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 …

[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 …

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 …

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) …

Will artificial intelligence make energy cleaner? Evidence of nonlinearity

CC Lee, J Yan - Applied Energy, 2024 - Elsevier
Energy plays a vital part in stimulating economic progress, and the shift towards a cleaner
energy system is highly significant for ensuring the sustainable development of the …

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 …

Do the benefits outweigh the disadvantages? Exploring the role of artificial intelligence in renewable energy

M Qin, W Hu, X Qi, T Chang - Energy Economics, 2024 - Elsevier
Probing the essential role of artificial intelligence in the energy market is crucial to improving
the development of renewable energy. The research adopts the full and sub sample …

Machine learning-based intrusion detection for smart grid computing: A survey

N Sahani, R Zhu, JH Cho, CC Liu - ACM Transactions on Cyber-Physical …, 2023 - dl.acm.org
Machine learning (ML)-based intrusion detection system (IDS) approaches have been
significantly applied and advanced the state-of-the-art system security and defense …