A review on digital twin technology in smart grid, transportation system and smart city: Challenges and future

M Jafari, A Kavousi-Fard, T Chen, M Karimi - IEEE Access, 2023 - ieeexplore.ieee.org
With recent advances in information and communication technology (ICT), the bleeding
edge concept of digital twin (DT) has enticed the attention of many researchers to …

Artificial intelligence in healthcare: review, ethics, trust challenges & future research directions

P Kumar, S Chauhan, LK Awasthi - Engineering Applications of Artificial …, 2023 - Elsevier
The use of artificial intelligence (AI) in medicine is beginning to alter current procedures in
prevention, diagnosis, treatment, amelioration, cure of disease and other physical and …

Deep learning based attack detection for cyber-physical system cybersecurity: A survey

J Zhang, L Pan, QL Han, C Chen… - IEEE/CAA Journal of …, 2021 - ieeexplore.ieee.org
With the booming of cyber attacks and cyber criminals against cyber-physical systems
(CPSs), detecting these attacks remains challenging. It might be the worst of times, but it …

Deep learning models for solar irradiance forecasting: A comprehensive review

P Kumari, D Toshniwal - Journal of Cleaner Production, 2021 - Elsevier
The growing human population in this modern society hugely depends on the energy to
fulfill their day-to-day needs and activities. Renewable energy sources, especially solar …

[HTML][HTML] Artificial intelligence in renewable energy: A comprehensive bibliometric analysis

L Zhang, J Ling, M Lin - Energy Reports, 2022 - Elsevier
In recent years, artificial intelligence methods have been widely applied to solve issues
related to renewable energy because of their ability to solve nonlinear and complex data …

DeepFed: Federated deep learning for intrusion detection in industrial cyber–physical systems

B Li, Y Wu, J Song, R Lu, T Li… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
The rapid convergence of legacy industrial infrastructures with intelligent networking and
computing technologies (eg, 5G, software-defined networking, and artificial intelligence) …

A review of deep learning for renewable energy forecasting

H Wang, Z Lei, X Zhang, B Zhou, J Peng - Energy Conversion and …, 2019 - Elsevier
As renewable energy becomes increasingly popular in the global electric energy grid,
improving the accuracy of renewable energy forecasting is critical to power system planning …

Smart grid cyber-physical attack and defense: A review

H Zhang, B Liu, H Wu - IEEE Access, 2021 - ieeexplore.ieee.org
Recent advances in the cyber-physical smart grid (CPSG) have enabled a broad range of
new devices based on the information and communication technology (ICT). However, these …

Machine learning driven smart electric power systems: Current trends and new perspectives

MS Ibrahim, W Dong, Q Yang - Applied Energy, 2020 - Elsevier
The current power systems are undergoing a rapid transition towards their more active,
flexible, and intelligent counterpart smart grid, which brings about tremendous challenges in …

Deep learning in the industrial internet of things: Potentials, challenges, and emerging applications

RA Khalil, N Saeed, M Masood, YM Fard… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
Recent advances in the Internet of Things (IoT) are giving rise to a proliferation of
interconnected devices, allowing the use of various smart applications. The enormous …