يعرض 1 - 20 نتائج من 221 نتيجة بحث عن '(( binary task required optimization algorithm ) OR ( binary based based optimization algorithm ))*', وقت الاستعلام: 0.67s تنقيح النتائج
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    Proposed Algorithm. حسب Hend Bayoumi (22693738)

    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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    Comparisons between ADAM and NADAM optimizers. حسب Hend Bayoumi (22693738)

    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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    MSE for ILSTM algorithm in binary classification. حسب Asmaa Ahmed Awad (16726315)

    منشور في 2023
    "…In this paper, a novel, and improved version of the Long Short-Term Memory (ILSTM) algorithm was proposed. The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …"
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    An Example of a WPT-MEC Network. حسب Hend Bayoumi (22693738)

    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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    Related Work Summary. حسب Hend Bayoumi (22693738)

    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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    Simulation parameters. حسب Hend Bayoumi (22693738)

    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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    Training losses for N = 10. حسب Hend Bayoumi (22693738)

    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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    Normalized computation rate for N = 10. حسب Hend Bayoumi (22693738)

    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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    Summary of Notations Used in this paper. حسب Hend Bayoumi (22693738)

    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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