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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Datasets and their properties. حسب Olaide N. Oyelade (14047002)

"…To address this, we proposed a novel hybrid binary optimization capable of effectively selecting features from increasingly high-dimensional datasets. …"

Parameter settings. حسب Olaide N. Oyelade (14047002)

"…To address this, we proposed a novel hybrid binary optimization capable of effectively selecting features from increasingly high-dimensional datasets. …"

Fig 4 - حسب Olaide N. Oyelade (14047002)

Fig 7 - حسب Olaide N. Oyelade (14047002)

Wilcoxon test results for feature selection. حسب Amal H. Alharbi (21755906)

"…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …"

Feature selection metrics and their definitions. حسب Amal H. Alharbi (21755906)

"…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …"

Statistical summary of all models. حسب Amal H. Alharbi (21755906)

"…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …"

Feature selection results. حسب Amal H. Alharbi (21755906)

"…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …"

ANOVA test for feature selection. حسب Amal H. Alharbi (21755906)

"…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …"

Classification performance of ML and DL models. حسب Amal H. Alharbi (21755906)

"…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …"