A deep reinforcement learning-based cooperative approach for multi-intersection traffic signal control
Abstract Recently, Adaptive Traffic Signal Control (ATSC) in the multi-intersection system is
considered as one of the most critical issues in Intelligent Transportation Systems (ITS) …
considered as one of the most critical issues in Intelligent Transportation Systems (ITS) …
Learning sequential distribution system restoration via graph-reinforcement learning
A distribution service restoration algorithm as a fundamental resilient paradigm for system
operators provides an optimally coordinated, resilient solution to enhance the restoration …
operators provides an optimally coordinated, resilient solution to enhance the restoration …
Deep Q-learning with Q-matrix transfer learning for novel fire evacuation environment
Deep reinforcement learning (RL) is achieving significant success in various applications
like control, robotics, games, resource management, and scheduling. However, the …
like control, robotics, games, resource management, and scheduling. However, the …
Energy drive and management of smart grids with high penetration of renewable sources of wind unit and solar panel
L Wei, C Yi, J Yun - International Journal of Electrical Power & Energy …, 2021 - Elsevier
This paper proposes a novel reinforcement learning based energy drive and management
in smart grids incorporating the uncertain behavior of the electric vehicles and renewable …
in smart grids incorporating the uncertain behavior of the electric vehicles and renewable …
Predictive maintenance model for IIoT-based manufacturing: A transferable deep reinforcement learning approach
The Industrial Internet of Things (IIoT) is crucial for accurately assessing the state of complex
equipment in order to perform predictive maintenance (PdM) successfully. However, existing …
equipment in order to perform predictive maintenance (PdM) successfully. However, existing …
Towards 6G: fast and self-adaptive dynamic bandwidth allocation for next-generation mobile fronthaul
6G networks will deliver dynamic and immersive applications that bridge the real and digital
worlds. The next-generation passive optical access network is a potential optical transport …
worlds. The next-generation passive optical access network is a potential optical transport …
Multipath TCP meets transfer learning: A novel edge-based learning for industrial IoT
We consider a fifth-generation (5G)-empowered future Industrial IoT (IIoT) networking
problem where IIoT machines are capable of communicating and sharing their data …
problem where IIoT machines are capable of communicating and sharing their data …
Diagnosis of COVID-19 pneumonia based on graph convolutional network
X Liang, Y Zhang, J Wang, Q Ye, Y Liu, J Tong - Frontiers in Medicine, 2021 - frontiersin.org
A three-dimensional (3D) deep learning method is proposed, which enables the rapid
diagnosis of coronavirus disease 2019 (COVID-19) and thus significantly reduces the …
diagnosis of coronavirus disease 2019 (COVID-19) and thus significantly reduces the …
A dynamic multi-model transfer based short-term load forecasting
L Xiao, Q Bai, B Wang - Applied Soft Computing, 2024 - Elsevier
The integration of renewable energy sources in power systems has resulted in increased
complexity in dispatch management, necessitating higher accuracy in short-term load …
complexity in dispatch management, necessitating higher accuracy in short-term load …
[HTML][HTML] Indoor emergency path planning based on the Q-learning optimization algorithm
S Xu, Y Gu, X Li, C Chen, Y Hu, Y Sang… - … International Journal of …, 2022 - mdpi.com
The internal structure of buildings is becoming increasingly complex. Providing a scientific
and reasonable evacuation route for trapped persons in a complex indoor environment is …
and reasonable evacuation route for trapped persons in a complex indoor environment is …