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process optimization » model optimization (Expand Search)
design optimization » bayesian optimization (Expand Search)
edge process » due process (Expand Search), edge processing (Expand Search), peace process (Expand Search)
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its design » i design (Expand Search), ii design (Expand Search), first design (Expand Search)
process optimization » model optimization (Expand Search)
design optimization » bayesian optimization (Expand Search)
edge process » due process (Expand Search), edge processing (Expand Search), peace process (Expand Search)
binary edge » binary image (Expand Search)
binary its » binary pairs (Expand Search)
its design » i design (Expand Search), ii design (Expand Search), first design (Expand Search)
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Comparisons of computation rate performance for different offloading algorithms.for N = 10, 20, 30.
Published 2025Subjects: -
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Comparison of total time consumed for different offloading algorithms.for N = 10, 20, 30.
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The evolution of the Wireless Power Transfer (WPT) time fraction β over simulation frames.
Published 2025Subjects: -
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CDF of task latency, approximated as the inverse of the achieved computation rate.
Published 2025Subjects: -
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Algorithm for generating hyperparameter.
Published 2024“…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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The Pseudo-Code of the IRBMO Algorithm.
Published 2025“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …”
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Results of machine learning algorithm.
Published 2024“…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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ROC comparison of machine learning algorithm.
Published 2024“…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”