Showing 1 - 20 results of 41,166 for search '(( significant node based ) OR ( significantly ((we decrease) OR (linear decrease)) ))', query time: 3.02s Refine Results
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    The linearly decreasing convergence factor a. by Junhao Wei (6816803)

    Published 2025
    “…The performance of the canonical WOA is improved through innovative strategies: first, an initialization process using Good Nodes Set is introduced to ensure that the search starts from a higher-quality baseline; second, a distance-based guided search strategy is employed to adjust the search direction and intensity by calculating the distance to the optimal solution, which enhances the algorithm’s ability to escape local optima; and lastly, LSWOA introduces an enhanced spiral updating strategy, while the enhanced spiral-enveloping prey strategy effectively balances exploration and exploitation by dynamically adjusting the spiral shape parameters to adapt to different stages of the search, thereby more accurately updating the positions of individuals and improving convergence speed. …”
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    Trajectory scores decrease during learning. by Chenguang Zhang (457185)

    Published 2024
    “…Black lines indicate linear fits. We observed significant decreasing trends (*<i>p <</i> 0.05, * * <i>p <</i> 0.001), except for the left target for Monkey T and the downwards target for Monkey K.…”
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    Linear regression model with MBI score. by Nadia Yanet Cortés-Álvarez (18611445)

    Published 2024
    “…Furthermore, the data demonstrated a significant decrease in sBDNF levels in burnout nurses and a negative correlation between BDNF levels and burnout syndrome. …”
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    Visualization of significant effects of interventions on nodes in the broad COVID–19 attitude network. by Monique Chambon (10430218)

    Published 2022
    “…<p>See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0276439#pone.0276439.g003" target="_blank">Fig 3a</a> for node legend. The green arrow indicates a significant effect with the specific intervention included in the arrow. …”
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