بدائل البحث:
learning optimization » learning motivation (توسيع البحث), lead optimization (توسيع البحث)
cosmic optimization » cost optimization (توسيع البحث), chemical optimization (توسيع البحث), dynamic optimization (توسيع البحث)
data learning » meta learning (توسيع البحث), deep learning (توسيع البحث), a learning (توسيع البحث)
binary data » primary data (توسيع البحث), dietary data (توسيع البحث)
binary a » binary _ (توسيع البحث), binary b (توسيع البحث), hilary a (توسيع البحث)
a cosmic » _ cosmic (توسيع البحث), a comic (توسيع البحث)
learning optimization » learning motivation (توسيع البحث), lead optimization (توسيع البحث)
cosmic optimization » cost optimization (توسيع البحث), chemical optimization (توسيع البحث), dynamic optimization (توسيع البحث)
data learning » meta learning (توسيع البحث), deep learning (توسيع البحث), a learning (توسيع البحث)
binary data » primary data (توسيع البحث), dietary data (توسيع البحث)
binary a » binary _ (توسيع البحث), binary b (توسيع البحث), hilary a (توسيع البحث)
a cosmic » _ cosmic (توسيع البحث), a comic (توسيع البحث)
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Mean fitness and standard deviation results of compared approaches on CEC2019 benchmark functions.
منشور في 2022الموضوعات: -
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The result of the Wilcoxon test of presented COFFO against compared methods.
منشور في 2022الموضوعات: -
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Convergence graphs for ten CEC 2019 benchmark functions and direct comparison between COFFO and FFO.
منشور في 2022الموضوعات: -
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Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things
منشور في 2025"…Hence, Binary Black Widow Optimization Algorithm (BBWOA) is proposed in this manuscript to improve the BRBPNN classifier that detects intrusion precisely. …"
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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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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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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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Effects of Class Imbalance and Data Scarcity on the Performance of Binary Classification Machine Learning Models Developed Based on ToxCast/Tox21 Assay Data
منشور في 2022"…However, ToxCast assays differ in the amount of data and degree of class imbalance (CI). Therefore, the resampling algorithm employed should vary depending on the data distribution to achieve optimal classification performance. …"
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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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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. …"