ArticleFrontiers in neuroscience2026
SMBO: a Sinusoidal Modulation Bi-population Optimizer for brain cancer MRI image clustering.
Article in Frontiers in neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
This study proposes the Sinusoidal Modulation Bi-population Optimizer (SMBO), which couples a sinusoidal modulation of the step size, jointly driven by iteration progress and individual fitness quality, with dynamic behavior switching (DBS) to achieve a self-adaptive, threshold-free balance between exploration and exploitation. This balance is further reinforced by an asymmetric information flow (AIF) mechanism that sustains diversity between the elite and exploration sub-populations. In simulation experiments on the CEC2017 benchmark suite, SMBO achieves the lowest average rank among six compared algorithms at both
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