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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:

Tool wear monitoring by ensemble learning and sensor fusion using power, sound, vibration, and AE signals
Vahid Nasir, Sina Dibaji, Kareem Alaswad, et al.
Manufacturing Letters (2021) Vol. 30, pp. 32-38
Closed Access | Times Cited: 31

Showing 1-25 of 31 citing articles:

Tool wear state recognition and prediction method based on laplacian eigenmap with ensemble learning model
Yang Xie, Shangshang Gao, Chaoyong Zhang, et al.
Advanced Engineering Informatics (2024) Vol. 60, pp. 102382-102382
Closed Access | Times Cited: 15
Acoustic emission monitoring of wood materials and timber structures: A critical review
Vahid Nasir, Samuel Ayanleye, Siavash Kazemirad, et al.
Construction and Building Materials (2022) Vol. 350, pp. 128877-128877
Open Access | Times Cited: 49
An online monitoring method of milling cutter wear condition driven by digital twin
Xintian Zi, Shangshang Gao, Yang Xie
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 10
Tool Wear Prediction Based on Multi-Information Fusion and Genetic Algorithm-Optimized Gaussian Process Regression in Milling
Zhiwen Huang, Jiajie Shao, Weicheng Guo, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-16
Open Access | Times Cited: 18
A novel tool wear monitoring approach based on attention mechanism and gated recurrent unit
Lei Zhang, Zhengcai Zhao, Shichen Zheng, et al.
Machining Science and Technology (2025), pp. 1-25
Closed Access
Compressive Strength Prediction of Rice Husk Ash Concrete Using a Hybrid Artificial Neural Network Model
Chuanqi Li, Xiancheng Mei, Daniel Dias, et al.
Materials (2023) Vol. 16, Iss. 8, pp. 3135-3135
Open Access | Times Cited: 15
A Deep-Learning-Based Multi-Modal Sensor Fusion Approach for Detection of Equipment Faults
Ömer Küllü, E. Miné Cinar
Machines (2022) Vol. 10, Iss. 11, pp. 1105-1105
Open Access | Times Cited: 20
Structured fault information-aided canonical variate analysis model for dynamic process monitoring
Siwei Lou, Ping Wu, Chunjie Yang, et al.
Journal of Process Control (2023) Vol. 124, pp. 54-69
Closed Access | Times Cited: 10
The Role of Drying Schedule and Conditioning in Moisture Uniformity in Wood: A Machine Learning Approach
Sohrab Rahimi, Vahid Nasir, Stavros Avramidis, et al.
Polymers (2023) Vol. 15, Iss. 4, pp. 792-792
Open Access | Times Cited: 9
Fiber Quality Prediction Using Nir Spectral Data: Tree-Based Ensemble Learning VS Deep Neural Networks
Vahid Nasir, Syed Danish Ali, Ahmad Mohammadpanah, et al.
Wood and Fiber Science (2023) Vol. 55, Iss. 1, pp. 100-115
Open Access | Times Cited: 7
Combining Artificial Neural Network and Response Surface Methodology to Optimize the Drilling Operating Parameters of MDF Panels
Bogdan Bedelean, Mihai Ispas, Sergiu Răcășan
Forests (2023) Vol. 14, Iss. 11, pp. 2254-2254
Open Access | Times Cited: 7
A chemistry-based explainable machine learning model based on NIR spectra for predicting wood properties and understanding wavelength selection
Laurence R. Schimleck, Samuel Ayanleye, Stavros Avramidis, et al.
Wood Material Science and Engineering (2023) Vol. 18, Iss. 6, pp. 2116-2127
Closed Access | Times Cited: 6
The Use of Multilayer Perceptron (MLP) to Reduce Delamination during Drilling into Melamine Faced Chipboard
Albina Jegorowa, Jarosław Kurek, Michał Kruk, et al.
Forests (2022) Vol. 13, Iss. 6, pp. 933-933
Open Access | Times Cited: 8
Multisensor data fusion and machine learning to classify wood products and predict workpiece characteristics during milling
Mehieddine Derbas, André Jaquemod, Stephan Frömel-Frybort, et al.
CIRP journal of manufacturing science and technology (2023) Vol. 47, pp. 103-115
Closed Access | Times Cited: 4
Intelligent parameters reconfiguration system for enhancing machine tools sustainability using real-time data-driven: an experimental cutting speed investigation
Murillo Skrzek, Anderson Luis Szejka, Fernando Mas
International Journal of Computer Integrated Manufacturing (2024), pp. 1-22
Closed Access | Times Cited: 1
Wood moisture monitoring and classification in kiln‐dried timber
Sohrab Rahimi, Vahid Nasir, Stavros Avramidis, et al.
Structural Control and Health Monitoring (2021) Vol. 29, Iss. 4
Open Access | Times Cited: 10
Prediction of Machining Condition Using Time Series Imaging and Deep Learning in Slot Milling of Titanium Alloy
Faramarz Hojati, Bahman Azarhoushang, Amir Daneshi, et al.
Journal of Manufacturing and Materials Processing (2022) Vol. 6, Iss. 6, pp. 145-145
Open Access | Times Cited: 7
Machine learning-based prediction of internal moisture variation in kiln-dried timber
Sohrab Rahimi, Stavros Avramidis, Farrokh Sassani, et al.
Wood Material Science and Engineering (2023) Vol. 19, Iss. 2, pp. 499-510
Closed Access | Times Cited: 2
Intelligent Lumber Production (Sawmill 4.0): Opportunities, Challenges, and Pathways to Adoption
Vahid Nasir, Sohrab Rahimi, Ahmad Mohammadpanah, et al.
(2024), pp. 213-231
Closed Access
Methodology and Experimental Verification for Predicting the Remaining Useful Life of Milling Cutters Based on Hybrid CNN-LSTM-Attention-PSA
Meilu Zhu, Ji Zhang, Lingfan Bu, et al.
Machines (2024) Vol. 12, Iss. 11, pp. 752-752
Open Access
Predicting wood moisture classes by sound frequency spectra and Explainable Machine Learning during milling
Mehieddine Derbas, Timothy M. Young, Stephan Frömel-Frybort, et al.
Wood Material Science and Engineering (2024), pp. 1-12
Closed Access
On the Stability and Homogeneous Ensemble of Feature Selection for Predictive Maintenance: A Classification Application to Tool Condition Monitoring in Milling
Maryam Assafo, J. Philipp Städter, Tenia Meisel, et al.
(2023)
Open Access | Times Cited: 1
On the Stability and Homogeneous Ensemble of Feature Selection for Predictive Maintenance: A Classification Application for Tool Condition Monitoring in Milling
Maryam Assafo, J. Philipp Städter, Tenia Meisel, et al.
Sensors (2023) Vol. 23, Iss. 9, pp. 4461-4461
Open Access | Times Cited: 1
Review Paper on Development of Nano Inserts for Machining HRSA Materials for Aerospace Applications
Shashidhar Kotian, K. Narayanaswamy, Dasharath S. M
Journal of Mines Metals and Fuels (2023), pp. 416-423
Open Access | Times Cited: 1
Application of wavelet ratio between acoustic emission and cutting force signal decomposing in intelligent monitoring of cutting tool wear when turning SKD 61
Dung Hoang Tien, Pham Thi Thieu Thoa, Trinh Nguyen Duy
International Journal on Interactive Design and Manufacturing (IJIDeM) (2023) Vol. 18, Iss. 1, pp. 525-539
Closed Access | Times Cited: 1
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