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

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

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

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

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Medium-scale dataset comparative analysis using classification accuracy for population sizes 50 and 100. حسب Olaide N. Oyelade (14047002)

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A radar plot illustrating the comparison of the classification accuracy, cost values, and fitness values for the hybrids of BEOSA when applied to some high-dimensional datasets usi... حسب Olaide N. Oyelade (14047002)

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

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Fig 7 - حسب Olaide N. Oyelade (14047002)

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Fig 4 - حسب Olaide N. Oyelade (14047002)

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

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A radar plot illustrating the comparison of the classification accuracy, cost values, and fitness values for the hybrids of BEOSA when applied to some medium-sized dimensional data... حسب Olaide N. Oyelade (14047002)

الموضوعات:

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

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

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A radar plot illustrating the comparison of the classification accuracy, cost values, and fitness values for the hybrids of BEOSA when applied to some small-sized dimensional datas... حسب Olaide N. Oyelade (14047002)

الموضوعات:

Large-scale dataset comparative analysis using classification accuracy for population sizes 50 and 100. حسب Olaide N. Oyelade (14047002)

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Parameter settings. حسب Olaide N. Oyelade (14047002)

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Fig 2 - حسب Olaide N. Oyelade (14047002)

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The Pseudo-Code of the IRBMO Algorithm. حسب Chenyi Zhu (9383370)

"…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. …"

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

"…<div><p>Modern sustainable farming demands precise water management techniques, particularly for crops like potatoes that require high-quality irrigation to ensure optimal growth. This study presents a novel hybrid metaheuristic framework that combines Dipper Throated Optimization (DTO), a bio-inspired algorithm modeled on bird foraging behavior, with Polar Rose Search (PRS) to enhance deep learning models in predictive water quality assessment. …"

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

"…<div><p>Modern sustainable farming demands precise water management techniques, particularly for crops like potatoes that require high-quality irrigation to ensure optimal growth. This study presents a novel hybrid metaheuristic framework that combines Dipper Throated Optimization (DTO), a bio-inspired algorithm modeled on bird foraging behavior, with Polar Rose Search (PRS) to enhance deep learning models in predictive water quality assessment. …"