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complement system » component system (Expand Search), complex system (Expand Search)
system algorithm » custom algorithm (Expand Search), sssgm algorithm (Expand Search), systematic algorithm (Expand Search)
coding algorithm » cosine algorithm (Expand Search), modeling algorithm (Expand Search), finding algorithm (Expand Search)
set algorithm » best algorithm (Expand Search), new algorithm (Expand Search), em algorithm (Expand Search)
second set » second step (Expand Search)
complement system » component system (Expand Search), complex system (Expand Search)
system algorithm » custom algorithm (Expand Search), sssgm algorithm (Expand Search), systematic algorithm (Expand Search)
coding algorithm » cosine algorithm (Expand Search), modeling algorithm (Expand Search), finding algorithm (Expand Search)
set algorithm » best algorithm (Expand Search), new algorithm (Expand Search), em algorithm (Expand Search)
second set » second step (Expand Search)
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ACC and LEN for the second set of experimental algorithms.
Published 2024“…<p>This figure shows the ACC and LEN of the second set of experimental algorithms.</p>…”
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LEN and dimension reduction rates for the second set of experiments.
Published 2024“…<p>This figure shows LEN and DRR for the second set of experimental algorithms on 20 datasets.…”
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Parameter settings for metaheuristic algorithms.
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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