Proposed Algorithm. حسب Hend Bayoumi (22693738)

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Comparisons between ADAM and NADAM optimizers. حسب Hend Bayoumi (22693738)

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Comparisons of computation rate performance for different offloading algorithms.for N = 10, 20, 30. حسب Hend Bayoumi (22693738)

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Comparison of total time consumed for different offloading algorithms.for N = 10, 20, 30. حسب Hend Bayoumi (22693738)

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Algorithm for generating hyperparameter. حسب Balraj Preet Kaur (20370832)

"…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. 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. …"

An Example of a WPT-MEC Network. حسب Hend Bayoumi (22693738)

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Related Work Summary. حسب Hend Bayoumi (22693738)

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Simulation parameters. حسب Hend Bayoumi (22693738)

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Training losses for N = 10. حسب Hend Bayoumi (22693738)

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Performance Comparison of State-of-the-Art WPT-MEC Offloading Methods. حسب Hend Bayoumi (22693738)

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The evolution of the Wireless Power Transfer (WPT) time fraction β over simulation frames. حسب Hend Bayoumi (22693738)

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Normalized computation rate for N = 10. حسب Hend Bayoumi (22693738)

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CDF of task latency, approximated as the inverse of the achieved computation rate. حسب Hend Bayoumi (22693738)

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Comparison between Bisection and Newton-Raphson in terms of (A) total time consumed, and (B) maximum computation rate. حسب Hend Bayoumi (22693738)

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Summary of Notations Used in this paper. حسب Hend Bayoumi (22693738)

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Results of machine learning algorithm. حسب Balraj Preet Kaur (20370832)

"…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. 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. …"

ROC comparison of machine learning algorithm. حسب Balraj Preet Kaur (20370832)

"…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. 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. …"

Best optimizer results of Lightbgm. حسب Balraj Preet Kaur (20370832)

"…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. 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. …"

Best optimizer results of Adaboost. حسب Balraj Preet Kaur (20370832)

"…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. 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. …"

Best optimizer results of Lightbgm. حسب Balraj Preet Kaur (20370832)

"…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. 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. …"