Search alternatives:
joint optimization » policy optimization (Expand Search), wolf optimization (Expand Search), codon optimization (Expand Search)
field optimization » lead optimization (Expand Search), guided optimization (Expand Search), linear optimization (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
levels based » level based (Expand Search), models based (Expand Search), cells based (Expand Search)
based field » pulsed field (Expand Search)
joint optimization » policy optimization (Expand Search), wolf optimization (Expand Search), codon optimization (Expand Search)
field optimization » lead optimization (Expand Search), guided optimization (Expand Search), linear optimization (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
levels based » level based (Expand Search), models based (Expand Search), cells based (Expand Search)
based field » pulsed field (Expand Search)
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Optimization results of MBB multi-material structure under different methods. (a) A level-set method for multi-material topology optimization [33]....
Published 2025“…(a) A level-set method for multi-material topology optimization [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0321100#pone.0321100.ref033" target="_blank">33</a>]. …”
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Parameter settings.
Published 2025“…<div><p>To improve the intelligent and refined management level of power distribution systems in equipment operation and maintenance as well as emergency support, this work proposes an integrated “prediction-optimization” model that combines genetic algorithm (GA) with machine learning methods. …”
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Indicator settings.
Published 2025“…<div><p>To improve the intelligent and refined management level of power distribution systems in equipment operation and maintenance as well as emergency support, this work proposes an integrated “prediction-optimization” model that combines genetic algorithm (GA) with machine learning methods. …”
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Parameter sets of the chosen algorithms.
Published 2024“…According to the encouraging research results in this paper, the IERWHO algorithm proposed has a place in the field of optimization.…”
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The flow chart of IERWHO algorithm.
Published 2024“…According to the encouraging research results in this paper, the IERWHO algorithm proposed has a place in the field of optimization.…”
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The flow chart of WHO algorithm.
Published 2024“…According to the encouraging research results in this paper, the IERWHO algorithm proposed has a place in the field of optimization.…”
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Function graph and algorithm iterative graph.
Published 2024“…According to the encouraging research results in this paper, the IERWHO algorithm proposed has a place in the field of optimization.…”
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The convergence curves of all the 10 algorithms.
Published 2024“…According to the encouraging research results in this paper, the IERWHO algorithm proposed has a place in the field of optimization.…”
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Algorithm flow of the GA-BPNN model.
Published 2025“…<div><p>This work explores an intelligent field irrigation warning system based on the Enhanced Genetic Algorithm—Backpropagation Neural Network (EGA-BPNN) model in the context of smart agriculture. …”
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Unsupervised Machine Learning Neural Gas Algorithm for Accurate Evaluations of the Hessian Matrix in Molecular Dynamics
Published 2021“…The algorithm belongs to the family of unsupervised machine learning methods, and it is based on the neural gas idea, where neurons are molecular configurations whose Hessians are adopted for groups of molecular dynamics configurations with similar geometries. …”
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Table 2_Intelligent grading of sugarcane leaf disease severity by integrating physiological traits with the SSA-XGBoost algorithm.docx
Published 2025“…</p>Methods<p>In this study, we propose an intelligent method for identifying sugarcane foliar disease severity based on physiological traits. Field-collected data—including Soil and Plant Analyzer Development (SPAD) values, leaf surface temperature, and nitrogen content—were acquired using a plant nutrient analyzer (TYS-4N) from sugarcane leaves infected with brown stripe disease, ring spot disease, and mosaic disease at four severity levels (mild, moderate, moderately severe, and severe). …”
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Table 1_Intelligent grading of sugarcane leaf disease severity by integrating physiological traits with the SSA-XGBoost algorithm.xlsx
Published 2025“…</p>Methods<p>In this study, we propose an intelligent method for identifying sugarcane foliar disease severity based on physiological traits. Field-collected data—including Soil and Plant Analyzer Development (SPAD) values, leaf surface temperature, and nitrogen content—were acquired using a plant nutrient analyzer (TYS-4N) from sugarcane leaves infected with brown stripe disease, ring spot disease, and mosaic disease at four severity levels (mild, moderate, moderately severe, and severe). …”
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SNR comparison of real-field seismic profile.
Published 2025“…We propose a novel seismic random noise suppression method based on enhanced variational mode decomposition (VMD) with grey wolf optimization (GWO) algorithm, which applies the envelope entropy to evaluate the wolf individual fitness, determine the grey wolf hierarchy, and obtain the optimized key elements <i><i>K</i></i> and <i>α</i> in VMD. …”
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State-Targeted Energy Projection: A Simple and Robust Approach to Orbital Relaxation of Non-Aufbau Self-Consistent Field Solutions
Published 2020“…However, orbital relaxation of a non-Aufbau determinant risks “variational collapse” back to the Aufbau solution of the self-consistent field (SCF) equations. Algorithms such as the maximum overlap method (MOM) that are designed to avoid this collapse are not guaranteed to work, and more robust alternatives increase the cost per SCF iteration. …”
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Data_Sheet_1_A Swarm Optimization Solver Based on Ferroelectric Spiking Neural Networks.PDF
Published 2019“…SI algorithms provide efficient and practical solutions to many difficult optimization problems through multi-agent metaheuristic search. …”