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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:

Prediction of surface roughness in turning using vibration features selected by largest Lyapunov exponent based ICEEMDAN decomposition
Vikrant Guleria, Vivek Kumar, Pradeep Kumar Singh
Measurement (2022) Vol. 202, pp. 111812-111812
Closed Access | Times Cited: 28

Showing 1-25 of 28 citing articles:

Improving milling tool wear prediction through a hybrid NCA-SMA-GRU deep learning model
Zhongyuan Che, Chong Peng, T. Warren Liao, et al.
Expert Systems with Applications (2024) Vol. 255, pp. 124556-124556
Closed Access | Times Cited: 7
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
Surface roughness and tool wear monitoring in turning processes through vibration analysis using PSD and GRMS
Roumaissa Bouchama, Mohamed Lamine Bouhalais, Abdelhakim Cherfia
The International Journal of Advanced Manufacturing Technology (2024) Vol. 130, Iss. 7-8, pp. 3537-3552
Closed Access | Times Cited: 5
Chatter Identification in Milling of Titanium Alloy Using Machine Learning Approaches with Non-Linear Features of Cutting Force and Vibration Signatures
Viswajith S. Nair, K. Rameshkumar, S. Saravanamurugan
International Journal of Prognostics and Health Management (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 5
The effect of cutting parameters on defect detection based on recurrence analysis of cutting force signals obtained from GFRP composite milling
Krzysztof Kęcik, Krzysztof Ciecieląg
Measurement (2024) Vol. 239, pp. 115406-115406
Open Access | Times Cited: 3
Hob vibration signal denoising and effective features enhancing using improved complete ensemble empirical mode decomposition with adaptive noise and fuzzy rough sets
Han Zhou, Ping Yan, Qin Huang, et al.
Expert Systems with Applications (2023) Vol. 233, pp. 120989-120989
Closed Access | Times Cited: 10
Surface Roughness Prediction of Titanium Alloy during Abrasive Belt Grinding Based on an Improved Radial Basis Function (RBF) Neural Network
Kun Shan, Yashuang Zhang, Yingduo Lan, et al.
Materials (2023) Vol. 16, Iss. 22, pp. 7224-7224
Open Access | Times Cited: 9
An integrated framework for a multi-material surface roughness prediction model in CNC turning using theoretical and machine learning methods
Kristin S. Bennett, Jose M. DePaiva, Stephen C. Veldhuis
The International Journal of Advanced Manufacturing Technology (2024) Vol. 131, Iss. 7-8, pp. 3579-3598
Closed Access | Times Cited: 3
Milling surface roughness prediction method based on spatiotemporal ensemble learning
Shi Zeng, Dechang Pi, Tao Xu
The International Journal of Advanced Manufacturing Technology (2023) Vol. 128, Iss. 1-2, pp. 91-119
Closed Access | Times Cited: 8
Optimisation of extrusion process parameters to make ABS-PC filament for 3D printing using Taguchi-GRA technique
Praveen Kumar, Pardeep Gupta, Indraj Singh
Advances in Materials and Processing Technologies (2023), pp. 1-22
Closed Access | Times Cited: 7
Understanding Electric Current Effects on Tribological Behaviors of Instantaneous Current-Carrying Pair with Recurrence Plot
Huan Zhao, Wei Wang, Xiaojun Xu, et al.
Journal of Tribology (2024) Vol. 147, Iss. 5
Closed Access | Times Cited: 2
Surface roughness prediction in turning processes using CEEMD-based vibration signal denoising and LSTM networks
A. Andrews, Manisekar Kondal
Proceedings of the Institution of Mechanical Engineers Part E Journal of Process Mechanical Engineering (2024)
Closed Access | Times Cited: 2
An expert system for vibration-based surface roughness prediction using firefly algorithm and LSTM network
A. Andrews, K. Manisekar, F. Michael Thomas Rex, et al.
Journal of the Brazilian Society of Mechanical Sciences and Engineering (2023) Vol. 45, Iss. 8
Closed Access | Times Cited: 5
PCA-IEM-DARNN: An enhanced dual-stage deep learning prediction model for concrete dam deformation based on feature decomposition
Xinyu Kang, Yanlong Li, Ye Zhang, et al.
Measurement (2024), pp. 115664-115664
Closed Access | Times Cited: 1
A comprehensive approach with DTW-driven IMF selection, multi-domain fusion, and TSA-based feature selection for compound fault diagnosis
A. Andrews, Manisekar Kondal
Measurement (2024) Vol. 242, pp. 115974-115974
Closed Access | Times Cited: 1
Surface roughness prediction based on fusion of dynamic-static data
Jiayi Wang, Xiaodan Wu, Qian Huang, et al.
Measurement (2024), pp. 116351-116351
Closed Access | Times Cited: 1
Prediction and pre-warning of step-like landslide displacement based on deep learning coupled with ICEEMDAN
Zheng Zhou, Yanlong Li, Ye Zhang, et al.
Measurement (2024), pp. 116585-116585
Closed Access | Times Cited: 1
Surface roughness estimation using vibration characteristics extracted by variational mode decomposition in turning
Vikrant Guleria, Vivek Kumar, Pradeep K. Singh
Engineering Research Express (2024) Vol. 6, Iss. 2, pp. 025426-025426
Open Access
A Novel Hybrid RSM-ANN Model for Surface Roughness Prediction in Turning of Al 6061 Alloy
Vivek Kumar, Vikrant Guleria, Sunil Kumar
Journal of Advanced Manufacturing Systems (2024) Vol. 23, Iss. 04, pp. 969-984
Closed Access
Vibration Signal Analysis for Surface Roughness Prediction in Machining
Roumaissa Bouchama, Abdelhakim Cherfia
(2024), pp. 1-4
Closed Access
Research on Ultrasonic Signal Denoising Method Based on Cpo-Iceemdan Combined with Fastica
Jiao Sun, Songsong Li, Xiao‐Ming Chen, et al.
(2024)
Closed Access
Classification of drilling surface roughness on computer numerical control (CNC) machine tools based on Mobilenet_v3_small_improved
Gang Chen, Peng Wang, Jiajun Tu, et al.
Mechanical sciences (2024) Vol. 15, Iss. 2, pp. 567-586
Open Access
Systematic error separation and compensation for complex surface in OMM
Yue Chen, Gaiyun He, Chenglin Yao, et al.
The International Journal of Advanced Manufacturing Technology (2024) Vol. 135, Iss. 5-6, pp. 2475-2489
Closed Access
Internet of Things and hybrid models-based interpretation systems for surface roughness estimation
R. S. Umamaheswara Raju, Ravi Kumar Kottala, B. Madhava Varma, et al.
Artificial intelligence for engineering design analysis and manufacturing (2024) Vol. 38
Closed Access
Enhanced concrete crack detection using nonlinear ultrasonic signal denoising and feature enhancement with CEEMDAN, VMD and GRU
Jianfeng Liu, Kui Wang, Mingjie Zhao, et al.
Measurement Science and Technology (2024) Vol. 36, Iss. 1, pp. 016164-016164
Closed Access
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