Machine learning-assisted self-powered intelligent sensing systems based on triboelectricity
Z Tian, J Li, L Liu, H Wu, X Hu, M Xie, Y Zhu, X Chen… - Nano Energy, 2023 - Elsevier
The advancement of 5 G and the Internet of Things (IoT) has ushered in an era of super-
interconnected intelligence, which promises high-quality social development. Triboelectric …
interconnected intelligence, which promises high-quality social development. Triboelectric …
Challenges and opportunities in deep reinforcement learning with graph neural networks: A comprehensive review of algorithms and applications
Deep reinforcement learning (DRL) has empowered a variety of artificial intelligence fields,
including pattern recognition, robotics, recommendation systems, and gaming. Similarly …
including pattern recognition, robotics, recommendation systems, and gaming. Similarly …
Artificial intelligence implication on energy sustainability in Internet of Things: A survey
The massive number of Internet of Things (IoT) devices connected to the Internet is
continuously increasing. The operations of these devices rely on consuming huge amounts …
continuously increasing. The operations of these devices rely on consuming huge amounts …
Deep SARSA-based reinforcement learning approach for anomaly network intrusion detection system
The growing evolution of cyber-attacks imposes a risk in network services. The search of
new techniques is essential to detect and classify dangerous attacks. In that regard, deep …
new techniques is essential to detect and classify dangerous attacks. In that regard, deep …
[HTML][HTML] Reinforcement learning-based routing protocols in vehicular ad hoc networks for intelligent transport system (its): A survey
J Lansky, AM Rahmani, M Hosseinzadeh - Mathematics, 2022 - mdpi.com
Today, the use of safety solutions in Intelligent Transportation Systems (ITS) is a serious
challenge because of novel progress in wireless technologies and the high number of road …
challenge because of novel progress in wireless technologies and the high number of road …
[HTML][HTML] Applicability of deep reinforcement learning for efficient federated learning in massive iot communications
To build intelligent model learning in conventional architecture, the local data are required to
be transmitted toward the cloud server, which causes heavy backhaul congestion, leakage …
be transmitted toward the cloud server, which causes heavy backhaul congestion, leakage …
Defect identification for oil and gas pipeline safety based on autonomous deep learning network
M Zhang, Y Guo, Q Xie, Y Zhang, D Wang… - Computer …, 2022 - Elsevier
The safety detection for oil and gas pipelines is more and more worthy of attention. It not only
promotes the development of pipeline safety work, but also provides a guarantee for …
promotes the development of pipeline safety work, but also provides a guarantee for …
Reinforcement learning in the sky: A survey on enabling intelligence in ntn-based communications
Non terrestrial networks (NTN) involving 'in the sky'objects such as low-earth orbit satellites,
high altitude platform systems (HAPs) and Unmanned Aerial Vehicles (UAVs) are expected …
high altitude platform systems (HAPs) and Unmanned Aerial Vehicles (UAVs) are expected …
Blockchain-enabled deep reinforcement learning approach for performance optimization on the internet of things
T Alam - Wireless Personal Communications, 2022 - Springer
Abstract Internet of Things (IoT) networks are rapidly expanding, which requires adequate
and reliable infrastructure and a large amount of data. The IoT device security and technical …
and reliable infrastructure and a large amount of data. The IoT device security and technical …
Dqra: Deep quantum routing agent for entanglement routing in quantum networks
Quantum routing plays a key role in the development of the next-generation network system.
In particular, an entangled routing path can be constructed with the help of quantum …
In particular, an entangled routing path can be constructed with the help of quantum …