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Time-series forecasting of Bitcoin prices using high-dimensional features: a machine learning approach
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Springer
, 2020 , Article)
© 2020, Springer-Verlag London Ltd., part of Springer Nature. Bitcoin is a decentralized cryptocurrency, which is a type of digital asset that provides the basis for peer-to-peer financial transactions based on blockchain ...
Machine learning-based management of electric vehicles charging: Towards highly-dispersed fast chargers
(
MDPI AG
, 2020 , Article)
Coordinated charging of electric vehicles (EVs) improves the overall efficiency of the power grid as it avoids distribution system overloads, increases power quality, and decreases voltage fluctuations. Moreover, the ...
Flow-based intrusion detection algorithm for supervisory control and data acquisition systems: A real-time approach
(
John Wiley and Sons Inc
, 2021 , Article)
Intrusion detection in supervisory control and data acquisition (SCADA) systems is integral because of the critical roles of these systems in industries. However, available approaches in the literature lack representative ...
A Deep Reinforcement Learning Framework for Data Compression in Uplink NOMA-SWIPT Systems
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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 ...
FSC-Set: Counting, Localization of Football Supporters Crowd in the Stadiums
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Institute of Electrical and Electronics Engineers Inc.
, 2022 , Article)
Counting the number of people in a crowd has gained attention in the last decade. Due to its benefit to many applications such as crowd behavior analysis, crowd management, and video surveillance systems, etc. Counting ...
RL-PDNN: Reinforcement Learning for Privacy-Aware Distributed Neural Networks in IoT Systems
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Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Due to their high computational and memory demand, deep learning applications are mainly restricted to high-performance units, e.g., cloud and edge servers. Particularly, in Internet of Things (IoT) systems, the data ...
On Designing Smart Agents for Service Provisioning in Blockchain-powered Systems
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IEEE Computer Society
, 2021 , Article)
Service provisioning systems assign users to service providers according to allocation criteria that strike an optimal trade-off between users Quality of Experience (QoE) and the operation cost endured by providers. These ...
Deep Reinforcement Learning for Network Selection over Heterogeneous Health Systems
(
IEEE Computer Society
, 2022 , Article)
Smart health systems improve our quality oflife by integrating diverse information and technologies into health and medical practices. Such technologies can significantly improve the existing health services. However, ...
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 ...
Reinforcement learning approaches for efficient and secure blockchain-powered smart health systems
(
Elsevier B.V.
, 2021 , Article)
Emerging technological innovation toward e-Health transition is a worldwide priority for ensuring people's quality of life. Hence, secure exchange and analysis of medical data amongst diverse organizations would increase ...