Search alternatives:
based optimization » whale optimization (Expand Search)
codon optimization » wolf optimization (Expand Search)
primary case » primary cause (Expand Search), primary care (Expand Search), primary causes (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
case based » made based (Expand Search), game based (Expand Search), rate based (Expand Search)
data codon » data code (Expand Search), data codes (Expand Search), data codings (Expand Search)
based optimization » whale optimization (Expand Search)
codon optimization » wolf optimization (Expand Search)
primary case » primary cause (Expand Search), primary care (Expand Search), primary causes (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
case based » made based (Expand Search), game based (Expand Search), rate based (Expand Search)
data codon » data code (Expand Search), data codes (Expand Search), data codings (Expand Search)
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Wilcoxon rank sum test results.
Published 2024“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”
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Wilcoxon rank sum test results.
Published 2024“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”
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Average number of selected features.
Published 2024“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”
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S1 Data -
Published 2024“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”
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Hybrid feature selection algorithm of CSCO-ROA.
Published 2024“…Next, we propose a hybrid chaotic sand cat optimization technique, together with the Remora Optimization Algorithm (ROA) for feature selection. …”
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Models’ performance without optimization.
Published 2024“…The findings indicate that the selected deep learning algorithms were proficient in forecasting COVID-19 cases, although their efficacy varied across different models. …”
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RNN performance comparison with/out optimization.
Published 2024“…The findings indicate that the selected deep learning algorithms were proficient in forecasting COVID-19 cases, although their efficacy varied across different models. …”
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Bootstrap results for Case 1.
Published 2024“…Regression models, on one side, optimize the prediction of the study variable’s non-sampled values while the classification algorithms, on the other side, look for the classification of non-sampled cases into different strata. …”
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35
Bootstrap results Case 2.
Published 2024“…Regression models, on one side, optimize the prediction of the study variable’s non-sampled values while the classification algorithms, on the other side, look for the classification of non-sampled cases into different strata. …”
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Performance metrics for BrC.
Published 2024“…Next, we propose a hybrid chaotic sand cat optimization technique, together with the Remora Optimization Algorithm (ROA) for feature selection. …”
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38
Proposed CVAE model.
Published 2024“…Next, we propose a hybrid chaotic sand cat optimization technique, together with the Remora Optimization Algorithm (ROA) for feature selection. …”
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Proposed methodology.
Published 2024“…Next, we propose a hybrid chaotic sand cat optimization technique, together with the Remora Optimization Algorithm (ROA) for feature selection. …”
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40
Loss vs. Epoch.
Published 2024“…Next, we propose a hybrid chaotic sand cat optimization technique, together with the Remora Optimization Algorithm (ROA) for feature selection. …”