Search alternatives:
process optimization » model optimization (Expand Search)
points optimization » joint optimization (Expand Search), potency optimization (Expand Search), policy optimization (Expand Search)
binary data » primary data (Expand Search), dietary data (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)
points optimization » joint optimization (Expand Search), potency optimization (Expand Search), policy optimization (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
a process » _ process (Expand Search)
binary a » binary _ (Expand Search), binary b (Expand Search), hilary a (Expand Search)
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Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm
Published 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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MCLP_quantum_annealer_V0.5
Published 2025“…This paper presents a quantum computing path for Transformation-to-Sampling-to-Verification of geospatial optimization problems, adaptable to the controlled qubit scale and coherence constraints under current NISQ conditions. …”
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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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