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A neural networks algorithm for data path synthesis
Published 2003“…This paper presents a deterministic parallel algorithm to solve the data path allocation problem in high-level synthesis. …”
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A method for data path synthesis using neural networks
Published 2017“…Presents a deterministic parallel algorithm to solve the data path allocation problem in high-level synthesis. …”
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A Novel Hybrid Genetic-Whale Optimization Model for Ontology Learning from Arabic Text
Published 2019“…The previously published research on Arabic ontology learning from text falls into three categories: developing manually hand-crafted rules, using ordinary supervised/unsupervised machine learning algorithms, or a hybrid of these two approaches. The model proposed in this work contributes to Arabic ontology learning in two ways. …”
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A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT
Published 2023“…<p dir="ltr">In mobile edge computing (MEC), it is difficult to recognise an optimum solution that can perform in limited energy by selecting the best communication path and components. This research proposed a hybrid model for energy-efficient cluster formation and a head selection (E-CFSA) algorithm based on convolutional neural networks (CNNs) and a modified k-mean clustering (MKM) method for MEC. …”
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Intelligent Rapidly-Exploring Random Tree Star Algorithm
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Hybrid Optimized Approaches for Routing and Resource Reservation Protocols in Optical Networks
Published 2021“…Route-Model computes routing information which is integrated with the first-fit algorithm. …”
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A systolic algorithm for VLSI design of a 1/N rate Viterbi decoder
Published 1989“…The second consists of a matrix of simpler processors which update survived paths and provide the decoded output. The systolic algorithm is modeled in AHPL to verify functional correctness. …”
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Nonlinear analysis of shell structures using image processing and machine learning
Published 2023“…The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. …”
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A parallel ant colony optimization to globally optimize area in high-level synthesis. (c2011)
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Design of A Theoretical Framework For A Real-Time Fire Evacuation Guidance System
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Guidance, Control and Trajectory Tracking of Small Fixed Wing Unmanned Aerial Vehicles (UAV's)
Published 2009Get full text
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Advanced Quantum Control with Ensemble Reinforcement Learning: A Case Study on the XY Spin Chain
Published 2025“…<p dir="ltr">This research presents an ensemble Reinforcement Learning (RL) approach that combines Deep Q-Network (DQN) and Proximal Policy Optimization (PPO) algorithms to tackle quantum control problems. This research aims to use the complementary strengths of DQN and PPO algorithms to develop robust and adaptive control policies for noisy and uncertain quantum systems. …”
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On the Provisioning of Ultra-Reliable Low-Latency Services in IoT Networks with Multipath Diversity
Published 2020“…Simulation results are presented for both parts of the thesis to illustrate the effectiveness of the proposed solutions and algorithms in comparison with optimal solutions and baseline algorithms.…”
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Virtual Inertia Support in Power Systems for High Penetration of Renewables—Overview of Categorization, Comparison, and Evaluation of Control Techniques
Published 2022“…Integrating intelligent methods, such as fuzzy logic, genetic algorithm, non-convex optimization, and heuristic optimization, signify intelligent control methods. …”
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Morphology for Planar Hexagonal Modular Self-Reconfigurable Robotic Systems
Published 2009Get full text
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Optimal Routing Protocol in Multimedia Wireless Sensor Networks
Published 2011Get full text
doctoralThesis