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Now showing items 11-19 of 19
I-SEE: Intelligent, Secure, and Energy-Efficient Techniques for Medical Data Transmission Using Deep Reinforcement Learning
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Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
The rapid evolution of remote health monitoring applications is foreseen to be a crucial solution for facing an unpredictable health crisis and improving the quality of life. However, such applications come with many ...
LEARNING-BASED CONTROL OF CANCER CHEMOTHERAPY TREATMENT
(
Elsevier B.V.
, 2017 , Article)
The increasing threat of cancer to human life and the improvement in survival rate of this disease due to effective treatment has promoted research in various related fields. This research has shaped clinical trials and ...
A Unified Framework for Differentiated Services in Intelligent Healthcare Systems
(
IEEE
, 2022 , Article)
The Coronavirus disease 2019 (COVID-19) outbreak continues to significantly expose the vulnerabilities of healthcare systems around the world. These unprecedented circumstances create an opportunity for improving healthcare ...
A Deep Reinforcement Learning Framework for Data Compression in Uplink NOMA-SWIPT Systems
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
<comment< Non-orthogonal multiple access (NOMA) shall play an important role in the current and foreseeable design of 5G and beyond networks. NOMA allows multiple users to share the same time-frequency ...
Reinforcement Learning-based Control of Signalized Intersections having Platoons
(
Institute of Electrical and Electronics Engineers Inc.
, 2022 , Article)
Smart transportation cities are based on intelligent systems and data sharing while human drivers generally have limited capabilities and imperfect observations in traffics. The perception of Connected and Autonomous Vehicle ...
Data-Driven Load Frequency Control Based on Multi-Agent Reinforcement Learning With Attention Mechanism
(
Institute of Electrical and Electronics Engineers Inc.
, 2022 , Article)
With the massive penetration of renewable energy, traditional reinforcement learning algorithms suffer from slow convergence and area control error (ACE) in interconnected power systems. This paper proposes data-driven ...
DRL-HEMS: Deep Reinforcement Learning Agent for Demand Response in Home Energy Management Systems Considering Customers and Operators Perspectives
(
Institute of Electrical and Electronics Engineers Inc.
, 2022 , Article)
With the smart grid and smart homes development, different data are made available, providing a source for training algorithms, such as deep reinforcement learning (DRL), in smart grid applications. These algorithms allowed ...
Can automated driving prevent crashes with distracted Pedestrians? An exploration of motion planning at unsignalized Mid-block crosswalks
(
Elsevier
, 2022 , Article)
Pedestrian distraction may provoke severe difficulties in automated vehicle (AV) control, which may significantly affect the safety performance of AVs, especially at unsignalized mid-block crosswalks (UMCs). However, there ...
Optimal operation of reverse osmosis desalination process with deep reinforcement learning methods
(
Springer
, 2024 , Article)
The reverse osmosis (RO) process is a well-established desalination technology, wherein energy-efficient techniques and advanced process control methods significantly reduce production costs. This study proposes an optimal ...