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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:

Deep Reinforcement Learning for Cybersecurity Assessment of Wind Integrated Power Systems
Xiaorui Liu, Juan Ospina, Charalambos Konstantinou
IEEE Access (2020) Vol. 8, pp. 208378-208394
Open Access | Times Cited: 47

Showing 1-25 of 47 citing articles:

Deep Reinforcement Learning for Cyber Security
Thanh Thi Nguyen, Vijay Janapa Reddi
IEEE Transactions on Neural Networks and Learning Systems (2021) Vol. 34, Iss. 8, pp. 3779-3795
Open Access | Times Cited: 315
Cyber-Physical Energy Systems Security: Threat Modeling, Risk Assessment, Resources, Metrics, and Case Studies
Ioannis Zografopoulos, Juan Ospina, Xiaorui Liu, et al.
IEEE Access (2021) Vol. 9, pp. 29775-29818
Open Access | Times Cited: 194
Deep Learning in Smart Grid Technology: A Review of Recent Advancements and Future Prospects
Mohamed Massaoudi, Haitham Abu‐Rub, Shady S. Refaat, et al.
IEEE Access (2021) Vol. 9, pp. 54558-54578
Open Access | Times Cited: 132
Consumer, Commercial, and Industrial IoT (In)Security: Attack Taxonomy and Case Studies
Christos Xenofontos, Ioannis Zografopoulos, Charalambos Konstantinou, et al.
IEEE Internet of Things Journal (2021) Vol. 9, Iss. 1, pp. 199-221
Open Access | Times Cited: 103
Machine learning for cybersecurity in smart grids: A comprehensive review-based study on methods, solutions, and prospects
Tarek Berghout, Mohamed Benbouzid, S. M. Muyeen
International Journal of Critical Infrastructure Protection (2022) Vol. 38, pp. 100547-100547
Open Access | Times Cited: 76
Integrating sustainability into cybersecurity: insights from machine learning based topic modeling
Krishnashree Achuthan, Sriram Sankaran, Swapnoneel Roy, et al.
Discover Sustainability (2025) Vol. 6, Iss. 1
Open Access | Times Cited: 2
Deep Reinforcement Learning for Smart Grid Operations: Algorithms, Applications, and Prospects
Yuanzheng Li, Chaofan Yu, Mohammad Shahidehpour, et al.
Proceedings of the IEEE (2023) Vol. 111, Iss. 9, pp. 1055-1096
Closed Access | Times Cited: 38
Identifying critical weak points of power-gas integrated energy system based on complex network theory
Chenwei Zhang, Ying Wang, Tao Zheng, et al.
Reliability Engineering & System Safety (2024) Vol. 246, pp. 110054-110054
Closed Access | Times Cited: 11
Advancements in Digital Twin Technology and Machine Learning for Energy Systems: A Comprehensive Review of Applications in Smart Grids, Renewable Energy, and Electric Vehicle Optimisation
Opy Das, Muhammad Hamza Zafar, Filippo Sanfilippo, et al.
Energy Conversion and Management X (2024), pp. 100715-100715
Open Access | Times Cited: 8
Toward a Secure and Resilient All-Renewable Energy Grid for Smart Cities
Charalambos Konstantinou
IEEE Consumer Electronics Magazine (2021) Vol. 11, Iss. 1, pp. 33-41
Closed Access | Times Cited: 51
Hardware-assisted detection of firmware attacks in inverter-based cyberphysical microgrids
Abraham Peedikayil Kuruvila, Ioannis Zografopoulos, Kanad Basu, et al.
International Journal of Electrical Power & Energy Systems (2021) Vol. 132, pp. 107150-107150
Open Access | Times Cited: 48
Review of Deep Reinforcement Learning and Its Application in Modern Renewable Power System Control
Qingyan Li, Tao Lin, Qianyi Yu, et al.
Energies (2023) Vol. 16, Iss. 10, pp. 4143-4143
Open Access | Times Cited: 17
Cyber resilience of power electronics-enabled power systems: A review
Jiazuo Hou, Chenxi Hu, Shunbo Lei, et al.
Renewable and Sustainable Energy Reviews (2023) Vol. 189, pp. 114036-114036
Closed Access | Times Cited: 16
On the Feasibility of Load-Changing Attacks in Power Systems During the COVID-19 Pandemic
Juan Ospina, Xiaorui Liu, Charalambos Konstantinou, et al.
IEEE Access (2020) Vol. 9, pp. 2545-2563
Open Access | Times Cited: 41
On the Feasibility Guarantees of Deep Reinforcement Learning Solutions for Distribution System Operation
Mohammad Mehdi Hosseini, Masood Parvania
IEEE Transactions on Smart Grid (2023) Vol. 14, Iss. 2, pp. 954-964
Closed Access | Times Cited: 12
A Risk Assessment Framework for Cyber-Physical Security in Distribution Grids with Grid-Edge DERs
Xue Gao, Mazhar Ali, Wei Sun
Energies (2024) Vol. 17, Iss. 7, pp. 1587-1587
Open Access | Times Cited: 4
Challenges, evaluation and opportunities for open-world learning
Mayank Kejriwal, Eric Kildebeck, Robert J. Steininger, et al.
Nature Machine Intelligence (2024) Vol. 6, Iss. 6, pp. 580-588
Closed Access | Times Cited: 4
Predicting CVSS Metric via Description Interpretation
Joana C. Costa, Tiago Roxo, João B. F. Sequeiros, et al.
IEEE Access (2022) Vol. 10, pp. 59125-59134
Open Access | Times Cited: 21
Load-Altering Attacks Against Power Grids Under COVID-19 Low-Inertia Conditions
Subhash Lakshminarayana, Juan Ospina, Charalambos Konstantinou
IEEE Open Access Journal of Power and Energy (2022) Vol. 9, pp. 226-240
Open Access | Times Cited: 19
Multi-objective solution of optimal power flow based on TD3 deep reinforcement learning algorithm
Bowei Sun, Minggang Song, Ang Li, et al.
Sustainable Energy Grids and Networks (2023) Vol. 34, pp. 101054-101054
Closed Access | Times Cited: 12
Real-time out-of-step prediction control to prevent emerging blackouts in power systems: A reinforcement learning approach
Hossein Hassani, Roozbeh Razavi–Far, Mehrdad Saif
Applied Energy (2022) Vol. 314, pp. 118861-118861
Closed Access | Times Cited: 18
Datadriven false data injection attacks against cyber-physical power systems
Jiwei Tian, Buhong Wang, Jing Li, et al.
Computers & Security (2022) Vol. 121, pp. 102836-102836
Closed Access | Times Cited: 17
Leveraging Deep Learning to Strengthen the Cyber-Resilience of Renewable Energy Supply Chains: A Survey
Malka N. Halgamuge
IEEE Communications Surveys & Tutorials (2024) Vol. 26, Iss. 3, pp. 2146-2175
Closed Access | Times Cited: 3
False data injection attack in smart grid: Attack model and reinforcement learning-based detection method
Xixiang Lin, Dou An, Feifei Cui, et al.
Frontiers in Energy Research (2023) Vol. 10
Open Access | Times Cited: 7
A Deep Deterministic Policy Gradient Learning Approach to Missile Autopilot Design
Angelo Candeli, G. De Tommasi, Dario Giuseppe Lui, et al.
IEEE Access (2022) Vol. 10, pp. 19685-19696
Open Access | Times Cited: 11
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