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Now showing items 11-18 of 18
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 ...
Reinforcement learning-based control of drug dosing for cancer chemotherapy treatment
(
Elsevier Inc.
, 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 ...
Optimal adaptive control of drug dosing using integral reinforcement learning
(
Elsevier Inc.
, 2019 , Article)
In this paper, a reinforcement learning (RL)-based optimal adaptive control approach is proposed for the continuous infusion of a sedative drug to maintain a required level of sedation. To illustrate the proposed method, ...
Reinforcement learning-based school energy management system
(
MDPI AG
, 2020 , Article)
Energy efficiency is a key to reduced carbon footprint, savings on energy bills, and sustainability for future generations. For instance, in hot climate countries such as Qatar, buildings are high energy consumers due to ...
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 ...
Data-Driven Load Frequency Control Based on Multi-Agent Reinforcement Learning With Attention Mechanism
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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 ...
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 ...