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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:

Simulation-assisted machine learning for operational digital twins
Christos Pylianidis, Val Snow, Hiske Overweg, et al.
Environmental Modelling & Software (2021) Vol. 148, pp. 105274-105274
Open Access | Times Cited: 36

Showing 1-25 of 36 citing articles:

Design, Modeling and Implementation of Digital Twins
Mariana Segovia, Joaquín García-Alfaro
Sensors (2022) Vol. 22, Iss. 14, pp. 5396-5396
Open Access | Times Cited: 193
Machine Learning-Assisted Low-Dimensional Electrocatalysts Design for Hydrogen Evolution Reaction
Jin Li, Naiteng Wu, Jian Zhang, et al.
Nano-Micro Letters (2023) Vol. 15, Iss. 1
Open Access | Times Cited: 66
A survey of applications of artificial intelligence and machine learning in future mobile networks-enabled systems
İbrahim Yazıcı, Ibraheem Shayea, Jafri Din
Engineering Science and Technology an International Journal (2023) Vol. 44, pp. 101455-101455
Open Access | Times Cited: 56
Exploding the myths: An introduction to artificial neural networks for prediction and forecasting
Holger R. Maier, Stefano Galelli, Saman Razavi, et al.
Environmental Modelling & Software (2023) Vol. 167, pp. 105776-105776
Open Access | Times Cited: 52
Climate change impacts on crop yields: A review of empirical findings, statistical crop models, and machine learning methods
Tongxi Hu, Xuesong Zhang, Sami Khanal, et al.
Environmental Modelling & Software (2024) Vol. 179, pp. 106119-106119
Closed Access | Times Cited: 19
A 3D functional plant modelling framework for agricultural digital twins
Christos Mitsanis, William Hurst, Bedir Teki̇nerdoğan
Computers and Electronics in Agriculture (2024) Vol. 218, pp. 108733-108733
Open Access | Times Cited: 18
Data-driven surrogate modeling: Introducing spatial lag to consider spatial autocorrelation of flooding within urban drainage systems
Heng Li, Chunxiao Zhang, Min Chen, et al.
Environmental Modelling & Software (2023) Vol. 161, pp. 105623-105623
Open Access | Times Cited: 30
Unleashing the potential of IoT, Artificial Intelligence, and UAVs in contemporary agriculture: A comprehensive review
Mustapha El Alaoui, Khalid El Amraoui, Lhoussaine Masmoudi, et al.
Journal of Terramechanics (2024) Vol. 115, pp. 100986-100986
Closed Access | Times Cited: 10
Hybrid voting-GA ensemble learning for multi-class fault detection in digital twin-driven IIoT systems
Ezz El‐Din Hemdan, Samar M. Zayed, Gamal Attiya, et al.
Computing (2025) Vol. 107, Iss. 2
Closed Access | Times Cited: 1
Mixing process-based and data-driven approaches in yield prediction
Bernardo Maestrini, Gordan Mimić, P.A.J. van Oort, et al.
European Journal of Agronomy (2022) Vol. 139, pp. 126569-126569
Open Access | Times Cited: 31
An Efficient Fault Diagnosis Framework for Digital Twins Using Optimized Machine Learning Models in Smart Industrial Control Systems
Samar M. Zayed, Gamal Attiya, Ayman El‐Sayed, et al.
International Journal of Computational Intelligence Systems (2023) Vol. 16, Iss. 1
Open Access | Times Cited: 21
Digital twin challenges in biodiversity modelling
Athanasios Trantas, Ruduan Plug, Paolo Pileggi, et al.
Ecological Informatics (2023) Vol. 78, pp. 102357-102357
Open Access | Times Cited: 17
Transforming agrifood production systems and supply chains with digital twins
Asaf Tzachor, Catherine E. Richards, Scott Jeen
npj Science of Food (2022) Vol. 6, Iss. 1
Open Access | Times Cited: 27
Physics-Informed Neural Network Solution of Point Kinetics Equations for a Nuclear Reactor Digital Twin
Konstantinos Prantikos, Lefteri H. Tsoukalas, Alexander Heifetz
Energies (2022) Vol. 15, Iss. 20, pp. 7697-7697
Open Access | Times Cited: 23
Can machine learning models provide accurate fertilizer recommendations?
Takashi Tanaka, G.B.M. Heuvelink, Taro Mieno, et al.
Precision Agriculture (2024) Vol. 25, Iss. 4, pp. 1839-1856
Open Access | Times Cited: 5
Cyber-Governance of the Natural World: The Implications of Digital Twins in Environmental Governance
Paulan Korenhof, Brett Metcalfe, Adam Henschke
(2025)
Closed Access
Integrating machine learning with agroecosystem modelling: Current state and future challenges
Meshach Ojo Aderele, A K Srivastava, Klaus Butterbach‐Bahl, et al.
European Journal of Agronomy (2025) Vol. 168, pp. 127610-127610
Open Access
Recent Progress in the Design and Application of Machine Learning for the Hydrogen Evolution Reaction in Electrocatalysis and Photocatalysis
Kaifeng Zhang, Xudong Wang, Yanjing Su
Materials Today Communications (2025), pp. 112462-112462
Closed Access
A definition and taxonomy of digital twins: case studies with machine learning and scientific applications
Adam Weingram, C.Y. Cui, Stephanie Lin, et al.
Frontiers in High Performance Computing (2025) Vol. 3
Open Access
Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future
Theodor Borangiu, Damien Trentesaux, Paulo Leitão
Studies in computational intelligence (2023)
Closed Access | Times Cited: 9
Achieving Zero Defected Products in Diary 4.0 using Digital Twin and Machine Vision
Fotios K. Konstantinidis, Vasiliki Balaska, Symeon Symeonidis, et al.
(2023), pp. 528-534
Closed Access | Times Cited: 7
Digital twin maturity levels: a theoretical framework for defining capabilities and goals in the life and environmental sciences
Brett Metcalfe, Hendriek C. Boshuizen, J.D. Bulens, et al.
F1000Research (2023) Vol. 12, pp. 961-961
Open Access | Times Cited: 6
Developing data-driven learning models to predict urban stormwater runoff volume
Rachel Wood-Ponce, Ghada Diab, Zeyu Liu, et al.
Urban Water Journal (2024) Vol. 21, Iss. 5, pp. 549-564
Closed Access | Times Cited: 1
Domain adaptation with transfer learning for pasture digital twins
Christos Pylianidis, Michiel Kallenberg, Ioannis N. Athanasiadis
Environmental Data Science (2024) Vol. 3
Open Access | Times Cited: 1
Digital Twin Technology in the Gas Industry: A Comparative Simulation Study
Jaeseok Yun, Sung-Yeon Kim, Jinmin Kim
Sustainability (2024) Vol. 16, Iss. 14, pp. 5864-5864
Open Access | Times Cited: 1
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