Search alternatives:
phase optimization » whale optimization (Expand Search), based optimization (Expand Search), path optimization (Expand Search)
task optimization » based optimization (Expand Search), path optimization (Expand Search), dose optimization (Expand Search)
binary using » injury using (Expand Search)
binary test » binary depot (Expand Search)
using task » cueing task (Expand Search), using test (Expand Search)
test phase » test case (Expand Search)
phase optimization » whale optimization (Expand Search), based optimization (Expand Search), path optimization (Expand Search)
task optimization » based optimization (Expand Search), path optimization (Expand Search), dose optimization (Expand Search)
binary using » injury using (Expand Search)
binary test » binary depot (Expand Search)
using task » cueing task (Expand Search), using test (Expand Search)
test phase » test case (Expand Search)
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ANOVA test for optimization results.
Published 2025“…We applied this hybrid strategy to a Radial Basis Function Network (RBFN), and validated its performance improvements through extensive experiments, including ANOVA and Wilcoxon tests for both feature selection and optimization phases. …”
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Wilcoxon test results for optimization.
Published 2025“…We applied this hybrid strategy to a Radial Basis Function Network (RBFN), and validated its performance improvements through extensive experiments, including ANOVA and Wilcoxon tests for both feature selection and optimization phases. …”
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CDF of task latency, approximated as the inverse of the achieved computation rate.
Published 2025Subjects: -
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ANOVA test for feature selection.
Published 2025“…We applied this hybrid strategy to a Radial Basis Function Network (RBFN), and validated its performance improvements through extensive experiments, including ANOVA and Wilcoxon tests for both feature selection and optimization phases. …”
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Wilcoxon test results for feature selection.
Published 2025“…We applied this hybrid strategy to a Radial Basis Function Network (RBFN), and validated its performance improvements through extensive experiments, including ANOVA and Wilcoxon tests for both feature selection and optimization phases. …”
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Comparisons of computation rate performance for different offloading algorithms.for N = 10, 20, 30.
Published 2025Subjects: -
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Comparison of total time consumed for different offloading algorithms.for N = 10, 20, 30.
Published 2025Subjects: -
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The Pseudo-Code of the IRBMO Algorithm.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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IRBMO vs. meta-heuristic algorithms boxplot.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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IRBMO vs. feature selection algorithm boxplot.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”