بدائل البحث:
allocation algorithm » location algorithm (توسيع البحث), selection algorithm (توسيع البحث), detection algorithm (توسيع البحث)
guided optimization » based optimization (توسيع البحث), model optimization (توسيع البحث)
binary data » primary data (توسيع البحث), dietary data (توسيع البحث)
a resource » _ resource (توسيع البحث), _ resources (توسيع البحث), low resource (توسيع البحث)
binary a » binary _ (توسيع البحث), binary b (توسيع البحث), hilary a (توسيع البحث)
allocation algorithm » location algorithm (توسيع البحث), selection algorithm (توسيع البحث), detection algorithm (توسيع البحث)
guided optimization » based optimization (توسيع البحث), model optimization (توسيع البحث)
binary data » primary data (توسيع البحث), dietary data (توسيع البحث)
a resource » _ resource (توسيع البحث), _ resources (توسيع البحث), low resource (توسيع البحث)
binary a » binary _ (توسيع البحث), binary b (توسيع البحث), hilary a (توسيع البحث)
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1
Dynamic resource allocation process.
منشور في 2025"…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …"
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2
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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3
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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4
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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5
Confusion matrix.
منشور في 2025"…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …"
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6
Parameter settings.
منشور في 2025"…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …"
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7
Event-driven data flow processing.
منشور في 2025"…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …"
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8
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. …"
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9
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10
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11
Pseudo Code of RBMO.
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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12
P-value on CEC-2017(Dim = 30).
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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13
Memory storage behavior.
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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14
Elite search behavior.
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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15
Description of the datasets.
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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16
S and V shaped transfer functions.
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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17
S- and V-Type transfer function diagrams.
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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18
Collaborative hunting behavior.
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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19
Friedman average rank sum test results.
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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20
MCLP_quantum_annealer_V0.5
منشور في 2025"…This approach is applicable to urban service facility planning, Internet of Things (IoT) and communication facility spatial deployment, smart city governance, and resource allocation.</p>…"