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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:

Optimized machine learning with hyperparameter tuning and response surface methodology for predicting tribological performance in bio‐composite materials
S. Saravanakumar, S. Sathiyamurthy, Vinoth Viswanathan, et al.
Polymer Composites (2024) Vol. 45, Iss. 10, pp. 9421-9439
Closed Access | Times Cited: 15

Showing 15 citing articles:

Enhancing machining accuracy of banana fiber-reinforced composites with ensemble machine learning
S. Saravanakumar, S. Sathiyamurthy, V. Vinoth
Measurement (2024) Vol. 235, pp. 114912-114912
Closed Access | Times Cited: 21
Influence of treatment and fly ash fillers on the mechanical and tribological properties of banana fiber epoxy composites: experimental and ANN-RSM modeling
S. Saravanakumar, S. Sathiyamurthy, G. Selvakumar, et al.
Composite Interfaces (2025), pp. 1-33
Closed Access | Times Cited: 3
Enhancing mechanical, degradation, and tribological properties of biocomposites via treatment and alumina content
S. Saravanakumar, S. Sathiyamurthy, Ravikumar Natarajan, et al.
Journal of Reinforced Plastics and Composites (2025)
Closed Access | Times Cited: 1
ADVANCED ENSEMBLE MACHINE LEARNING PREDICTION TO ENHANCE THE ACCURACY OF ABRASIVE WATERJET MACHINING FOR BIOCOMPOSITES
Gopi Periyappillai, S. Sathiyamurthy, S. Saravanakumar
Materials Chemistry and Physics (2024), pp. 130175-130175
Closed Access | Times Cited: 5
A Short Review: Tribology in Machining to Understand Conventional and Latest Modeling Methods with Machine Learning
Seisuke Kano
Machines (2025) Vol. 13, Iss. 2, pp. 81-81
Open Access
Optimization and Finite Element Analysis Simulation on Mechanical Behavior of Wire Arc Additive Manufacturing for SS316L Using Response Surface Methodology
Anantha R. Sethuraman, Vijayaragavan Elumalai, T. Lakshmanan, et al.
Journal of Materials Engineering and Performance (2025)
Closed Access
Machine Learning Prediction and Optimization of Cold Metal Transfer Welding Parameters for Enhancing the Mechanical and Microstructural Properties of Austenitic-Ferritic Stainless-Steel Joints
R. Ravikumar, A. Mathivanan
Journal of Materials Engineering and Performance (2025)
Closed Access
Assessment of mechanical, thermal, and sliding wear performance of chemically treated alumina‐filled biocomposites using machine learning and response surface methodology
V.S. Shaisundaram, S. Saravanakumar, Rajesh Mohan, et al.
Polymer Composites (2025)
Closed Access
Natural Fiber Composites: A Comprehensive Review on Machine Learning Methods
Timothy K. Mulenga, Sanjay Mavinkere Rangappa, Suchart Siengchin
Archives of Computational Methods in Engineering (2025)
Closed Access
Advanced ensemble machine learning and response surface methodology for optimizing and predicting tribological performance of CMT-WAAM fabricated Al5356 alloy
M.K. Nagarajan, Manikandan Arumugam
International Journal on Interactive Design and Manufacturing (IJIDeM) (2025)
Closed Access
Synergistic Effects of NaOH Treatment and Ceramic Fillers on the Mechanical and Tribological Behavior of Roselle Fiber-Reinforced Epoxy Composites
S. Saravanakumar, S. Sathiyamurthy, Ravikumar Natarajan, et al.
Fibers and Polymers (2025)
Closed Access
Optimization of Friction Stir Processing Parameters to Improve Mechanical Properties and Microstructure of Al5083 Aluminum Alloy Reinforced with AlCoCrFeNiSi High-Entropy Alloy
S. Kumaravel, Suresh Perinpanayagam
Physica Scripta (2024) Vol. 99, Iss. 10, pp. 105903-105903
Closed Access | Times Cited: 3
Optimizing Cold Metal Transfer-Wire Arc Additive Manufacturing Parameters for Enhanced Mechanical Properties and Microstructure of ER5356 Aluminum Alloy Using Artificial Neural Network and Response Surface Methodology
N Manikandan, Manikandan Arumugam
Journal of Materials Engineering and Performance (2024)
Closed Access | Times Cited: 3
A novel normalized fatigue progressive damage model for complete stress levels based on artificial neural network
Jie Zhou, Zhen Wu, Zhengliang Liu, et al.
International Journal of Fatigue (2024) Vol. 187, pp. 108447-108447
Closed Access | Times Cited: 1
Predictive analysis of tensile strength ratios in laminated bamboo composites: Unraveling the stochastic impact of ply angle variations through machine learning model
Deepak Kumar, Apurba Mandal
Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science (2024)
Closed Access
Impact behavior analysis of carbon fiber‐reinforced polymer composites via a data‐driven scheme with Artificial Neural Network approach
Shivashankar Hiremath, Young-Hoon Jung, J. E. Oh, et al.
Polymer Composites (2024)
Closed Access
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