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The Frontiers of Deep Reinforcement Learning for Resource Management in Future Wireless HetNets: Techniques, Challenges, and Research Directions
Published 2022“…Then, we provide a comprehensive review of the most widely used DRL algorithms to address RRAM problems, including the value- and policy-based algorithms. …”
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123
Reinforcement Learning for Resilient Aerial-IRS Assisted Wireless Communications Networks in the Presence of Multiple Jammers
Published 2024“…<p dir="ltr">The evolving landscape of beyond 5G and 6G wireless communication systems in smart urban environments faces numerous interference-related challenges posed by legitimate and illicit devices. …”
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124
Meta Reinforcement Learning for UAV-Assisted Energy Harvesting IoT Devices in Disaster-Affected Areas
Published 2024“…In this context, we formulate the problem as a non-linear programming (NLP) optimization problem aimed at maximizing the total EH IoT devices and determining the optimal trajectory paths for UAVs while adhering to the constraints related to the maximum time duration, the UAVs’ maximum energy consumption, and the minimum data rate to achieve a reliable transmission. Due to the complexity of the problem, the combinatorial nature of the formulated problem, and the difficulty of obtaining the optimal solution using conventional optimization problems, we propose a lightweight meta-RL solution capable of solving the problem by learning the system dynamics. …”
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Multigrid solvers in reconfigurable hardware. (c2006)
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masterThesis -
127
Measuring ripple effect for object-oriented programs. (c2004)
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masterThesis -
128
UML-based regression testing for OO software
Published 2010“…For the second phase, we present algorithms for detecting system level changes in the interaction overview diagram. …”
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129
Higher-order statistics (HOS)-based deconvolution for ultrasonic nondestructive evaluation (NDE) of materials
Published 1997“…The proposed techniques are: i) a batch-type deconvolution method using the complex bicepstrum algorithm, and ii) automatic ultrasonic defect classification system using a modular learning strategy. …”
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masterThesis -
130
Collision-Free Autonomous Navigation Solution for Mobile Wheeled
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doctoralThesis -
131
Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management
Published 2019Get full text
doctoralThesis -
132
A Novel Centrality-Based Approach for Link Prediction
Published 2025“…Link prediction aims to identify missing or future connections between entities of a complex system, when modeled as a network. This research problem has attracted significant attention due to its relevance in numerous fields. …”
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masterThesis -
133
Assigning proctors to exams using scatter search. (c2006)
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masterThesis -
134
DRL-Based IRS-Assisted Secure Visible Light Communications
Published 2022“…Therefore, we proposed a Deep Reinforcement Learning (DRL) solution based on Deep Deterministic Policy Gradient (DDPG) algorithm to solve the highly complex SC problem by adjusting the BF weights and mirror orientations. …”
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135
A Novel Internal Model Control Scheme for Adaptive Tracking of Nonlinear Dynamic Plants
Published 2006“…The use of U-model alleviates the computational complexity of on-line nonlinear controller design that arises when using other modelling frame works such as NARMAX model. …”
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136
Improving Rule Set Based Software Quality Prediction
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137
Data-driven robust model predictive control for greenhouse temperature control and energy utilisation assessment
Published 2023“…The artificial neural network demonstrates a higher prediction accuracy and is used as the system model in the proposed control framework. A robust model predictive control strategy, based on the minimax objective function and particle swarm optimisation algorithm, is developed to handle the uncertainties in the system. …”
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138
Leveraging UAVs for Coverage in Cell-Free Vehicular Networks
Published 2020“…Then, we leverage deep reinforcement learning to propose an approach for learning the optimal trajectories of the deployed UAVs to efficiently maximize the coverage, where we adopt Actor-Critic algorithm to learn the vehicular environment and its dynamics to handle the complex continuous action space. …”
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139
A hybrid EDF/FIFO queue for efficient real time flow handling
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conferenceObject -
140
Efficient Seismic Volume Compression using the Lifting Scheme
Published 2000“…Finally a runlength plus a Huffman encoding are applied for binary coding of the quantized coefficients.…”
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