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Hybrid wind-diesel-battery system planning considering multiple different wind turbine technologies installation
(
Elsevier Ltd
, 2020 , Article)
Today, renewable resources have become one of the main pillars of electricity generation because of the constant reduction in their costs. In this regard, wind energy possesses the highest share in installed capacity and ...
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 ...
Distributed CNN Inference on Resource-Constrained UAVs for Surveillance Systems: Design and Optimization
(
Institute of Electrical and Electronics Engineers Inc.
, 2022 , Article)
Unmanned aerial vehicles (UAVs) have attracted great interest in the last few years owing to their ability to cover large areas and access difficult and hazardous target zones, which is not the case of traditional systems ...
On Designing Smart Agents for Service Provisioning in Blockchain-powered Systems
(
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 ...
Energy-Aware Distributed Edge ML for mHealth Applications with Strict Latency Requirements
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Edge machine learning (Edge ML) is expected to serve as a key enabler for real-time mobile health (mHealth) applications. However, its reliability is governed by the limited energy and computing resources of user equipment ...
Optimal User-Edge Assignment in Hierarchical Federated Learning Based on Statistical Properties and Network Topology Constraints
(
IEEE Computer Society
, 2022 , Article)
Distributed learning algorithms aim to leverage distributed and diverse data stored at users' devices to learn a global phenomena by performing training amongst participating devices and periodically aggregating their local ...
B5G: Predictive Container Auto-Scaling for Cellular Evolved Packet Core
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
In order to maintain a satisfactory performance in the midst of rapid growth of mobile traffic, the mobile network infrastructure needs to be scaled. Thus there has been significant interest in scalability of mobile core ...
Kinetic modeling of microalgae growth and CO2 bio-fixation using central composite design statistical approach
(
Elsevier B.V.
, 2020 , Article)
The optimum growth (μ), CO2 bio-fixation (RCO2) rates and the energy ratio (ER) of microalgae Chlorella vulgaris (C.v) were identified using central composite design statistical approach (CCD-SA). μ and RCO2 parameters ...
New Deep Learning-Based Approach for Wind Turbine Output Power Modeling and Forecasting
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
An intelligent machine learning-based method is developed in this paper for modeling and prediction of the wind turbine (WT) output power. The developed technique makes use of the advanced machine learning models for ...
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 ...