بدائل البحث:
learning optimization » learning motivation (توسيع البحث), lead optimization (توسيع البحث)
design optimization » bayesian optimization (توسيع البحث)
meta learning » motor learning (توسيع البحث), deep learning (توسيع البحث), e learning (توسيع البحث)
pairs design » first design (توسيع البحث), art design (توسيع البحث)
binary meta » binary data (توسيع البحث)
learning optimization » learning motivation (توسيع البحث), lead optimization (توسيع البحث)
design optimization » bayesian optimization (توسيع البحث)
meta learning » motor learning (توسيع البحث), deep learning (توسيع البحث), e learning (توسيع البحث)
pairs design » first design (توسيع البحث), art design (توسيع البحث)
binary meta » binary data (توسيع البحث)
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Table_1_An efficient decision support system for leukemia identification utilizing nature-inspired deep feature optimization.pdf
منشور في 2024"…To optimize feature selection, a customized binary Grey Wolf Algorithm is utilized, achieving an impressive 80% reduction in feature size while preserving key discriminative information. …"
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Seed mix selection model
منشور في 2022"…The model thus requires three types of data presented as matrices in order to calculate the maximum number of bee species supported by a given seed mix: 1) adult phenology of each bee species, where each cell represents whether or not that bee species was observed in the data during a given time period, 2) flowering phenology of plants, where each cell represents whether or not a bee was collected from that plant species during a given time period, and 3) pairwise interactions between plant species and bee species, where each cell represents whether each plant-bee species pair was observed interacting in the data.</p> <p> </p> <p>We applied the seed mix selection model using a binary genetic algorithm to select seed mixes (R package ‘GA’; Scrucca 2013; Scrucca 2017). …"
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Data_Sheet_1_Multiclass Classification Based on Combined Motor Imageries.pdf
منشور في 2020"…And we propose two new multilabel uses of the Common Spatial Pattern (CSP) algorithm to optimize the signal-to-noise ratio, namely MC2CMI and MC2SMI approaches. …"