Search alternatives:
using algorithm » cosine algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
element » elements (Expand Search)
tracking » training (Expand Search), taking (Expand Search)
using algorithm » cosine algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
element » elements (Expand Search)
tracking » training (Expand Search), taking (Expand Search)
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Sample intelligence-based progressive hedging algorithms for the stochastic capacitated reliable facility location problem
Published 2024“…To manage uncertainty and decide effectively, stochastic programming (SP) methods are often employed. Two commonly used SP methods are approximation methods, i.e., Sample Average Approximation (SAA), and decomposition methods, i.e., Progressive Hedging Algorithm (PHA). …”
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Bird’s Eye View feature selection for high-dimensional data
Published 2023“…This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …”
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Robust Control Of Sampled Data Systems
Published 2020“…They then present a numerical controller design algorithm based on the derived bounds. Examples are used for demonstration.…”
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Robust Control Of Sampled Data Systems
Published 2020“…They then present a numerical controller design algorithm based on the derived bounds. Examples are used for demonstration.…”
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Robust Control Of Sampled Data Systems
Published 2020“…They then present a numerical controller design algorithm based on the derived bounds.Examples are used for demonstration.…”
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A MIMO Sampling-Rate-Dependent Controller
Published 2014“…The SRD controller makes use of higher sampling rates for larger variations in the desired trajectories. …”
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Chlorophyll-a concentrations in the Arabian Gulf waters of arid region: A case study from the northern coast of Qatar
Published 2022“…All the results were validated using field measurements, in-situ measurements, and laboratory analyses of field samples. …”
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Classifying Maqams of Qur'anic Recitations Using Deep Learning
Published 2021“…Technological advancement can be utilized for automatic classification of these melodies which can then be used by students for self-learning. Using state-of-the-art deep learning algorithms, this research focuses on the classification of the eight popular maqamat (plural of maqam). …”
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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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A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method
Published 2022“…To deal with the data-imbalance issue, this research develops an efficient hybrid network-based IDS model (HNIDS), which is utilized using the enhanced genetic algorithm and particle swarm optimization(EGA-PSO) and improved random forest (IRF) methods. …”
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Bootstrap-based Aggregations and their Stability in Feature Selection
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Accuracy of an internationally validated genetic-guided warfarin dosing algorithm compared to a clinical algorithm in an Arab population
Published 2024“…After reaching warfarin maintenance dose, the dose was recalculated using the GWD and median absolute error (MAE) and the percentage of warfarin doses within 20% of the actual dose were calculated and compared for the two algorithms. …”
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An L2 Gap Metric Identification Algorithm
Published 2020“…In this paper, an L2-gap metric identification algorithm is proposed. The algorithm uses a set of frequency response samples to come up with rational models so that the L2-gap between the observations and the identified model is minimized. …”
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Parallel Algorithm for Hardware Implementation of Inverse Halftoning
Published 2005“…The 15-pixel parallel version of the algorithm was tested on sample images and a simple and effective method has been used to overcome quality degradation due to pixel loss in the proposed algorithm. …”
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Parallel algorithm for hardware implementation of inverse halftoning
Published 2005“…The 15-pixel parallel version of the algorithm was tested on sample images and a simple and effective method has been used to overcome quality degradation due to pixel loss in the proposed algorithm. …”
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