Search alternatives:
driven optimization » design optimization (Expand Search), dose optimization (Expand Search), process optimization (Expand Search)
guided optimization » based optimization (Expand Search), model optimization (Expand Search)
based driven » based diet (Expand Search), wave driven (Expand Search), user driven (Expand Search)
lines based » lens based (Expand Search), genes based (Expand Search), lines used (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
driven optimization » design optimization (Expand Search), dose optimization (Expand Search), process optimization (Expand Search)
guided optimization » based optimization (Expand Search), model optimization (Expand Search)
based driven » based diet (Expand Search), wave driven (Expand Search), user driven (Expand Search)
lines based » lens based (Expand Search), genes based (Expand Search), lines used (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
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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. …”
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IRBMO vs. variant comparison adaptation data.
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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