Feature selection convergence time comparison of various binary metaheuristic algorithms. حسب Amal H. Alharbi (21755906)

The flowchart showing the optimization process of the hybrid methods using BEOSA as the base algorithm and SA and FFA as integrated algorithms. حسب Olaide N. Oyelade (14047002)

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<i>hi</i>PRS algorithm process flow. حسب Michela C. Massi (14599915)

Schematic of iteration process of IDE-IIGA. حسب Ling Zhao (111365)

Histograms of various water quality parameters, including pH, Hardness, Solids, Chloramines, Sulfate, Organic Carbon, Trihalomethanes, Turbidity, and a binary portability check. حسب Amal H. Alharbi (21755906)

Proposed Algorithm. حسب Hend Bayoumi (22693738)

"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. EHRL integrates Reinforcement Learning (RL) with Deep Neural Networks (DNNs) to dynamically optimize binary offloading decisions, which in turn obviates the requirement for manually labeled training data and thus avoids the need for solving complex optimization problems repeatedly. …"

Homomorphic binary tree. حسب Jianhua He (341366)

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

"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. EHRL integrates Reinforcement Learning (RL) with Deep Neural Networks (DNNs) to dynamically optimize binary offloading decisions, which in turn obviates the requirement for manually labeled training data and thus avoids the need for solving complex optimization problems repeatedly. …"

Classification performance after optimization. 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 optimization 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. …"

Wilcoxon test results for optimization. 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. …"

The workflow diagram for the gene expression biomarker study which involve using principal component analysis (PCA) to reduce the number of features (principal components), thus re... حسب Aninda Astuti (21736334)

An optimization process of the proposed hybrid BEOSA (HBEOSA) combining both SA and FFA methods into BEOSA. حسب Olaide N. Oyelade (14047002)

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An illustration and comparison of the fitness convergence curves for the Large-scale dataset (WaveformEW), medium-scale dataset (Zoo dataset), and Small-scale (Wine dataset) using... حسب Olaide N. Oyelade (14047002)

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Medium-scale dataset comparative analysis using fitness and cost values for population size 50 and 100. حسب Olaide N. Oyelade (14047002)

الموضوعات:

Large-scale dataset comparative analysis using computation resources. حسب Olaide N. Oyelade (14047002)

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

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An illustration and comparison of the cost convergence curves for the Large-scale dataset (WaveformEW), medium-scale dataset (Zoo dataset), and Small-scale (Wine dataset) using 50... حسب Olaide N. Oyelade (14047002)

الموضوعات:

Small-scale dataset comparative analysis using fitness and cost values for population sizes 50 and 100. حسب Olaide N. Oyelade (14047002)

الموضوعات:

Medium-scale dataset comparative analysis using the number of features selected. حسب Olaide N. Oyelade (14047002)

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