بدائل البحث:
design optimization » bayesian optimization (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
binary based » library based (توسيع البحث), linac based (توسيع البحث), binary mask (توسيع البحث)
binary task » binary mask (توسيع البحث)
task design » based design (توسيع البحث)
based based » based case (توسيع البحث), based basis (توسيع البحث), ranked based (توسيع البحث)
design optimization » bayesian optimization (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
binary based » library based (توسيع البحث), linac based (توسيع البحث), binary mask (توسيع البحث)
binary task » binary mask (توسيع البحث)
task design » based design (توسيع البحث)
based based » based case (توسيع البحث), based basis (توسيع البحث), ranked based (توسيع البحث)
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An Example of a WPT-MEC Network.
منشور في 2025"…The objective is to optimize binary offloading decisions under dynamic wireless channel conditions and energy harvesting constraints. …"
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Related Work Summary.
منشور في 2025"…The objective is to optimize binary offloading decisions under dynamic wireless channel conditions and energy harvesting constraints. …"
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Simulation parameters.
منشور في 2025"…The objective is to optimize binary offloading decisions under dynamic wireless channel conditions and energy harvesting constraints. …"
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Training losses for N = 10.
منشور في 2025"…The objective is to optimize binary offloading decisions under dynamic wireless channel conditions and energy harvesting constraints. …"
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Normalized computation rate for N = 10.
منشور في 2025"…The objective is to optimize binary offloading decisions under dynamic wireless channel conditions and energy harvesting constraints. …"
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Summary of Notations Used in this paper.
منشور في 2025"…The objective is to optimize binary offloading decisions under dynamic wireless channel conditions and energy harvesting constraints. …"
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Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results
منشور في 2025الموضوعات: -
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DE algorithm flow.
منشور في 2025"…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …"
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Test results of different algorithms.
منشور في 2025"…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …"
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Algorithm for generating hyperparameter.
منشور في 2024"…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"
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Results of machine learning algorithm.
منشور في 2024"…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"
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ROC comparison of machine learning algorithm.
منشور في 2024"…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"
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36
Pseudo Code of RBMO.
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. …"
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P-value on CEC-2017(Dim = 30).
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. …"
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Memory storage behavior.
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. …"
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Elite search behavior.
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. …"
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Description of the datasets.
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. …"