled strip
Ling Ming Meng, Jingguo Ding, Haozhan Du, et al.
Ironmaking & Steelmaking Processes Products and Applications (2024) Vol. 51, Iss. 4, pp. 281-296
Closed Access | Times Cited: 3
Wear Prediction of Functionally Graded Composites Using Machine Learning
Reham Fathi, Minghe Chen, Mohammed Abdallah, et al.
Materials (2024) Vol. 17, Iss. 18, pp. 4523-4523
Open Access | Times Cited: 3
Optimization of Caper Drying Using Response Surface Methodology and Artificial Neural Networks for Energy Efficiency Characteristics
Hasan Demir, Hande Demi̇r, Biljana Lončar, et al.
Energies (2023) Vol. 16, Iss. 4, pp. 1687-1687
Open Access | Times Cited: 8
Sunflower Oil Winterization Using the Cellulose-Based Filtration Aid—Investigation of Oil Quality during Industrial Filtration Probe
Katarina Nedić Grujin, Tanja Lužaić, Lato Pezo, et al.
Foods (2023) Vol. 12, Iss. 12, pp. 2291-2291
Open Access | Times Cited: 8
Analysis of energy consumption of tobacco drying process based on industrial big data
Zijuan Li, Zixian Feng, Zezhou Zhang, et al.
Drying Technology (2023) Vol. 42, Iss. 2, pp. 307-317
Closed Access | Times Cited: 7
Biomass Higher Heating Value Estimation: A Comparative Analysis of Machine Learning Models
Ivan Brandić, Lato Pezo, Neven Voća, et al.
Energies (2024) Vol. 17, Iss. 9, pp. 2137-2137
Open Access | Times Cited: 2
Dynamic Data-Driven degradation method for monitoring remaining useful life of cutting tools
Yao Li, Zhengcai Zhao, Yucan Fu, et al.
Measurement (2024) Vol. 237, pp. 115247-115247
Closed Access | Times Cited: 2
Mechanical response of additively manufactured foam: A machine learning approach
Rajat Neelam, Shrirang Ambaji Kulkarni, H. S. Bharath, et al.
Results in Engineering (2022) Vol. 16, pp. 100801-100801
Open Access | Times Cited: 11
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