بدائل البحث:
process optimization » model optimization (توسيع البحث)
using optimization » joint optimization (توسيع البحث), design optimization (توسيع البحث), step optimization (توسيع البحث)
primary data » primary care (توسيع البحث)
a process » _ process (توسيع البحث)
binary a » binary _ (توسيع البحث), binary b (توسيع البحث), hilary a (توسيع البحث)
process optimization » model optimization (توسيع البحث)
using optimization » joint optimization (توسيع البحث), design optimization (توسيع البحث), step optimization (توسيع البحث)
primary data » primary care (توسيع البحث)
a process » _ process (توسيع البحث)
binary a » binary _ (توسيع البحث), binary b (توسيع البحث), hilary a (توسيع البحث)
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Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm
منشور في 2025"…In this work, we propose a novel framework that integrates </p><p dir="ltr">Convolutional Neural Networks (CNNs) for image classification and a binary Grey Wolf Optimization (GWO) </p><p dir="ltr">algorithm for feature selection. …"
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Short overview of the primary dataset.
منشور في 2023"…Furthermore, on (HDD Mono) the SMO classifier gives the highest percentage of accuracy and less fault prediction fault in terms of 80/20 (87.72%), 70/30 (89.41%), and 5 folds cross-validation (88.38%), and (HDD-Multi) in terms of 80/20 (93.64%), 70/30 (90.91%), and 5 folds cross-validation (88.20%). Whereas, primary data results found RF classifier gives the highest percentage of accuracy and less fault prediction in terms of 80/20 (97.14%), 70/30 (96.19%), and 5 folds cross-validation (95.85%) in the primary data results, but the algorithm complexity (0.17 seconds) is not good. …"
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An Example of a WPT-MEC Network.
منشور في 2025"…To enhance the offloading decision-making process, the algorithm incorporates the Newton-Raphson method for fast and efficient optimization of the computation rate under energy constraints. …"
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Analysis and design of algorithms for the manufacturing process of integrated circuits
منشور في 2023"…The (approximate) solution proposals of state-of-the-art methods include rule-based approaches, genetic algorithms, and reinforcement learning. There is a binary integer programming model for this problem in the literature, from which its authors proposed a genetic algorithm to obtain approximate solutions. …"
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FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
منشور في 2024الموضوعات: -
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FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
منشور في 2024الموضوعات: -
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FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
منشور في 2024الموضوعات: -
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FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
منشور في 2024الموضوعات: -
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FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
منشور في 2024الموضوعات: