بدائل البحث:
design optimization » bayesian optimization (توسيع البحث)
step optimization » after optimization (توسيع البحث), swarm optimization (توسيع البحث), based optimization (توسيع البحث)
binary first » bars first (توسيع البحث), binary pairs (توسيع البحث)
first design » test design (توسيع البحث), post design (توسيع البحث)
binary data » primary data (توسيع البحث), dietary data (توسيع البحث)
data step » data set (توسيع البحث)
design optimization » bayesian optimization (توسيع البحث)
step optimization » after optimization (توسيع البحث), swarm optimization (توسيع البحث), based optimization (توسيع البحث)
binary first » bars first (توسيع البحث), binary pairs (توسيع البحث)
first design » test design (توسيع البحث), post design (توسيع البحث)
binary data » primary data (توسيع البحث), dietary data (توسيع البحث)
data step » data set (توسيع البحث)
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The Pseudo-Code of the IRBMO Algorithm.
منشور في 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.
منشور في 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.
منشور في 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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Datasets and their properties.
منشور في 2023"…The binary Ebola optimization search algorithm (BEOSA) is applied for the level-1 mutation, while the simulated annealing (SA) and firefly (FFA) algorithms are investigated for the level-2 optimizer. …"
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Parameter settings.
منشور في 2023"…The binary Ebola optimization search algorithm (BEOSA) is applied for the level-1 mutation, while the simulated annealing (SA) and firefly (FFA) algorithms are investigated for the level-2 optimizer. …"
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Parameter settings of the comparison algorithms.
منشور في 2024"…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …"
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IRBMO vs. variant comparison adaptation data.
منشور في 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. …"