Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems
Jared Willard, Xiaowei Jia, Shaoming Xu, et al.
ACM Computing Surveys (2022) Vol. 55, Iss. 4, pp. 1-37
Open Access | Times Cited: 299

Showing 1-25 of 299 citing articles:

Applications of Physics-Informed Neural Networks in Power Systems - A Review
Bin Huang, Jianhui Wang
IEEE Transactions on Power Systems (2022) Vol. 38, Iss. 1, pp. 572-588
Closed Access | Times Cited: 187
Combustion machine learning: Principles, progress and prospects
Matthias Ihme, Wai Tong Chung, Aashwin Mishra
Progress in Energy and Combustion Science (2022) Vol. 91, pp. 101010-101010
Open Access | Times Cited: 159
A Review of Physics-Informed Machine Learning in Fluid Mechanics
Pushan Sharma, Wai Tong Chung, Bassem Akoush, et al.
Energies (2023) Vol. 16, Iss. 5, pp. 2343-2343
Open Access | Times Cited: 85
Assessing the Physical Realism of Deep Learning Hydrologic Model Projections Under Climate Change
Sungwook Wi, Scott Steinschneider
Water Resources Research (2022) Vol. 58, Iss. 9
Closed Access | Times Cited: 84
Enhancing predictive skills in physically-consistent way: Physics Informed Machine Learning for hydrological processes
Pravin Bhasme, Jenil Vagadiya, Udit Bhatia
Journal of Hydrology (2022) Vol. 615, pp. 128618-128618
Open Access | Times Cited: 80
Review of Pedestrian Trajectory Prediction Methods: Comparing Deep Learning and Knowledge-Based Approaches
Raphael Korbmacher, Antoine Tordeux
IEEE Transactions on Intelligent Transportation Systems (2022) Vol. 23, Iss. 12, pp. 24126-24144
Open Access | Times Cited: 80
A review of machine learning methods applied to structural dynamics and vibroacoustic
Barbara Zaparoli Cunha, Christophe Droz, Abdelmalek Zine, et al.
Mechanical Systems and Signal Processing (2023) Vol. 200, pp. 110535-110535
Open Access | Times Cited: 72
Recent applications of AI to environmental disciplines: A review
A Kónya, Peyman Nematzadeh
The Science of The Total Environment (2023) Vol. 906, pp. 167705-167705
Closed Access | Times Cited: 57
Deep learning for water quality
Wei Zhi, Alison Appling, Heather E. Golden, et al.
Nature Water (2024) Vol. 2, Iss. 3, pp. 228-241
Closed Access | Times Cited: 55
Long-term fatigue estimation on offshore wind turbines interface loads through loss function physics-guided learning of neural networks
Francisco de Nolasco Santos, Pietro D’Antuono, Koen Robbelein, et al.
Renewable Energy (2023) Vol. 205, pp. 461-474
Open Access | Times Cited: 44
A review of the application of artificial intelligence to nuclear reactors: Where we are and what's next
Qingyu Huang, Shinian Peng, Jian Deng, et al.
Heliyon (2023) Vol. 9, Iss. 3, pp. e13883-e13883
Open Access | Times Cited: 41
Knowledge-guided machine learning can improve carbon cycle quantification in agroecosystems
Licheng Liu, Wang Zhou, Kaiyu Guan, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 37
Lake Water Temperature Modeling in an Era of Climate Change: Data Sources, Models, and Future Prospects
Sebastiano Piccolroaz, Senlin Zhu, Robert Ladwig, et al.
Reviews of Geophysics (2024) Vol. 62, Iss. 1
Open Access | Times Cited: 36
Multilevel domain decomposition-based architectures for physics-informed neural networks
Victorita Dolean, Alexander Heinlein, Siddhartha Mishra, et al.
Computer Methods in Applied Mechanics and Engineering (2024) Vol. 429, pp. 117116-117116
Open Access | Times Cited: 22
Hybrid physics-machine learning models for predicting rate of penetration in the Halahatang oil field, Tarim Basin
Shengjie Jiao, Wei Li, Zhuolun Li, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 20
Machine Learning-Integrated Sustainable Engineering and Energy Systems
M. Sarat Chandra Prasad, M. Dhanalakshmi, M. Mohan, et al.
Advances in systems analysis, software engineering, and high performance computing book series (2024), pp. 74-98
Closed Access | Times Cited: 18
Explainable artificial intelligence: A survey of needs, techniques, applications, and future direction
Melkamu Mersha, Khang Nhứt Lâm, Joseph Wood, et al.
Neurocomputing (2024) Vol. 599, pp. 128111-128111
Closed Access | Times Cited: 15
Towards the next generation of Geospatial Artificial Intelligence
Gengchen Mai, Yiqun Xie, Xiaowei Jia, et al.
International Journal of Applied Earth Observation and Geoinformation (2025) Vol. 136, pp. 104368-104368
Open Access | Times Cited: 1
Can machine learning accelerate process understanding and decision‐relevant predictions of river water quality?
Charuleka Varadharajan, Alison Appling, Bhavna Arora, et al.
Hydrological Processes (2022) Vol. 36, Iss. 4
Open Access | Times Cited: 51
A framework for machine learning of model error in dynamical systems
Matthew E. Levine, Andrew M. Stuart
Communications of the American Mathematical Society (2022) Vol. 2, Iss. 7, pp. 283-344
Open Access | Times Cited: 44
On Strictly Enforced Mass Conservation Constraints for Modeling the Rainfall-Runoff Process
Jonathan Frame, Paul Ullrich, Grey Nearing, et al.
EarthArXiv (California Digital Library) (2022)
Open Access | Times Cited: 44
Toward impact-based monitoring of drought and its cascading hazards
Amir AghaKouchak, Laurie S. Huning, Mojtaba Sadegh, et al.
Nature Reviews Earth & Environment (2023) Vol. 4, Iss. 8, pp. 582-595
Closed Access | Times Cited: 35
Digital Twins in Wind Energy: Emerging Technologies and Industry-Informed Future Directions
Florian Stadtmann, Adil Rasheed, Trond Kvamsdal, et al.
IEEE Access (2023) Vol. 11, pp. 110762-110795
Open Access | Times Cited: 28
On strictly enforced mass conservation constraints for modelling the Rainfall‐Runoff process
Jonathan Frame, Frederik Kratzert, Hoshin V. Gupta, et al.
Hydrological Processes (2023) Vol. 37, Iss. 3
Closed Access | Times Cited: 27
Physics-Guided Data-Driven Seismic Inversion: Recent progress and future opportunities in full-waveform inversion
Youzuo Lin, James Theiler, Brendt Wohlberg
IEEE Signal Processing Magazine (2023) Vol. 40, Iss. 1, pp. 115-133
Closed Access | Times Cited: 26
Page 1 - Next Page

Scroll to top