بدائل البحث:
joint optimization » policy optimization (توسيع البحث), wolf optimization (توسيع البحث), codon optimization (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
final model » animal model (توسيع البحث)
binary data » primary data (توسيع البحث), dietary data (توسيع البحث)
data based » data used (توسيع البحث)
joint optimization » policy optimization (توسيع البحث), wolf optimization (توسيع البحث), codon optimization (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
final model » animal model (توسيع البحث)
binary data » primary data (توسيع البحث), dietary data (توسيع البحث)
data based » data used (توسيع البحث)
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Proposed Algorithm.
منشور في 2025"…EHRL integrates Reinforcement Learning (RL) with Deep Neural Networks (DNNs) to dynamically optimize binary offloading decisions, which in turn obviates the requirement for manually labeled training data and thus avoids the need for solving complex optimization problems repeatedly. …"
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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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The Pseudo-Code of the IRBMO Algorithm.
منشور في 2025"…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …"
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Comparisons between ADAM and NADAM optimizers.
منشور في 2025"…EHRL integrates Reinforcement Learning (RL) with Deep Neural Networks (DNNs) to dynamically optimize binary offloading decisions, which in turn obviates the requirement for manually labeled training data and thus avoids the need for solving complex optimization problems repeatedly. …"
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Values of input parameters.
منشور في 2024"…The cost includes the agency operating and user travel. The optimal design model is formulated as a mixed-integer program and solved using a fuzzy analytic hierarchy process (FAHP) and a genetic algorithm (GA). …"
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35
Display of the bilateral BRT line in Jinan.
منشور في 2024"…The cost includes the agency operating and user travel. The optimal design model is formulated as a mixed-integer program and solved using a fuzzy analytic hierarchy process (FAHP) and a genetic algorithm (GA). …"
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Fuzzy scale value.
منشور في 2024"…The cost includes the agency operating and user travel. The optimal design model is formulated as a mixed-integer program and solved using a fuzzy analytic hierarchy process (FAHP) and a genetic algorithm (GA). …"
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37
IRBMO vs. meta-heuristic algorithms boxplot.
منشور في 2025"…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …"
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IRBMO vs. feature selection algorithm boxplot.
منشور في 2025"…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …"
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