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modeling algorithm » scheduling algorithm (Expand Search)
cosine algorithm » colony algorithm (Expand Search)
coding algorithm » colony algorithm (Expand Search), scheduling algorithm (Expand Search)
path modeling » spatial modeling (Expand Search)
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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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Predicting Compression Modes and Split Decisions for HEVC Video Coding Using Machine Learning Techniques
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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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Large language models for code completion: A systematic literature review
Published 2024“…Different techniques can achieve code completion, and recent research has focused on Deep Learning methods, particularly Large Language Models (LLMs) utilizing Transformer algorithms. …”
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Synthesis of MVL Functions - Part I: The Genetic Algorithm Approach
Published 2006“…Multiple-Valued Logic (MVL) has been used in the design of a number of logic systems, including memory, multi-level data communication coding, and a number of special purpose digital processors. …”
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Optimized FPGA Implementation of PWAM-Based Control of Three—Phase Nine—Level Quasi Impedance Source Inverter
Published 2019“…Since, PWAM control algorithm is more complex than PSCPWM, FPGA based implementation for PWAM control is discussed. …”
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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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Sensitivity analysis and genetic algorithm-based shear capacity model for basalt FRC one-way slabs reinforced with BFRP bars
Published 2023“…Finally, a design equation that can predict the shear capacity of one-way BFRC-BFRP slabs was proposed based on genetic algorithm. The proposed model showed the best prediction accuracy compared to the available design codes and guidelines with a mean of predicted to experimental shear capacities (V<sub>pred</sub>/V<sub>exp</sub>) ratio of 0.97 and a coefficient of variation of 17.91%.…”
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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. …”