بدائل البحث:
based optimization » whale optimization (توسيع البحث)
task optimization » phase optimization (توسيع البحث), path optimization (توسيع البحث), dose optimization (توسيع البحث)
library based » laboratory based (توسيع البحث)
binary data » primary data (توسيع البحث), dietary data (توسيع البحث)
based based » based case (توسيع البحث), based basis (توسيع البحث), ranked based (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
task optimization » phase optimization (توسيع البحث), path optimization (توسيع البحث), dose optimization (توسيع البحث)
library based » laboratory based (توسيع البحث)
binary data » primary data (توسيع البحث), dietary data (توسيع البحث)
based based » based case (توسيع البحث), based basis (توسيع البحث), ranked based (توسيع البحث)
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Comparison of ranks for classification algorithms across performance metrics.
منشور في 2022الموضوعات: -
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Tradeoff between execution time and predictive performance for classification algorithms.
منشور في 2022الموضوعات: -
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RosettaAMRLD: A Reaction-Driven Approach for Structure-Based Drug Design from Combinatorial Libraries with Monte Carlo Metropolis Algorithms
منشور في 2025"…The Rosetta automated Monte Carlo reaction-based ligand design (RosettaAMRLD) integrates a Monte Carlo Metropolis (MCM) algorithm and reaction-driven molecule proposal to enhance structure-based <i>de novo</i> drug discovery. …"
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The Pseudo-Code of the IRBMO Algorithm.
منشور في 2025"…To address this problem, this paper proposes an improved red-billed blue magpie algorithm (IRBMO), which is specifically optimized for the feature selection task, and significantly improves the performance and efficiency of the algorithm on medical data by introducing multiple innovative behavioral strategies. …"
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Proposed Algorithm.
منشور في 2025"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. 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. …"