بدائل البحث:
initialization algorithm » optimization algorithms (توسيع البحث), maximization algorithm (توسيع البحث), identification algorithm (توسيع البحث)
resource initialization » resource utilization (توسيع البحث), resource utilisation (توسيع البحث), resource optimization (توسيع البحث)
wolf optimization » whale optimization (توسيع البحث), swarm optimization (توسيع البحث), _ optimization (توسيع البحث)
binary data » primary data (توسيع البحث), dietary data (توسيع البحث)
initialization algorithm » optimization algorithms (توسيع البحث), maximization algorithm (توسيع البحث), identification algorithm (توسيع البحث)
resource initialization » resource utilization (توسيع البحث), resource utilisation (توسيع البحث), resource optimization (توسيع البحث)
wolf optimization » whale optimization (توسيع البحث), swarm optimization (توسيع البحث), _ optimization (توسيع البحث)
binary data » primary data (توسيع البحث), dietary data (توسيع البحث)
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1
The flowchart of the proposed algorithm.
منشور في 2024"…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …"
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2
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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3
Summary of literature review.
منشور في 2024"…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …"
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4
Topic description.
منشور في 2024"…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …"
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5
Notations along with their descriptions.
منشور في 2024"…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …"
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6
Detail of the topics extracted from DUC2002.
منشور في 2024"…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …"
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8
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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9
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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10
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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11
Table_1_An efficient decision support system for leukemia identification utilizing nature-inspired deep feature optimization.pdf
منشور في 2024"…Next, a hybrid feature extraction approach is presented leveraging transfer learning from selected deep neural network models, InceptionV3 and DenseNet201, to extract comprehensive feature sets. To optimize feature selection, a customized binary Grey Wolf Algorithm is utilized, achieving an impressive 80% reduction in feature size while preserving key discriminative information. …"
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Seed mix selection model
منشور في 2022"…</p> <p> </p> <p>We applied the seed mix selection model using a binary genetic algorithm to select seed mixes (R package ‘GA’; Scrucca 2013; Scrucca 2017). …"