بدائل البحث:
policy optimization » topology optimization (توسيع البحث), wolf optimization (توسيع البحث), process optimization (توسيع البحث)
binary mask » binary image (توسيع البحث)
mask policy » risk policy (توسيع البحث)
binary 2 » binary _ (توسيع البحث), binary b (توسيع البحث)
2 global » _ global (توسيع البحث), a global (توسيع البحث), b global (توسيع البحث)
policy optimization » topology optimization (توسيع البحث), wolf optimization (توسيع البحث), process optimization (توسيع البحث)
binary mask » binary image (توسيع البحث)
mask policy » risk policy (توسيع البحث)
binary 2 » binary _ (توسيع البحث), binary b (توسيع البحث)
2 global » _ global (توسيع البحث), a global (توسيع البحث), b global (توسيع البحث)
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Data_Sheet_1_A Global Optimizer for Nanoclusters.PDF
منشور في 2019"…This method is implemented in PyAR (https://github.com/anooplab/pyar) program. The global optimization in PyAR involves two parts, generation of several trial geometries and gradient-based local optimization of the trial geometries. …"
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Table_1_A scheduling route planning algorithm based on the dynamic genetic algorithm with ant colony binary iterative optimization for unmanned aerial vehicle spraying in multiple...
منشور في 2022"…Serial fusion is subsequently employed on the two algorithms to optimize the route planning for multi-regional operations. …"
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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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Hyperparameters of the LSTM Model.
منشور في 2025"…The AD-PSO-Guided WOA overcomes limitations of conventional optimization algorithms, such as premature convergence by balancing global search (exploration) and local refinement (exploitation). …"
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The AD-PSO-Guided WOA LSTM framework.
منشور في 2025"…The AD-PSO-Guided WOA overcomes limitations of conventional optimization algorithms, such as premature convergence by balancing global search (exploration) and local refinement (exploitation). …"
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Prediction results of individual models.
منشور في 2025"…The AD-PSO-Guided WOA overcomes limitations of conventional optimization algorithms, such as premature convergence by balancing global search (exploration) and local refinement (exploitation). …"
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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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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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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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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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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. …"