Search alternatives:
process optimization » model optimization (Expand Search)
robust optimization » robust estimation (Expand Search), joint optimization (Expand Search)
dynamic robust » dynamic robustness (Expand Search)
a process » _ process (Expand Search)
binary a » binary _ (Expand Search), binary b (Expand Search), hilary a (Expand Search)
process optimization » model optimization (Expand Search)
robust optimization » robust estimation (Expand Search), joint optimization (Expand Search)
dynamic robust » dynamic robustness (Expand Search)
a process » _ process (Expand Search)
binary a » binary _ (Expand Search), binary b (Expand Search), hilary a (Expand Search)
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An Example of a WPT-MEC Network.
Published 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
Published 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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Classification performance after optimization.
Published 2025“…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …”
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ANOVA test for optimization results.
Published 2025“…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …”
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Wilcoxon test results for optimization.
Published 2025“…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …”
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The flowchart of the proposed algorithm.
Published 2024“…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …”
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Datasets and their properties.
Published 2023“…The approach used in this study designed a sub-population selective mechanism that dynamically assigns individuals to a 2-level optimization process. …”
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Parameter settings.
Published 2023“…The approach used in this study designed a sub-population selective mechanism that dynamically assigns individuals to a 2-level optimization process. …”
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Image processing workflow.
Published 2020“…<p>Raw fluorescent microscope images (a) were processed with a binary segmentation algorithm, and clusters of bacterial cells were manually annotated. …”
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Multicategory Angle-Based Learning for Estimating Optimal Dynamic Treatment Regimes With Censored Data
Published 2021“…Specifically, the proposed method obtains the optimal DTR via integrating estimations of decision rules at multiple stages into a single multicategory classification algorithm without imposing additional constraints, which is also more computationally efficient and robust. …”
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Related Work Summary.
Published 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. …”