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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:

A robust low data solution: Dimension prediction of semiconductor nanorods
Xiaoli Liu, Yang Xu, Jiali Li, et al.
Computers & Chemical Engineering (2021) Vol. 150, pp. 107315-107315
Open Access | Times Cited: 12

Showing 12 citing articles:

Vibration analysis of embedded porous nanobeams under thermal effects using boosting machine learning algorithms and semi-analytical approach
Aiman Tariq, Büşra Uzun, Babür Deliktaş, et al.
Mechanics of Advanced Materials and Structures (2024), pp. 1-24
Closed Access | Times Cited: 14
Advanced Modeling and Optimization Strategies for Process Synthesis
Efstratios N. Pistikopoulos, Yuhe Tian
Annual Review of Chemical and Biomolecular Engineering (2024) Vol. 15, Iss. 1, pp. 81-103
Closed Access | Times Cited: 12
Classification of white blood cells with SVM by selecting SqueezeNet and LIME properties by mRMR method
Erdal Başaran
Signal Image and Video Processing (2022) Vol. 16, Iss. 7, pp. 1821-1829
Closed Access | Times Cited: 28
Artificial intelligence based operational strategy development and implementation for vibration reduction of a supercritical steam turbine shaft bearing
Waqar Muhammad Ashraf, Yasir Rafique, Ghulam Moeen Uddin, et al.
Alexandria Engineering Journal (2021) Vol. 61, Iss. 3, pp. 1864-1880
Open Access | Times Cited: 34
Application of machine learning methodology for investigating the vibration behavior of functionally graded porous nanobeams
Aiman Tariq, Büşra Uzun, Babür Deliktaş, et al.
The Journal of Strain Analysis for Engineering Design (2024)
Closed Access | Times Cited: 5
Assessment of machine learning methods predicting the axial vibration frequencies of microbars
Aiman Tariq, Büşra Uzun, Babür Deliktaş, et al.
ZAMM ‐ Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik (2023) Vol. 104, Iss. 3
Closed Access | Times Cited: 8
A Deep Learning Hybrid Framework Combining an Efficient Evolutionary Algorithm for Complex Many-Objective Optimization of Sustainable Triple CO2 Feed Methanol Production
Hong‐Tao Cao, Yue Li, Chenglin Chang, et al.
ACS Sustainable Chemistry & Engineering (2024) Vol. 12, Iss. 17, pp. 6682-6696
Closed Access | Times Cited: 2
Stable local interpretable model-agnostic explanations based on a variational autoencoder
Xu Xiang, Hong Yu, Ye Wang, et al.
Applied Intelligence (2023) Vol. 53, Iss. 23, pp. 28226-28240
Closed Access | Times Cited: 5
Linearizing nonlinear dynamics using deep learning
Akhil Ahmed, Ehecatl Antonio del Río-Chanona, Mehmet Mercangöz
Computers & Chemical Engineering (2022) Vol. 170, pp. 108104-108104
Open Access | Times Cited: 8
Machine Learning-Aided Process Design for Microwave-Assisted Ammonia Production
Md Abdullah Al Masud, Alazar Araia, Yuxin Wang, et al.
Systems and Control Transactions (2024) Vol. 3, pp. 316-321
Closed Access
Machine learning‐aided process design using limited experimental data: A microwave‐assisted ammonia synthesis case study
Md Abdullah Al Masud, Alazar Araia, Yuxin Wang, et al.
AIChE Journal (2024)
Open Access
COVERT: A classless approach to generating balanced datasets for process modelling
Isaac Severinsen, Wei Yu, Timothy Gordon Walmsley, et al.
ISA Transactions (2023) Vol. 144, pp. 1-10
Open Access | Times Cited: 1
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